Author: Thirunavukkarasu K

10 Real Agentic AI Use Cases Transforming Corporate Skilling in 2026

Agentic AI is rapidly moving from experimentation to enterprise adoption, and corporate learning is emerging as one of its most promising applications. From personalized learning journeys to real-time mentoring, agentic AI use cases are redefining how organizations build, validate, and deploy workforce capabilities. As enterprises look to close skill gaps faster and prepare employees for an AI-driven future, a new set of trends is beginning to shape the future of corporate learning.

What Makes An AI Agent “agentic” in Corporate Learning? 

Unlike a chatbot that waits for a prompt, an agentic AI system observes, decides, and acts; assessing a learner’s skill level, flagging a capability gap, recommending the next module, and adjusting the path the moment performance data changes.  

An agentic AI system is distinguished by four traits: 

1. It acts as an autonomous learning agent rather than waiting for every instruction 
2. It works toward a defined goal rather than a single output 
3. It improves from experience instead of repeating a fixed script 
4. It interacts directly with its environment; pulling data from an LMS, an HRIS, or a project tool to decide its next action 

Explore our in-depth AI in HR guide to understand how AI is transforming every stage of the employee lifecycle, from hiring and onboarding to learning, talent management, and workforce planning.

10 Agentic AI Use Cases Already Running in Corporate L&D

Gartner projects that 40% of enterprise applications will embed task-specific AI agents by the end of 2026, up from less than 5% in 2025; one of the fastest technology adoption curves the enterprise software market has seen. If you lead Learning & Development, Talent Management, Workforce Transformation, or Enterprise Skilling initiatives, these are 10 Agentic AI use cases worth knowing. 

1. Autonomous Onboarding Agents

AI tools are transforming HRTech in many ways. Employee onboarding is usually the first place agentic systems get deployed. These agents assign personalized learning paths, surface resources at the right moment, answer routine questions via AI chat, and track completion automatically, learning from every interaction to refine the next hire’s journey.  

2. Self-Managing Compliance Training

Compliance is repetitive by design, making it an ideal candidate for agentic ownership. Instead of relying on L&D coordinators to manually track certification expiries in spreadsheets, AI-driven employee training systems continuously monitor compliance, auto-assign refresher modules, generate audit-ready dashboards. 

3. Adaptive, Personalized Learning Journeys

This is arguably the most cited of all agentic AI use cases, and for good reason; generic learning paths fail the moment a workforce has mixed experience levels. An AI agent continuously reads learner behavior, performance, and feedback, then adjusts content difficulty, skips mastered topics, and recommends the next-best module in real time. 

4. AI-Powered Skills Gap Analysis

Static skill matrices go stale the moment they’re published. Agentic AI in HR continuously integrates data from HR systems, performance reviews, and learning activity to maintain a live view of workforce skills and organizational capability. 

5. Real-Time Learning Analytics and Intervention

Traditional L&D analytics report on what has already happened. Agentic systems intervene while it’s still happening. It reads engagement signals, quiz performance, and participation to detect a disengaging learner and automatically deploying a nudge before that learner drops off entirely.

6. Automated Feedback Loops and Course Optimization

Post-training feedback is usually collected, then ignored for months. Agents surface what’s failing inside a no-code dashboard, and let L&D teams adjust content, pacing, or delivery style immediately.

7. Document-to-Course Content Generation

Course creation is one of L&D’s most expensive bottlenecks; turning SOPs, manuals, and technical documents into structured learning content can take weeks per program. AI-driven employee training addresses this challenge by enabling intelligent content builders to read source documents, extract learning objectives, and automatically generate structured learning modules that L&D teams can review and refine.

8. Contextual Microlearning, Delivered on Demand

Agentic systems deliver a short, relevant lesson at the exact moment it’s useful; a leadership tip before a 1:1, a compliance refresher before an audit, directly inside the tools people already use, like Slack or Teams. 

9. Reinforcement Learning for Knowledge Retention

The forgetting curve is L&D’s oldest problem, and agentic reinforcement is one of the more durable fixes. After a course ends, the agent schedules follow-up micro-quizzes, sends spaced summaries, and prompts scenario-based challenges to keep key concepts active in memory rather than letting them decay.  

10. Automated ROI and Business-Impact Measurement

Proving L&D’s business impact has historically required manually correlating training records with performance data. Agentic dashboards now pull from the LMS, HRIS, CRM, and project tools simultaneously, correlating learning activity with productivity, engagement, or sales metrics in a continuously updating view. A telecom enterprise using this approach cut analysis time by 90% while giving leadership a far more transparent picture of training ROI. 

How Tekstac Brings Agentic AI Use Cases into Enterprise Skilling 

SAP’s Value of AI Report 2026 projects that Indian enterprises will increase Agentic AI investment fivefold over the next two years. As organizations accelerate adoption, the challenge is no longer access to AI technology; it’s building the workforce capabilities required to use it effectively. 

That challenge became evident for one of the world’s top five IT consulting and services organizations. Despite significant investments in AI learning programs, very few engineers had hands-on experience building and deploying multi-agent systems in production environments. 

To bridge that gap, the organization partnered with Tekstac in January 2026 to launch a 1,200-engineer Agentic AI Project Accelerator. Designed around a project-first approach, the four-week program required engineers to build and deploy live multi-agent applications using CrewAI and LangGraph on real AWS and Azure environments. Every stage of the development process was automatically evaluated, scored, and supported with instant feedback. 

The results are measured the way the thesis demands. In the first batch of 340 engineers, 40% have already built and shipped production Agentic AI applications, with 100% of project delivery auto-evaluated against capability rather than attendance.  

Agentic AI For 2026 And Beyond 

AI fluency at work is already a thing, and the enterprise adoption curve is accelerating. And the most impactful agentic AI use cases are already moving beyond pilots into real-world workforce transformation initiatives. 

For L&D and talent leaders, the opportunity is not simply to automate existing processes, but to rethink how skills are developed, measured, and applied at scale. Organizations that act now will be better positioned to build the workforce agility required in an AI-driven future. 

Ready to accelerate your enterprise’s Agentic AI journey?

Book a demo to see how Tekstac can help your teams build production-ready Agentic AI capabilities.

FAQs on Agentic AI use cases

1. What do you mean by Agentic AI use cases in corporate skilling?

Agentic AI use cases in corporate skilling refer to applications where AI agents can autonomously assess, decide, and take actions to support workforce development. Common agentic AI use cases include personalized learning journeys, skills gap analysis, onboarding automation, compliance management, learning analytics, coaching assistants, content generation, and workforce readiness tracking.

2. What type of AI agents are used in corporate upskilling initiatives?

Corporate upskilling initiatives typically use a combination of specialized AI agents rather than a single AI assistant.

Some of the most common types include:

• Learning Recommendation Agents that personalize learning paths based on skills, role requirements, and career goals.
• Skills Assessment Agents that identify capability gaps and recommend targeted interventions.
• Analytics Agents that track engagement, measure learning effectiveness, and correlate learning outcomes with business performance.

3. What are some popular Agentic AI certifications and learning programs?

Popular options include certifications and programs focused on AI agents, multi-agent systems, LLM orchestration, autonomous workflows, and AI application development. To address this need, Tekstac offers specialized Agentic AI capability-building programs for enterprises.

Some commonly pursued learning paths offered by Tekstac:

• CrewAI
• LangGraph
• AutoGen
• LangChain

4. How does Agentic AI improve enterprise learning and workforce upskilling?

Agentic AI improves enterprise learning by moving beyond static training programs to deliver personalized, adaptive, and outcome-driven learning experiences. Unlike traditional AI tools that simply respond to prompts, AI agents can autonomously assess employee skill levels, identify capability gaps, recommend tailored learning pathways, provide real-time coaching, and continuously adapt learning based on performance and business needs.

Top 15 HR and L&D Leaders Making an Impact in 2026

As organizations navigate AI disruption, digital transformation, and evolving workforce expectations, a new generation of HR and L&D leaders in India is redefining how talent is built, nurtured, and retained. 

Across India’s leading enterprises, these visionaries are driving enterprise-wide reskilling, leadership development, organizational transformation, and capability-building initiatives that prepare businesses for tomorrow’s challenges. Their work goes beyond training programs; they are shaping cultures of continuous learning, building future-ready leaders, and ensuring organizations remain competitive in an AI-driven world. 

15 HR and L&D Leaders Shaping the Future of Work in 2026

Here’s a look at some of the most influential HR and L&D leaders making an impact in 2026.

1. Sivakumaran Ranganathan

Enterprise L&D and Talent Transformation Leader | Infosys BPM 

With over 2 decades of experience, Sivakumaran Ranganathan has emerged as a leading force in enterprise learning transformation. He has successfully aligned large-scale reskilling initiatives with business outcomes, enabling organizations to build future-ready talent pipelines across technology and services sectors. His expertise spans capability building, leadership development, role readiness, and digital skilling strategies that accelerate productivity and business growth. 

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2. Simren Mehn

Practice Lead – OD & Senior Leadership Development (Global) | Amdocs 

Simren Mehn is widely recognized for blending organizational development with leadership transformation and AI-driven talent strategies. With more than 18 years of experience, she has designed global leadership programs, executive coaching ecosystems, succession frameworks, and AI-powered capability initiatives that drive measurable business impact. Her human-centered approach, combined with deep expertise in inclusion and organizational design, has made her one of India’s most respected L&D leaders. 

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3. Biju Mathew

Director – Learning Design & Development | Dell Technologies 

With more than 30 years of industry experience, Biju Mathew has played a pivotal role in advancing digital learning and enterprise capability development at Dell Technologies. His expertise spans learning design, customer experience transformation, technical enablement, and global training operations. His leadership has consistently contributed to strengthening learning ecosystems that support digital transformation at scale. 

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4. Bobby Joy

Senior Director – Innovation and Learning, Technology and Product | Salesforce 

Bobby Joy is a globally recognized talent development leader with over 25 years of experience in leadership development, innovation, and organizational learning. An executive coach and industry thought leader, he has influenced learning strategies across multinational organizations while speaking at leading global forums including Brandon Hall, NASSCOM, and Zinnov. His passion for building high-performing teams continues to shape next-gen learning practices. 

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5. Aishwarya Iyer

Talent Development Leader | Walmart Global Tech India 

Aishwarya Iyer leads enterprise talent development initiatives focused on leadership growth, workforce capability building, manager enablement, and future-skills readiness. Known for her learner-centric and data-driven approach, she combines organizational psychology with strategic learning design to build scalable learning ecosystems. Her work continues to empower technology talent through inclusive and experience-led development programs. 

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6. Madhurya Hariharan

People and Talent Leader – India Technology Center | Lennox 

Madhurya Hariharan brings nearly 2 decades of experience across talent development, HR strategy, analytics, and organizational transformation. From building large cloud and data organizations to leading talent initiatives across North America and India, she has consistently helped businesses navigate technology shifts through people-centric strategies. Her passion for innovation, workforce analytics, and leadership development makes her a prominent voice in India’s HR landscape. 

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7. Palekar Anand

Executive Director – Talent and Learning | Wells Fargo 

Palekar Anand has built an impressive career spanning banking, financial services, and GCCs, leading learning and talent functions across organizations including Wells Fargo, WNS Global Services, DSP Merrill Lynch, and Standard Chartered Bank. With nearly two decades of leadership experience, he has been instrumental in shaping enterprise learning strategies, leadership development frameworks, and organizational capability-building initiatives that support business transformation at scale. 

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8. Srikanth Vachaspati

Vice President & Head – People & Organization | Siemens Technology and Services 

With over three decades of global HR leadership experience, Srikanth Vachaspati has led large-scale people transformations across multinational organizations. His expertise spans organizational change, leadership coaching, cultural integration, and HR strategy, making him a key driver of future-ready workplaces that balance business growth with people excellence. 

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9. Shefali Sharma Garg

Chief Talent Officer | Publicis Sapient India 

Shefali Sharma Garg is a strategic talent leader known for building high-performing organizations through innovative people-centric practices. With deep expertise across talent management, leadership development, employee engagement, organizational design, and HR transformation, she has consistently aligned people strategy with business priorities to drive sustainable growth and performance. 

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10. Thomas Raj

Global Talent & Learning Leader | Neurealm 

Thomas Raj is a seasoned HR and L&D leader championing AI-powered workforce transformation. From establishing enterprise AI Skilling Academies to redesigning onboarding and learning ecosystems that deliver measurable business impact, his work demonstrates how strategic talent development can accelerate organizational agility and innovation at scale. 

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11. Krishnan Nilakantan

Chief Learning Officer | UST 

Krishnan Nilakantan, popularly known as NK, is one of India’s most respected learning leaders with nearly three decades of experience in organizational transformation and capability development. Renowned for modernizing corporate learning through technology and business-aligned strategies, he has been recognized among the country’s top CLOs for driving continuous learning cultures that deliver measurable business outcomes. 

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12. Jagatheesh Jayanand

Head – Learning & Development | Tata Electronics 

Jagatheesh Jayanand leads learning and talent transformation for one of India’s fastest-growing manufacturing organizations, driving capability building for a workforce of over 70,000 associates. Drawing from extensive experience across consulting, manufacturing, and technology services, he focuses on integrating business strategy with innovative learning solutions to build agile and future-ready talent.

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13. Anamika Sinha

Head of People & Culture | Centrico India 

Anamika Sinha brings more than two decades of HR leadership experience across workforce transformation, people strategy, and organizational development. Passionate about leveraging AI and digital technologies in HR, she combines data-driven decision-making with inclusive talent practices to create employee experiences that foster innovation, collaboration, and long-term growth. 

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14. Aruna Nair Pawaskar

Director – People Learning Lead | Deloitte South Asia

Aruna Nair Pawaskar leads learning strategy for Deloitte South Asia, designing enterprise-wide capability development aligned with business priorities and global talent strategies. Her expertise lies in competency-based learning, curriculum design, stakeholder collaboration, and analytics-driven learning interventions that strengthen organizational capability across every career stage. 

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15. Seema Acharya

Global Head of Learning | GlobalLogic 

Seema Acharya is a global learning leader driving digital transformation through enterprise-wide capability building and AI-enabled learning ecosystems. With over 25 years of experience spanning technology and education, she has successfully scaled technical academies and workforce upskilling initiatives that position learning as a strategic business advantage rather than a support function. 

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The L&D Leaders Shaping India’s AI-Ready Workforce

As AI reshapes industries and skills evolve faster than ever, the role of the L&D leader has become one of the most influential positions in the modern enterprise.  In 2026, India’s most impactful HR and L&D leaders are proving that the future of business will belong to organizations that invest in learning with the same intensity as they invest in technology. Their work serves as a blueprint for building agile, resilient, and future-ready workforces that can thrive through constant change. 

Tekstac vs. Degreed: Which Platform Builds Better Enterprise Skills in 2026?

Between Tekstac vs. Degreed, choosing an enterprise learning platform in 2026 is not a simple decision. The platform you choose will determine whether your workforce can prove their skills or merely complete courses. Those are not the same outcome.

Tekstac is built to verify skills. Degreed is built to aggregate content. If your organization needs to demonstrate workforce capability for project allocation, compliance reporting, or talent decisions, that distinction matters enormously.

Two platforms frequently appear on enterprise L&D shortlists: Tekstac and Degreed. This guide breaks down both across every dimension that matters for enterprise procurement: features, assessments, analytics, integrations, pricing, and security.

What is Tekstac? 

Tekstac is an AI-first skills intelligence platform built specifically for IT enterprises, Global Capability Centers (GCCs), and tech-led organizations. Its mission is unambiguous: transform how enterprises build, measure, and verify skills at scale. 

As a strong Degreed alternative, Tekstac combines four core capabilities into one unified platform: hands-on labs, auto-evaluated assessments, AI-powered proctoring, and skill gap analytics. Every feature is engineered to close the gap between ‘training completed’ and ‘skill proven’. 

Over 1 million professionals have been trained on the platform. Enterprise clients include Accenture, Cognizant, and Capgemini, among others. Tekstac has maintained a 100% uptime track record across tens of thousands of simultaneous learning journeys and concurrent assessments. 

Key Tekstac Capabilities 

• Hands-on Labs: Sandbox environments covering a wide range of technologies; learners practice real-world scenarios without needing external tools. Instant post-session feedback and step-by-step guidance accelerate skill adoption. 
• Auto-Evaluated Assessments: Quizzes, coding tasks, video assessments, and case-based evaluations with real-time results. Gamified with XP points, badges, and leaderboards to drive sustained engagement. 
• AI-Powered Proctoring: Monitors webcam, screen, and audio activity in real time. Configurable across coding, video, essay, and MCQ formats. Generates audit trails for compliance and leadership review. 
• Plagiarism Detection: Built into every code submission, automatically. Not an add-on — a standard part of every assessment. 
• Skills Gap Analysis: Data-driven skill insights identifying individual and team-level gaps against role-specific benchmarks. Integrated with the Skill Inventory and Growth Path Analyzer for continuous capability planning. 
• Learning Paths: Personalized, role-aligned pathways with LTI integration, gamified milestones, and industry-aligned tech content across AI, cloud, data analytics, and full-stack development. 
• Enterprise Scalability: Efficiently manages tens of thousands of simultaneous learning journeys and concurrent assessments without performance degradation. 
• Security & Compliance: ISO 27001 (2023) certified, SOC2 Type II compliant, GDPR-ready, with AI proctoring audit trails for regulated industries. 

What is Degreed? 

Degreed is a Learning Experience Platforms (LXPs) to aggregate content from multiple sources into a single employee interface.  

Degreed’s model is that of a content aggregator: it pulls from premium providers, internal libraries, self-generated material, and open-source resources, and surfaces it in one place. Its core assumption is that your organization already has strong content partnerships. If that assumption holds, Degreed can be a useful aggregation layer. If it does not, the platform’s value diminishes significantly.

Key Degreed Capabilities 

• Content Aggregation: Pulls from premium content providers (edX, Cybrary, Ethena), internal content libraries, self-generated material, and open-source resources. 
• Daily Learning Digest: Personalized daily email recommending relevant videos, courses, and articles based on each learner’s skill profile. Frequently cited as the platform’s most-used feature. 
• AI-Driven Skill Intelligence: Identifies skill gaps across the organization, generates personalized learning pathways, and connects learning activity to career opportunity. 
• Social Learning: Peer skill ratings, follow colleagues’ learning journeys, comment and collaborate on pathways, share knowledge across teams. 
• Internal Mobility: Identifies internal talent, maps skills to open roles, and makes career advancement pathways visible to employees. 

Tekstac vs. Degreed: Side-by-Side Feature Comparison

How Tekstac and Degreed Compare Across Key Capabilities

Both enterprise skilling platforms have unique features that offer.

1. Learning Experience & Content Delivery

Tekstac

Tekstac’s enterprise learning platform is built around doing, not watching. It provides personalized learning paths that blend course modules with hands-on coding labs, simulations, and skill assessments at scale. 

Learners progress through gamified milestones, earning XP points, badges, and rankings on company-wide leaderboards. The platform is mobile-ready with progress saved in real time, and lab environments cover a wide range of tech stacks without requiring external tools. 

Critically, Tekstac owns its content library. But the platform is also open to integrating content from third-party providers based on the client’s request.

Degreed 

Degreed’s learning experience centers on content discovery and curation. The platform aggregates learning from premium content providers, internal libraries, self-generated material, and open-source resources, making all of it accessible in one interface. 

The Daily Learning Digest, a personalized daily email recommending videos, courses, and articles, is Degreed’s signature engagement driver. For organizations with rich content partnerships, this model works. For organizations with thin or inconsistent content libraries, the experience suffers proportionally.  

Best Choice: Tekstac excels for hands-on technical skilling and labs, while Degreed is stronger for content aggregation and learning discovery. 

2. Assessments & Skills Measurement

According to the Economic Graph X LinkedIn Report 2025, adopting a skills-based hiring approach can expand the global talent pool by as much as 6.1 times. 

It is an important deciding factor for most enterprise buyers in every organization.  

Tekstac: Verified Skill Proof 

Tekstac’s skill assessment architecture is designed around one principle: you cannot manage what you cannot measure with certainty. The platform delivers: 

• Auto-evaluated assessments across coding tasks, video submissions, MCQs, and case-based evaluations — results generated in real time, no manual grading 
• AI proctoring with webcam, screen, and audio monitoring: configurable by assessment type and compliance requirement 
• Plagiarism detection built into every code submission: standard, not optional 
• Role-level benchmarking that maps individual proficiency against industry standards 
• Personalized feedback after every assessment: specific step-by-step guidance, not generic scores 

 Skill Development Dashboard of Tekstac Platform

AI proctoring is particularly important for enterprise decisions around promotions, certifications, and project readiness. When an L&D leader signs off on a team’s cloud competency, they need to know those skills are real, not self-reported.

Degreed: Self-Reported Scores, Not Verified Skills

Degreed’s Learning Experience Platform measures skills differently. Skill levels on Degreed are established through self-assessments, peer ratings, and completion data from connected content. Learners create skill profiles that reflect what they have studied and how peers rate their capabilities. 

This model provides broad workforce visibility; L&D leaders can see org-wide skill distribution across hundreds of competencies. But it does not provide the proctored, independently verified measurement that compliance-regulated environments or high-stakes talent decisions require. 

Best Choice: Tekstac, for AI-proctored assessments, hands-on evaluations, and verified skill validation.

3. Analytics & Reporting

Tekstac 

Tekstac’s analytics stack is built for L&D decision-making, not just reporting. Customizable dashboards provide real-time visibility into individual and team learning journeys, skill-wise performance trends, cohort benchmarks, and time-spent patterns. 

The Skill Inventory and Growth Path Analyzer give HR and L&D leaders a live view of workforce capability with skill gap analysis and projecting where they will emerge. Learning ROI tracking connects training investment directly to skill outcomes, giving business stakeholders the data they need to justify L&D spending. The data also provides a broad picture of who needs to be a part of organization’s upskilling and reskilling initiatives.

At scale, the skills intelligence platform manages tens of thousands of concurrent assessments and learning journeys without performance issues. 

Degreed 

Degreed’s analytics center on skill insights at the organizational level; skill gap dashboards, engagement trends, content performance data, and career pathway analytics. The platform surfaces which skills are in demand across the organization for workforce transformation. 

Reporting depth increases with integrations, particularly Workday. For organizations already invested in Workday, this integration adds analytics value; though it means your reporting quality depends on a third-party integration holding, not native platform capability. A change in Workday configuration or contract affects what Degreed can surface. 

Where Degreed’s analytics fall short is individual skill verification: the platform can tell you what employees have engaged with, but not whether they can demonstrate the skill under controlled conditions.  

Best Choice: Tekstac, for organizations focused on skill gap analysis, learning ROI, and workforce capability measurement. Degreed is better suited for tracking learning engagement and content consumption. 

Degreed’s Skill Inventory Dashboard

4. Platform Framework

Tekstac

Unlike generic training platforms that offer the same content to everyone, Tekstac enables role-based skill development through competency frameworks tailored to specific job roles such as Backend Developer, Cloud Engineer, QA Engineer, and more. Learning paths, hands-on labs, and assessments are aligned to clearly defined proficiency levels, from Foundation to Practitioner to Advanced. 

By mapping learning directly to real-world job expectations, organizations can eliminate irrelevant training and accelerate capability building. This approach has also helped enterprises create targeted upskilling programs for internal mobility.

Degreed

Degreed uses a skills intelligence framework that helps organizations identify, measure, and develop workforce capabilities at scale. Learning content is mapped to skills and proficiency levels, enabling personalized recommendations based on an employee’s current skills, career aspirations, and organizational priorities. Through skill taxonomies, proficiency ratings, and skill-to-role mapping, organizations can gain visibility into skill gaps and align development initiatives with business needs.

Best Choice: Tekstac, for role-based competency development and structured technical capability building, while Degreed offers a broader skills intelligence framework for enterprise learning. 

Tekstac vs. Degreed: Which Platform Should You Choose?

Both workforce upskilling platforms primarily focus on employee training and development; and your procurement shortlist likely includes both. Here is the clearest way to decide. 

The Decision Framework 

Choose Tekstac when your priority is: 

  → Verifying that employees can actually do the job, not just complete a course 

  → Running proctored assessments at scale for IT, GCC, or compliance-regulated roles 

  → Building deep technical skills in AI, cloud, and data with owned labs and content 

  → Generating audit trails that make talent decisions defensible 

Consider Degreed when: 

  → You already have active content provider subscriptions and need a unified aggregation layer 

  → Your L&D scope spans non-technical functions across a large cross-functional enterprise 

  → You are already on Workday and the native integration is a strategic requirement 

Choosing the Right Enterprise Learning Platform for 2026

While both platforms support enterprise learning and workforce development, they address different organizational priorities. The right choice ultimately depends on whether your focus is on building measurable technical capabilities or delivering a broad, content-driven learning experience. 

Take the next step toward workforce transformation. Book a Tekstac Demo today and experience how our platform delivers measurable skill development through hands-on learning and capstone projects at scale. 

Frequently Asked Questions on Degreed Alternatives

1. Is Tekstac better than Degreed? 

For IT enterprises and GCCs, yes — Tekstac is purpose-built for deep tech skill assessment, AI proctoring, and verified skill measurement that compliance-regulated environments require. Degreed suits organizations that already have strong content subscriptions and need a broad LXP.

2. Is Tekstac GDPR compliant? 

Yes. Tekstac is ISO 27001 (2023) certified, SOC2 Type II compliant, and GDPR-ready, with AI proctoring audit trails that support compliance reporting in regulated industries. 

3. What is a Degreed alternative for tech enterprises? 

Tekstac is the leading Degreed alternative for IT enterprises and GCCs that require proctored assessments, hands-on labs, and verified skill measurement. Other platforms in the comparison include Cornerstone, EdCast, and TalentLMS — but none combine technical skill depth with assessment integrity at the level Tekstac delivers. 

4. What is Degreed’s core risk? 

Degreed is like a smart TV; it is only as valuable as the content services you pay for to watch on it.’ This is the core risk of Degreed. If you cancel a content provider contract, then the platform hollows out. Tekstac’s own content library and hands-on labs carry no such dependency. What you access on day one is what you access at scale. 

How Tekstac Turns L&D Data into Business Decisions

Most L&D leaders don’t suffer from a lack of data. They suffer from too much fragmented data, too little trust in it, and no clear way to translate it into better business decisions. 

The default metrics such as completion rates, satisfaction scores, and average quiz marks feel precise. They’re easy to pull from an LMS and easy to put in a report. But they almost never answer the question a CFO or COO is actually asking: Is our team capable? What’s our learning ROI?

This is where the conversation in L&D needs to change — from data-driven to data-informed decision making. Without this shift, L&D will continue to struggle to demonstrate learning ROI to the C-suite. 

Challenges of Turning L&D Data into Business Decisions

Organizations collect vast amounts of L&D data, but converting that information into meaningful business decisions is often challenging. Without the right context and insights, learning metrics can create confusion instead of driving action.

1. Fragmented & Siloed Data 

Ask any L&D leader where their data comes from, and the answers are familiar: LMS reports, post-training surveys, assessment scores, manager feedback, HR systems. And yet the most common complaint remains: “We don’t have enough data.” 

In reality, the problem is almost never data availability. It’s that data lives in silos, owned by different functions, in different systems, with different access controls. Performance data sits in HR. System usage data sits in IT. Customer interaction data sits in operations. Each island holds a piece of the puzzle, but no one is assembling the picture. 

If LMS completion data is your primary evidence base, you’re operating within very narrow boundaries, and every business decision you inform is built on an incomplete foundation. 

2. Completion ≠ Competence

In L&D, too many teams are operating on autopilot, following the waggle dance of LMS reports and quiz scores without asking what those numbers actually mean, or what they’re failing to surface. A learner can score 90% on a cloud security assessment and still fail to stop a live breach. Completion is not competence. Passing is not performance. 

The hard truth: An LMS tells you who completed what and when. It cannot tell you who is actually job-ready, where capability gaps are quietly growing, or whether training reduced a single point of business risk. 

According to the World Economic Forum (WEF), 50% of the global workforce completed formal training in 2025, but many L&D teams still face challenges in translating learning activity into measurable business decisions. 

3. Hidden Skill Gaps 

Beyond the silo problem, there’s a more fundamental limitation: your LMS can only ever reflect the environment you designed. It surfaces insights you thought to look for. It will never show you what you didn’t think to measure.  

The shift we need is from treating data as a dictator; something that tells us what to do, to treating it as one critical input in a larger business decision-making process. 

4. Metrics Without Business Context 

As Jerry Z. Muller argues in The Tyranny of Metrics, chasing numbers can cause organizations to miss their real objectives entirely. Completion rates, satisfaction scores, and quiz averages feel precise, but without context, they can actively mislead. They reward compliance, not competence. They measure what was easy to measure, not what actually matters. 

The most effective fix is not better dashboards. It’s a declared, documented, pre-agreed methodology for how your function engages with data; one that ties training effectiveness directly to workforce capability and business outcomes. 

”The goal of analytics isn’t to report on the past. It’s to separate the signal from the noise so we can predict the future.”
— David Green, Global Leader in People Analytics

5. Low Trust in L&D ROI

L&D often struggles to earn trust, not because of a lack of capability, but because of a lack of documented methodology. When a business leader asks “Why did you choose a workshop over e-learning?” or “How do you know this is a training problem and not a management problem?”, the answer is too often “we judged it based on experience.” 

Experience is valuable. But it’s not auditable. And in an environment where every function is being asked to justify its budget in outcome terms, “we felt it was the right call” is not a defensible position. 

Without a clear methodology tying learning activity to workforce capability and business outcomes, L&D insights will always feel subjective, even when the underlying data is sound. 

How Tekstac’s L&D Analytics Platform Drives Better Business Decisions 

Tekstac is a skills intelligence platform built to close the gap between learning activity and real workforce capability, giving organizations the data intelligence needed to make confident business decisions. 

Tekstac doesn’t start with reports. It starts with the questions business leaders actually need answered: 

• Who is ready to be deployed today? 
• Where are our capability risks across teams and functions? 
• Did proficiency actually improve, or just compliance? 
• How fast is competence developing, and where are learners plateauing? 
• Which employees are closest to role-readiness and can be redeployed now? 

Each of these capabilities shifts the conversation from “Did training happen?” to “Can the team perform?” 

At the core of this platform is role–skill fitment. Rather than treating learners as course completers, it maps individuals against required role skills and proficiency levels. This gives L&D teams, managers, and leaders a shared, objective view of where the workforce stands and ultimately translates into better business decisions. 

The platform replaces passive quizzes with auto-evaluated hands-on labs. When a developer works inside the platform’s sandbox, the platform doesn’t simply record whether they got the right answer; it tracks their logic, their error-correction speed, and their technical accuracy under realistic conditions. The result is a proficiency heatmap: not “100 people passed” but “40 people are ready for senior DevOps work; 60 need targeted support with deployment automation.” 

Using AI-driven, multi-dimensional talent matching, it identifies employees who are closest to role-readiness. For large organizations hiring or redeploying at scale, this directly reduces time to productivity, training costs, and project risk. In one consultancy case study, targeted micro-lab interventions identified from Tekstac data reduced time-to-competency by 20%, moving staff to billable projects weeks ahead of schedule. 

TL; DR 

Data-informed decision making in L&D means using learning data such as proficiency scores, skill gap analysis, role-fitment assessments as one input alongside business context. Unlike purely data-driven approaches where numbers dictate action, data-informed teams use analytics to ask better questions and validate decisions, not replace human thinking.

Turning Learning Signals into Business Decisions

The future of L&D is not about collecting more data; it’s about turning the right signals into smarter business decisions. Completion rates and quiz scores may show activity, but they rarely reveal whether teams are truly capable, deployable, or ready for change. 

In a business environment where speed, adaptability, and capability define competitive advantage, L&D can no longer afford to operate on assumptions. That’s where Tekstac changes the conversation. By combining role–skill fitment, hands-on assessments, and AI-driven skill intelligence, it helps organizations move beyond reporting metrics to making informed business decisions.   

👉 Book a Tekstac demo and see your workforce capability data in action

Business Decision FAQs

 1. What is decision-making in business? 

Business decision-making is the process of analyzing information, evaluating risks and opportunities, and choosing the best course of action to achieve organizational goals. Effective decision-making combines data, business context, experience, and strategic priorities to drive better outcomes across operations, people, finance, and growth. 

2. What is the difference between data-driven and data-informed L&D?

Data-driven means the numbers dictate the action. Data-informed means data is one critical input alongside professional judgment, qualitative signals, and business context. The latter produces better decisions because it accounts for what data can’t capture: the messiness of real work, shifting organizational context, and the knowledge held by experienced practitioners that never makes it into a dashboard. 

3. How do you measure L&D impact beyond completion rates? 

Track proficiency improvement over time using pre/post assessments, speed to competency (how fast capability develops, not just whether a course was finished), role–skill fitment scores that show readiness against actual job requirements, and downstream business metrics such as QA scores, deployment speed, error rates, and time-to-productivity. Tekstac connects practice behavior in hands-on labs directly to on-the-job performance, creating a defensible link between learning activity and business outcome. 

4. How should L&D present impact data to the C-suite? 

Lead with outcomes, not activity. Structure the narrative as: the problem → the signal → the action → the result. Executives don’t need a dashboard; they need a decision. Make the business outcome the hero of the story, not the L&D team or the platform.

5. How do we stop being ‘order takers’ and become strategic partners?

Stop saying yes to every course request. If the data shows no meaningful skill gap exists, the problem is likely a process issue, a management issue, or a confidence issue, none of which a training course will fix. Having a documented methodology for how you diagnose problems and communicate that clearly to the business. 

How Tekstac Addresses the Top HR Challenges in 2026

HR challenges include hiring qualified candidates, retaining talent, ensuring employee engagement, and complying with labor laws, among many others. In 2026, HR challenges are becoming more complex as the function sits at the intersection of workforce transformation, AI adoption, productivity, employee expectations, and rapid skill disruption.  

However, one of the biggest challenges is the lack of clear visibility into workforce skills. Most organizations still don’t have reliable, role-level data on what their workforce can actually do, making it difficult to plan hiring, reskilling, internal mobility, and future workforce strategies effectively. The data tells a stark story. According to the WEF’s Future of Jobs Report 2025, 63% of employers globally identify skills gaps as the single biggest barrier to business transformation.

That gap between conviction and infrastructure is where organizations stall. Before looking at what modern skills intelligence platforms can solve, it’s worth being precise about what’s actually broken.

The Top HR Challenges Holding Organizations Back in 2026

1. Widening Skills Gaps

The WEF projects that 39% of workers’ current skill sets will be outdated or require transformation by 2030, and 59 out of every 100 workers will need reskilling or upskilling before then. More than 120 million workers globally are at medium-term risk of redundancy if that training doesn’t happen.

But the deeper problem isn’t the size of the gap. It’s the invisibility of it. Despite 98% of business executives agreeing that skills are becoming central to how organizations define work and value people (Deloitte), only 8% of those same organizations have reliable skills data to act on (Gartner, 2025). Training budgets get spent on generic programs, reskilling initiatives target the wrong gaps, and the skills drain caused by attrition goes unmeasured until critical project stalls.

As Jason Desentz, CHRO of Toshiba, noted at UNLEASH America 2026: “By 2030, successful organizations will be defined not by generational differences, but by a shared set of human skills that enable employees and managers to thrive alongside AI. These are no longer ‘nice to haves’ — they are the non-negotiable capabilities that HR leaders must intentionally cultivate.”

2. Talent Acquisition Stuck on the Wrong Signals

Hiring has grown more competitive and more expensive, but not more predictive. McKinsey data shows that 20–30% of key roles in many organizations are not filled by the most suitable people don’t exist, but because evaluation still relies on proxies: degrees, job titles, years of experience.

3. Workforce Planning Built on Incomplete Data

Strategic workforce planning is the second-highest HR priority globally, yet it ranks only 15th in current organizational capability, according to BCG’s “Creating People Advantage 2026.” What’s missing is a living, continuously updated picture of organizational skills; one that can inform decisions about internal mobility, succession, and whether to build, buy, borrow, or automate specific capabilities.

Patricia Frost, CHRO of Seagate, captures the challenge clearly: “Middle managers are really the powerhouse of any company. How well do they understand their teams and the skills within their teams, and understand also what people are passionate about?”

4. The Broken ROI Loop

LinkedIn’s 2025 Workplace Learning Report reveals that 88% of organizations are concerned about employee retention and that providing learning opportunities is the top retention strategy. Yet most L&D and HR teams cannot demonstrate the business impact of development investment in terms that CFOs or boards respond to.

The gap between spend and provable outcome is a budget risk with compounding consequences. When HR ROI measurement can’t be quantified, training budgets become vulnerable at precisely the moment the skills crisis demands more investment.

As Mark Whittle, VP of Advisory in the Gartner HR practice, put it: “CHROs should take an enterprise-wide view of AI’s impact on work, the impact of change on leaders and employees, and how to evolve organizational culture to support performance expectations.”

5. Internal Mobility That Doesn’t Actually Move

Despite increased investment in internal mobility programs, mobility rates have remained flat. Only 24% of organizations have structured programs in place.

The barrier is rarely culture alone; it’s data. Without visibility into verified employee skills profiles, matching internal talent to new roles relies on manager networks and informal knowledge, which introduces bias. The result is a pattern that costs organizations on both ends: external hiring for those roles existing talent could fill, while tenured employees leave because they see no pathway forward.

Stacia Garr, Co-Founder of Redthread Research, captures the stakes at UNLEASH America 2026: “AI transformation will only deliver tangible results when HR, IT and the organization jointly own it — aligning on clear ROI, intentionally redesigning work, and preserving culture and connection as core differentiators.”

How Leading HR Teams Are Solving HR Challenges

1. Skills Intelligence Platforms

The most consequential shift in enterprise HR technology over the past two years has been the move toward skills intelligence platforms. As AI in HR continues to reshape workforce planning and talent decision-making, these platforms are becoming critical for organizations looking to build data-driven talent strategies. Skills gap analytics from these platforms allow HR leaders to prioritize development investments at the role, team, or organizational level.

2. Predictive Workforce Analytics

Modern HR platform evaluation increasingly centers on predictive capability. By combining internal skills data with role demand signals, skills intelligence platforms help HR leaders anticipate which capability gaps will become critical in the next 6–18 months.

3. Connected Learning Pathways

Skills data becomes significantly more actionable when it links directly to development content. Platforms that integrate skills gap analytics with curated learning pathways allow organizations to move from “we have a gap in data engineering” to “here are 14 engineers who are 60% of the way there, and here’s the 90-day pathway to close it.” This is the mechanism that transforms HR ROI measurement from an aspiration into a reportable business metric.

How Tekstac Solves HR Challenges

Tekstac is built as an enterprise skills intelligence platform that makes skills data the connective tissue between talent acquisition, development, and strategic workforce planning.

The platform gives organizations a validated, role-specific view of where their workforce stands against industry benchmarks. Rather than relying on self-assessments or anecdotal input, the platform runs structured auto evaluations that produce skills gap analytics at the individual, team, and organizational level. This enables the HR leaders identify which roles carry the highest capability risk and which internal talent is ready to step up.

For enterprises managing high-volume hiring or large-scale internal skills audits, The assessment engine combines adaptive, scenario-based questions with AI proctoring for enterprises. This ensures that the skills data entering your workforce planning decisions is accurate and trustworthy.

Closing the ROI Loop

One of the clearest ways Tekstac supports HR ROI measurement is by connecting pre- and post-development skills data. When an organization runs an upskilling cohort, Tekstac shows how capability scores shifted, which roles are now better covered, and what the business impact looks like. This transforms the learning investment conversation from cost to measurable return.

Turning HR Challenges into Opportunities

The HR challenges of 2026 share a single root cause: organizations are making consequential decisions about their people without the skills infrastructure to make those decisions well.
Carrie Rasmussen, CHRO at Dayforce, frames the imperative plainly: “The old ways of deploying new technology will not suffice. CIOs and CHROs must move together. AI demands a unified mission.”  

For HR leaders, the message is clear. The future of workforce transformation will depend on how effectively organizations can identify skills, close capability gaps, and align talent strategies with business goals. Explore how Tekstac can help your teams stay future-ready in an evolving world of work.

FAQs on HR Challenges and Solutions in 2026

1. What are the current HR trends & challenges?

In 2026, HR leaders are navigating 5 challenges. Skills gaps are widening faster than hiring pipelines can fill them. Talent acquisition is shifting toward skills-based hiring, but most organizations lack the assessment infrastructure to operationalize it. Workforce planning remains largely reactive, with only 12% of companies having plans that extend beyond a single year (McKinsey). Employee retention is under pressure. And internal mobility, despite being a stated priority, stays flat because organizations don’t have reliable visibility into what skills their existing workforce actually holds.

2. How are HR leaders addressing the AI skills gap in 2026?

First, they’re building visibility using skills intelligence platforms like Tekstac to run structured assessments that reveal exactly where AI-related capability gaps exist at the team and role level. Second, they’re connecting that data directly to targeted learning pathways, so reskilling efforts are precise rather than broad. What’s changed in 2026 is the recognition that AI literacy isn’t a single skill; it spans prompt engineering, AI governance, human-AI collaboration, and role-specific application.

3. Why do most HR teams struggle to turn reskilling initiatives into measurable business outcomes?

Organizations invest in training but can’t connect it to performance, retention, or revenue. The answer naturally leads into why skills data infrastructure (assessments, benchmarking, pre/post tracking) is the missing link, which is exactly what Tekstac solves.

4. What are the top 5 HR priorities for 2026?

HR leaders are prioritizing closing skill gaps through upskilling and reskilling, integrating AI into HR and learning processes, and using skills intelligence platforms to gain better visibility into workforce capabilities. Improving employee retention and internal mobility has also become critical as organizations compete for skilled talent. At the same time, HR teams are expected to align talent and learning strategies more closely with business growth, productivity, and long-term workforce readiness.

Top 10 High Demand Skills for the Next 10 Years in India

The top high demand skills for the next 10 years in India are AI/ML, Data Analytics, Cybersecurity, Cloud/DevOps, Software Development, Product Management, Digital Marketing, Financial Analysis, UX/UI Design, and Strategic Communication. Together, these 10 capabilities define who gets hired, promoted, and paid more through 2035, regardless of degree or seniority. 

Roles like AI prompt engineer, MLOps specialist, and cloud security architect barely existed five years ago. They are now among India’s fastest-growing job titles, according to LinkedIn’s 2025 Jobs on the Rise report. At the same time, NASSCOM data shows entry-level IT roles declining by 18% as automation absorbs repetitive tasks. The skills for the next 10 years determine which side of that shift you land on. 

Why High Demand Skills Matter More Than Degrees in 2026

According to the World Economic Forum’s Future of Jobs Report 2025, nearly 44% of workers’ core skills will need to change by 2030. McKinsey’s Global Institute echoes this, projecting that up to 12 million occupational transitions may occur in India alone this decade. Organizations have responded by shifting their hiring filter from academic credentials to demonstrated capability. They are prioritizing outcomes, portfolios, and proof of work. 

As per Gartner’s 2025 HR Technology Survey found that skills-based hiring adoption grew by 39% year-over-year among enterprise technology firms. NASSCOM’s State of the Tech Talent Report estimates India faces a deficit of 800,000 qualified professionals in AI, cloud, and cybersecurity roles, despite producing 1.5 million engineering graduates annually. 

In simple terms, the market rewards capability over credentials.

Workforce Skills Trends India: What’s Changing

India’s labor market is undergoing a transformation driven by AI, automation, and digital infrastructure. 

• AI/ML job demand up by ~39%  
• Entry-level IT roles declining  
• Cybersecurity demand outpacing supply  

The World Economic Forum predicts 170 million new jobs by 2030. For India specifically, the WEF projects a net gain of approximately 11 million jobs by 2030, concentrated in technology, green energy, and care economy sectors, but only for workers who have already transitioned their skills. 

Deloitte’s 2025 Global Human Capital Trends report found that organizations which invested in structured upskilling saw 2.4x higher internal mobility rates; meaning skilled employees are also more likely to grow within a company, not just get hired. 

This is why skills for the future workforce are becoming the most valuable career currency.

10 High Demand Skills for the Next 10 Years

A. TECH SKILLS

1. Artificial Intelligence & Machine Learning (AI/ML)

Why This Matters Now

AI is no longer a niche skill; it’s becoming as fundamental as internet literacy once was. From recommendation engines to fraud detection and generative AI tools, AI is embedded into how businesses operate. According to LinkedIn’s 2025 Emerging Jobs Report, AI and generative AI-related job postings in India grew 3.1x year-over-year, making it one of the fastest-scaling emerging skills in India. 

Current Market Reality

• According to IBM’s Global AI Adoption Index, AI adoption across enterprises has crossed 70% 
• Companies are shifting from experimentation to full-scale deployment  
• Demand exists across BFSI, healthcare, retail, and manufacturing 

What You’ll Actually Earn

• Entry-level: ₹6–12 LPA  
• Mid-level: ₹15–25 LPA  
• Senior roles: ₹40+ LPA  

What You Need to Learn

• Python, TensorFlow, PyTorch  
• NLP and Large Language Models  
• Deep learning and neural networks  
• Real-world AI deployment  

2. Data Analytics & Data Science

Why This Matters Now

If AI is the engine, data is the fuel. Every organization today generates vast amounts of data, but very few can translate it into meaningful insights. This is why data analytics continues to rank among the most valuable in-demand skills. 

A 2025 Nasscom-Zinnov report found that only 23% of Indian organizations have a data analytics function that directly influences C-suite decisions. Unlike some specialized technical roles, data analytics is relevant across industries; from finance and healthcare to retail and logistics. What has changed, however, is expectation. Companies are no longer looking for professionals who can only analyze data; they want individuals who can connect data insights to business outcomes. This shift has elevated the role from a support function to a strategic one. 

Current Market Reality 

• India’s analytics market is projected to reach $16 billion by 2025, according to NASSCOM, with BFSI and e-commerce accounting for 45% of demand.  
• Demand for data professionals in healthcare has grown 67% since 2022, driven by hospital digitization programs under the National Health Mission. 

What You’ll Actually Earn

• Entry-level: ₹5–10 LPA  
• Mid-level: ₹12–20 LPA  
• Senior roles: ₹25+ LPA  

What You Need to Learn 

• SQL, Python, R  
• Data visualization (Power BI, Tableau)  
• Statistical modeling  
• Business analytics  

3. Cybersecurity

Why This Matters Now

As organizations become more digital, their exposure to cyber threats increases. Cybersecurity is no longer a backend function—it is central to business continuity. This makes it one of the most essential skills required for future jobs. 

The nature of cyber threats is also evolving. With the rise of AI-driven attacks and increasingly sophisticated hacking techniques, companies need professionals who can anticipate and mitigate risks proactively. India, in particular, faces a significant shortage of cybersecurity talent, creating strong opportunities for those entering this field. What makes this skill unique is its long-term relevance—security will remain a priority as long as digital systems exist. 

Current Market Reality

• Demand rising across BFSI, IT, manufacturing  
• Cybersecurity roles are becoming strategic, not just technical  
• India needs ~1 million professionals in this domain, according to Data Security Council of India (DSCI) 2024 report 

What You’ll Actually Earn

• ₹8–22 LPA depending on expertise  

What You Need to Learn 

• Network security  
• Ethical hacking  
• Risk management  
• Threat intelligence  

4. Cloud Computing & DevOps

Why This Matters Now

Cloud computing has become the backbone of modern business infrastructure. Every application, platform, and digital service relies on cloud systems to function efficiently. This makes cloud expertise one of the most critical digital skills in demand today. The demand for cloud professionals continues to outpace supply, particularly in India, where digital transformation is accelerating across industries. For professionals, this translates into strong career growth and global opportunities. 

Current Market Reality 

• India’s cloud talent demand is growing 2.4X, according to Nasscom’s Cloud Skills Report 
• Cloud is critical in telecom, biotech, fintech, and AI-driven sectors  
• India is now the second-largest cloud talent market globally after the US, according to LinkedIn’s 2025 Workforce Report. 

What You’ll Actually Earn

• ₹8–25 LPA depending on experience  

What You Need to Learn 

• AWS, Azure, Google Cloud  
• Kubernetes, Docker  
• CI/CD pipelines  
• Infrastructure as Code  

5. Software Development (Full Stack + DevOps) 

Why This Matters Now

Software development is one of the most important next generation skills. The demand for full-stack developers, in particular, reflects the industry’s need for versatility. At the same time, the integration of AI tools into development workflows is reshaping how software is built, making continuous learning essential for professionals in this field. 

Current Market Reality

• Full-stack developers are in the “high demand + difficult to hire” category  
• GitHub Copilot and similar AI coding assistants have not reduced demand for developers, they have raised the ceiling 
• A 2025 GitHub study found that developers using AI coding tools completed tasks 55% faster, which employers have translated into expecting higher output per hire rather than fewer hires 

What You’ll Actually Earn

• ₹6–15 LPA (average)  
• Higher for experienced developers  

What You Need to Learn 

• Frontend: React, Angular  
• Backend: Node.js, Python  
• Databases: MongoDB, SQL  
• DevOps tools  

B. DIGITAL & BUSINESS SKILLS

6. Product Management

Why This Matters Now

India has seen a 52% increase in product manager job postings between 2022 and 2025, driven by the rise of SaaS companies, fintech platforms, and consumer super-apps. Unlike most tech roles, PM salaries jump steeply with experience; a 3-year PM at a funded startup typically earns more than a 7-year software engineer at a service company. What makes this role unique is its emphasis on decision-making. Product managers are responsible for identifying market needs, defining product strategies, and ensuring successful execution.  

Current Market Reality

• Demand rising across startups and enterprises  
• Companies need professionals who can translate ideas into scalable products  

What You’ll Actually Earn

• ₹15–35 LPA depending on experience  

What You Need to Learn 

• Product lifecycle management  
• Data-driven decision making  
• Stakeholder management

7. Digital Marketing 

Why This Matters Now

The shift toward digital platforms has transformed how businesses reach their audiences. Marketing is no longer limited to traditional channels; it is driven by data, algorithms, and user behavior. This makes digital marketing one of the most practical digital skills in demand. 

Current Market Reality 

• FMCG hiring for digital roles has increased significantly  
• 23% of fresher roles now linked to digital and e-commerce  

What You’ll Actually Earn

• ₹4–12 LPA (entry to mid-level)  

What You Need to Learn 

• SEO, SEM  
• Social media marketing  
• Performance marketing  
• Analytics tools  

8. Financial Analysis & FinTech 

Why This Matters Now

India processed over 14.3 billion UPI transactions in January 2025 alone, making it the world’s most active real-time payments market. This volume has created a structural need for financial analysts and is now one of the high paying skills. 

Current Market Reality

• High demand in BFSI and startups  
• Growth driven by digital payments and financial inclusion  

What You’ll Actually Earn 

• ₹8–25 LPA  

What You Need to Learn 

• Financial modeling  
• Risk analytics  
• FinTech tools  

9. UX/UI Design

Why This Matters Now

India’s EdTech sector saw 22 million new users in 2024, all of whom interact with products designed in English but used in Hindi, Tamil, or Bengali. UX designers who can research and prototype for multilingual, low-bandwidth users are commanding a growing premium that English-first markets simply don’t create. This has elevated UX/UI design from a supporting role to a core business function. It is now one of the most essential skills for the future workforce. 

Current Market Reality 

The Taggd report highlights rising demand due to: 

• EdTech growth  
• Mobile-first applications  
• Multilingual user experiences  

What You’ll Actually Earn

• ₹5–15 LPA  

What You Need to Learn

• User research  
• Wireframing  
• Interaction design  
• Design tools (Figma, Adobe XD)  

C. HUMAN & COGNITIVE SKILLS

10. Strategic Communication & Problem Solving

Why This Matters Now

The most underpaid insight in India’s upskilling conversation is that communication and problem-solving skills amplify every other skill on this list. A data analyst who presents insights clearly earns 25–35% more than one who cannot, according to LinkedIn Salary benchmarking data. This is why communication skills continue to rank among the most important future skills in India.

Current Market Reality

• 70% of employers report communication gaps  
• Teams with strong emotional intelligence perform 20–30% better  

What You’ll Actually Earn

Not a direct salary skill, but a career multiplier 

What You Need to Learn

• Public speaking  
• Business communication  
• Critical thinking  
• Emotional intelligence  

What the Next Decade Holds for India  

India’s workforce is at an advantage that other large economies don’t have: a young, English-fluent, tech-curious population that is already in the middle of this transition. The 10 skills in this article are not predictions; they are current hiring realities. The gap between who gets hired and who doesn’t is narrowing to a single question: have you built the evidence to prove what you can do? 

Platforms like Tekstac are designed for exactly this; structured, role-aligned skill insights with assessments that create the kind of verifiable proof employers now require. If you’re mapping out your upskilling path, it’s worth starting there. 

High Demand Skills FAQs

1. Is foundational skill like Microsoft Excel still in demand today in the age of AI?  

Yes, Microsoft Excel continues to be one of the most widely used tools across industries, especially for data analysis, reporting, and operational tracking. When combined with analytics or business intelligence tools, Excel becomes a strong foundational component of broader digital skills in demand, improving both efficiency and decision-making capability. 

2. Why do skills matter more than degrees today?  

The shift toward skills-based hiring is driven by the need for immediate, measurable impact. While degrees provide foundational knowledge, they do not always reflect a candidate’s ability to perform in real-world scenarios.  

3. What are the most important future skills in India?  

 Technical skills such as AI, data analytics, cybersecurity, and cloud computing are driving demand across industries. At the same time, organizations are placing increasing value on communication, problem-solving, and adaptability. The combination of these capabilities reflects the broader shift toward a skill-based economy, where both technical expertise and human judgment play a critical role. 

4. Why is adaptability considered a high-demand skill?  

Adaptability is a high-demand skill because workplaces today are constantly changing with new technologies, roles, and expectations. People who can quickly learn, adjust, and handle change are more likely to stay relevant and perform well. It also helps them take on new challenges, work across different situations, and grow in their careers, making them valuable to any organization. 

Tekstac vs Outskill: Which is Best for Enterprise Learning?

Every L&D leader today is looking at the cost vs benefit of learning platforms to create a sustainable plan for the upcoming years. The landscape of tech education has shifted dramatically with the rise of AI, making it more critical than ever to choose a platform that delivers measurable results rather than just certificates. 

The Best Outskill Alternative for Enterprise AI Upskilling

If your organization has outgrown Outskill and needs an enterprise AI upskilling platform, this guide is for you. Outskill is designed for individual professionals; it delivers fast, engaging AI workshops, but it was not built for L&D teams managing hundreds of learners, tracking ROI, or integrating with enterprise HR systems. Tekstac is. 

Here is a detailed comparison to help you choose the right platform for your workforce.

Platform Overview of Tekstac vs Outskill 

When comparing Tekstac vs Outskill, it’s crucial to understand their fundamental differences. They are built for entirely different learning ecosystems. While both platforms cater to the modern workforce, their core philosophies, content breadth, and methods for measuring corporate training ROI sit on opposite ends of the spectrum. 

What is Tekstac? 

Tekstac is a 360° SaaS-based skills intelligence platform, designed to transform workforce capabilities and drive measurable ROI. Tekstac offers a holistic environment where associates can consume content, practice labs, receive mentorship, undergo assessments, and demonstrate real proficiency in emerging technologies.  

Tekstac delivers skilling depth across 250+ skills and 4000+ hands-on labs for enterprises & assessments, with enterprise clients such as IBM, PwC, Capgemini, Cognizant, among many others. 

Who is Tekstac best for? Tekstac is tailored for enterprises, corporate L&D teams, and learning leaders who need a secure, scalable, and skills intelligence platform to upskill their tech workforce in addition to an enterprise AI upskilling platform. 

What is Outskill? 

Outskill is a highly marketed, self-funded educational technology company focused on one specific domain: Generative AI. Operating on an app-based model connecting learners globally, Outskill is famous for its high-energy weekend “Generative AI Masterminds” and intensive multi-month programs like the “AI Generalist Fellowship” and “AI Engineering Fellowship.” 

The platform prioritizes agile, practical application over traditional academic theory. It functions more like a targeted bootcamp than a traditional AI learning platform for corporate teams. 

Who is Outskill best for? Outskill is best suited for individual working professionals, startup founders, agile marketing teams, and non-technical staff looking for a fast, intensive crash course in leveraging modern AI tools. 

Tekstac vs Outskill Comparison Table  

Learning Model Comparison of Tekstac and Outskill

When evaluating any upskilling platform, the first real differentiator is how learning is delivered and reinforced. 

Outskill’s model is designed for momentum. Learners are exposed to tools, workflows, and real-world use cases in a fast-paced format. The emphasis is on understanding how AI can be used today rather than outskill AI. 

Tekstac follows a different path. Learning is broken into structured pathways aligned to roles. Each concept is followed by guided practice, and progression depends on demonstrated understanding rather than completion. 

If visualized, the difference looks like this: 

• Outskill → Fast ramp-up → Tool exposure → Self-driven depth  
• Tekstac → Structured progression → Hands-on practice → Assessments → Detailed feedback 

This is not a matter of better or worse; it is a difference in intent. One prioritizes speed of adoption; the other prioritizes reliability of outcomes. 

Tekstac vs Outskill Feature Comparison

Tekstac

Tekstac’s feature set is more advanced. Beyond content delivery, it also integrates third-party content, provides hands-on labs, continuous auto-evaluation systems, AI-proctored assessments, and performance analytics.  

Learning Paths

Instead of program-led journeys, the platform offers clearly defined tracks across critical technology areas such as software engineering, full-stack development, data engineering, AI/ML, GenAI, cloud platforms, and infrastructure engineering. Each of these domains represents a comprehensive learning path designed to build capability progressively. 

For instance, a learner in the GenAI or data engineering track is guided through a sequence that begins with foundational concepts, moves into applied learning, and culminates in real-world problem-solving. Similarly, cloud-focused tracks cover platforms like AWS, Azure, and GCP, ensuring that learners build both conceptual understanding and practical expertise. 

Program Framework  

Tekstac focusses on the application of knowledge through its “Objective to Outcome” methodology, ensuring ROI-driven results. 

At its core, the platform integrates multiple layers; learning, practice, assessment, and analytics into a single ecosystem. Learners are not just consuming content; they are continuously evaluated through coding assessments, MCQs, capstone projects, and lab-based exercises. 

From an enterprise perspective, the framework is highly adaptable. It supports multiple use cases; from pre-hire assessments and onboarding programs to lateral training, reskilling initiatives, and project-specific readiness programs.  

In practical terms, this means: 

• Outskill emphasizes learning experience features  
• Tekstac emphasizes learning + evaluation + analytics systems  

This becomes especially important when learning needs to translate into workforce decisions. 

See how Tekstac supports enterprise AI upskilling at scale. Book a demo to explore hands-on labs, skills dashboards, and your organization’s learning ROI.

Outskill 

Outskill offers strong capabilities around AI learning experiences. These include guided sessions, real-world demonstrations, and exposure to widely used tools and workflows. The platform is designed to make learners comfortable with AI quickly, which is critical for organizations at an early stage of adoption. 

Learning Paths 

Outskill’s learning paths are built around program-led journeys that evolve with the learner’s stage of AI adoption, primarily focused on Gen AI and its real-world applications. 

At the entry level, the platform offers short, high-intensity programs such as the AI Mastermind, a two-day live experience. It then expands into more hands-on formats like the AI Generalist Bootcamp and similar accelerator-style programs, typically running for a couple of weeks.  

At the advanced end, Outskill offers longer, career-oriented programs such as the AI Generalist Program and also provides function-specific tracks like AI for Product Managers, AI for Marketers, and AI for Founders.  

Program Framework 

The platform follows a cohort-based, experience-driven program framework, where learning is anchored around live interaction, practical exposure, and immediate execution. 

Most of its flagship programs, particularly the AI Generalist Accelerator, are built around a mix of live training sessions, guided mentorship, and hands-on projects. Learners typically go through 40+ hours of live AI sessions, combined with dedicated project mentorship that helps them apply concepts in real scenarios. 

A key component of the framework is its focus on tool-driven learning. 

Advanced Solutions & Tools: Tekstac vs Outskill 

Tekstac

1. TekBuddy (AI Learning Assistant): It is an integrated AI-powered assistant that provides relevant, just-in-time support. They answer questions, suggest resources, and guide employees through real-world situations.

2. Skills Intelligence Dashboards

Advanced dashboards that provide:

• learner-level performance tracking
• cohort-level insights
• skills gap identification
• Gamified learning experience

This enables data-driven talent decisions, not just learning visibility.

3. AI-Proctored Assessment System

A built-in proctoring layer that ensures secure evaluations with random capability checks.

Outskill 

Instead of building proprietary tools, Outskill integrates learning with existing AI tools and platforms. 

Learners are trained on: 

• ChatGPT, Gemini, Midjourney-type tools  
• automation workflows  
• no-code / low-code builders  

As one learner noted, the value often comes from “learning how to use common AI tools in day-to-day life” rather than using a dedicated system. 

Tekstac vs Outskill Corporate Training ROI comparison 

According to The IDC Report, 39% complain about a lack of appropriate AI education, despite 94% of CEOs identifying AI as the top in-demand skill for 2026. This disconnect isn’t just a capability gap; it’s an ROI problem. When training doesn’t reach scale or deliver outcomes, investments fail to translate into business impact.  

The Tekstac vs. Outskilling ROI comparison highlights how they compare to one another in one of the most crucial metrics. 

Tekstac ROI metrics 

For one of its leading tech clients, Tekstac enabled workforce upskilling at scale, supporting over 1,100,000 learners. This led to more accurate talent identification, reduced hiring and training costs, and translating directly into measurable ROI.  

What drives this impact is Tekstac’s ability to go beyond training delivery. The organizations gain real-time visibility into skill progression, performance readiness, and business alignment. Learning is not just tracked; it is directly linked to productivity outcomes, making corporate training ROI measurable. 

Outskill ROI metrics 

Learners often report value in terms of “being able to apply AI in their work almost immediately”, with Outskill. The short-term impact is typically visible in time saved, workflow efficiency, and improved output quality. 

However, this ROI is largely: 

• individual-driven, not system-tracked  
• use-case based, not organization-wide  
• difficult to standardize or measure at scale 

Tekstac vs Outskill — Which One Should You Choose? 

Choosing between Tekstac and Outskill ultimately comes down to what you expect learning to deliver for your organization. As roles evolve and nearly 39% of today’s workforce skills are expected to become outdated by 2030, the conversation is shifting from quick adoption to building capabilities that last. 

If your immediate priority is to get teams comfortable with AI and not workforce upskilling at scale, Outskill offers a fast and engaging path to get there. If you are a solo learner or a small team exploring generative AI without a formal L&D program, Outskill delivers that fast.  

If you are an L&D leader responsible for upskilling a workforce, and you need measurable outcomes, skill validation, and compliance tracking, Tekstac is the best Outskill alternative. It is designed for environments where learning needs to be measured, tracked, and aligned with business outcomes. 

Tekstac’s Skilling Platform helps organizations run large-scale talent transformation programs and build future-ready capabilities across diverse technologies. 

Book a Tekstac demo today and start building your tech talent pipeline>> 

FAQs on Outskill Alternatives

1. Is Outskill suitable for enterprise corporate training?

No. Outskill is a B2C platform built for individual professionals. It has no org-level admin controls, no HRIS integration, no compliance tracking, and no team-level skill gap analytics. It is not designed for enterprise L&D programs.

2. Which companies offer training ROI analytics platforms in India? 

While platforms like Udemy and Coursera have made high-quality learning content easily accessible, organizations today are looking beyond just content delivery.
This is where platforms like Tekstac come in; focusing not just on content, but on end-to-end capability building, with deep skill tracking, real-world assessments, and measurable ROI analytics.

3. How does Tekstac differ from Outskill for enterprise upskilling?

Outskill delivers cohort-based AI workshops for individuals. Tekstac delivers structured learning paths, hands-on labs with auto-evaluation, AI-proctored assessments, and org-level analytics across 500+ learning paths.

4. What are the top AI learning platforms for beginners?

Many platforms help beginners get started with AI. But effective learning begins with strong fundamentals and then moves into real-world application. Platforms like Tekstac start with AI fundamentals; covering what AI is, key concepts like LLMs, machine learning, neural networks, and prompting, along with demystifying common terminology and building practical vocabulary through use cases.

AI in HR 2026: The Comprehensive Guide to Strategy, Tools, and Transformation

Reid Hoffman’s book ‘Superagency: What Could Possibly Go Right with Our AI Future’ asks a provocative question: what if AI expands human capability instead of replacing it? That question now defines the reality of AI in HR. 

Across boardrooms in every corner of the world, AI is no longer experimental; it is operational. CHROs are not asking whether AI belongs in HR. They are asking how fast they can deploy it without losing control. 

During HR roundtables we conducted across India in 2025, several CHROs shared that their organizations reduced hiring timelines by up to 47% after implementing AI-driven recruitment systems. That number isn’t incremental. It’s structural. This blog walks through the frameworks, implementation models, real-world impact metrics, and leadership decisions shaping that shift in 2026 so HR leaders can move from experimentation to enterprise transformation.  

1. What is AI in HR?

At its foundation, artificial intelligence in HR refers to the integration of machine learning, predictive analytics, generative AI, conversational systems, and intelligent automation into core HR processes. 

This includes: 

• AI-powered resume screening 
• Predictive attrition modeling 
• Intelligent workforce planning 
• Conversational HR assistants 
• Skills intelligence platforms 
• Agentic workflow orchestration 

Unlike traditional HR automation, which focused on digitizing forms and workflows, AI introduces cognition into systems. It enables pattern recognition, forecasting, personalization, and adaptive decision-making. 

This marks the shift from process digitization to digital HR transformation. 

Instead of asking what happened last quarter, HR can now ask: 

• Who is at risk of leaving? 
• Which skills are becoming obsolete? 
• Where should we reskill instead of hire? 
• How do we personalize growth at scale? 
• That shift is redefining the HR operating model.

2. The Urgency: Why AI in HR Adoption Cannot Wait

The urgency around AI adoption in HR is not theoretical. Let’s see some actual numbers. 

According to McKinsey & Company – Global AI Survey, 65% of professionals report their organizations use AI in at least one business function. Yet within HR specifically, maturity remains uneven. 

43% of organizations now use AI in HR, up from 26% in 2024. 45% of Indian organizations have already integrated Generative AI into HR, with 93% reporting increased efficiency. 

And yet 93% of employees say AI is underutilized. 55% of HR leaders say their tech stack does not meet evolving needs. 60% of business leaders admit they lack a clear AI implementation vision. 

This is the paradox of the current moment: High investment. Low clarity. 

The organizations delaying implementation are not saving money. They are widening the capability gap. 

The Future of Work with AI will not wait for organizations to feel ready. To remain competitive, organizations must focus on helping employees outskill AI, building capabilities that complement AI technologies rather than lag behind them. 

3. The State of AI in HR 2026: Market Shift and Strategic Realignment 

Josh Bersin describes the current phase of AI in human resources as enthusiastic but immature. Many companies are experimenting, but few have identified high-impact, scalable use cases. 

He emphasizes that AI deployment is not like ERP rollouts. It requires iteration, trust-building, and continuous governance, particularly in hiring and performance evaluation. 

At the same time, one of the leading reports in 2026 projects that the global AI in HR market will grow from $4.3 billion to $25 billion by 2031. 

Drivers of this growth include: 

• Demand for automation 
• Data-driven decision-making 
• Personalized employee experiences 
• Advanced talent analytics 
• Intelligent workforce planning systems 

Much of this momentum is being shaped by emerging AI trends in L&D, as organizations rethink how skills are built, measured, and scaled across the enterprise. 

4. Real-World Enterprise Case Studies of AI in HR

The following case studies highlight how AI is transforming HR from an administrative function into a strategic growth engine. 

4.1 AI in Hiring & Assessments 

A global retail enterprise deployed an AI-powered hiring assistant. Due to this, application completion rates increased from 50% to 85%. Hiring timelines reduced from 12 days to just 4. 

Result? Efficiency improved and more importantly, candidate experience improved. 

In another remarkable instance, Unilever implemented AI-driven assessments in early hiring stages and reported improved diversity in candidate pipelines while reducing time-to-hire. As former CHRO Leena Nair stated: 

“Technology should remove bias and enable meritocracy, not reinforce existing patterns.” 

On the contrary, AI in HR also had some negative results. Take, for instance, Amazon’s AI recruiting tool, which showed gender bias in training data that resulted in eradicating the tool itself.  

These examples illustrate both the power and responsibility of AI and automation in HR. 

4.2 HR Automation with Agentic AI 

Agentic AI represents a major leap beyond rule-based automation. HR adoption of Agentic AI currently sits at 15%, but Salesforce projects it will reach 64% within two years. 

Unlike isolated tools, Agentic AI systems can plan, reason, and execute multi-step workflows across systems. At Advanced Micro Devices (AMD), an AI-powered HR service orchestration agent was deployed to handle high-volume employee support across systems like SAP SuccessFactors and Microsoft Teams. Instead of routing every request to a human helpdesk, the agent interprets employee intent, retrieves context from HR systems, initiates workflows, routes approvals, and escalates complex issues when needed. The result for AMD was an 80% reduction in time to resolve inquiries, 50% of requests handled via self-service. 

5. The Benefits of AI in HR 

The impact of AI in HR isn’t limited to automation. Its value unfolds across three powerful layers: operational efficiency, strategic intelligence, and employee experience.

5.1 Operational Efficiency 

At the foundational level, AI streamlines everyday HR operations. From resume screening and interview scheduling to payroll validation and helpdesk queries, repetitive and time-intensive tasks can now be automated with precision. 

In fact, as per ETHR, 68% of companies say AI improves job accuracy in HR processes, while 72% report enhanced productivity and time savings. 

5.2 Strategic Intelligence 

Beyond efficiency, AI elevates HR from administrative execution to predictive strategy. Machine learning models analyze workforce data to identify patterns and generate forward-looking insights. 

Organizations are using AI for: 

• Attrition forecasting 
• Performance trend analysis 
• Compensation planning 
• Workforce planning 
• Advanced skill gap analysis 

Instead of relying on reactive reports, HR leaders can anticipate risks, model future scenarios, and make data-backed talent decisions aligned with business goals. 

5.3 Enhanced Employee Experience 

AI also plays a critical role in personalizing the employee journey. It enables: 

• Personalized onboarding experiences 
• Adaptive learning journeys 
• Career path simulations 
• Real-time HR support through intelligent assistants 

As organizations shift toward skills-first talent models, AI-powered workforce upskilling becomes essential. Today, 88% of organizations report active upskilling programs, and companies investing in reskilling are 2.5 times more likely to achieve positive business outcomes from AI initiatives. 

6. AI tools Transforming HR

AI is increasingly helping HR teams work smarter, not harder, by automating routine tasks, improving decision-making, and enhancing employee experiences. Here are five standout AI tools that are shaping the future of HR: 

• HiredScore AI – Uses AI to find the right candidates by screening resumes and providing insights. 
• Fetcher – Automates candidate sourcing and outreach, helping HR teams engage top talent faster. 
• ChatGPT – Generates job descriptions, candidate emails, and other recruitment documents. 
• Tekstac – Helps HR teams analyze employee skill profiles, identify growth paths, and automate learning workflows for internal mobility. 
• Maestra – Transcribes audio and video to text for interviews, meetings, and training. 

7. The CHRO Advantage in Leading AI Transformation

AI transformation is not an IT initiative. It is a people transformation. 

More than 70% of enterprises are investing in AI, yet many struggle to extract value due to skill gaps and change resistance. 

CHROs must lead in three critical areas: 

• Aligning AI with enterprise strategy 
• Reinventing HR through intelligent experience 
• Preparing the workforce for the AI impact on jobs and skills 

As Prabir Jha, leading HR advocate in India, has consistently articulated in his writings and leadership conversations, digital transformation succeeds only when capability transformation precedes technology adoption.  

The top HR leaders in India are already demonstrating what proactive AI leadership looks like, integrating technology with talent strategy. 

AI’s greatest value emerges when strategy and talent are synchronized. 

CHROs must build AI literacy, embed ethical guardrails, and champion cross-functional partnerships. 

AI’s greatest value emerges when strategy and talent are synchronized. 

CHROs must build AI literacy, embed ethical guardrails, and champion cross-functional partnerships. 

The most effective HR leaders are not reacting to AI. They are orchestrating it. 

8. AI in HR Implementation Framework 

When discussing AI implementation in HR, Dave Ulrich, widely known as the Father of Modern HR has discussed recently about an analysis from PwC’s Workforce Transformation Team, which examined how AI is likely to reshape the four core elements of the HR operating model. The central idea is powerful. AI should not sit as a separate HR initiative.

It should be embedded into the HR operating model to increase stakeholder value.

AI implementation succeeds when it is structured, intentional, and aligned with business outcomes. While many organizations begin with isolated pilots, sustainable impact comes from a clear framework that connects technology, people, and processes. 

8.1 Phase 1: Assessment 

Identify high-impact processes. Evaluate tech stack readiness. Assess data quality and governance models. 

Many companies fail here by rushing implementation without clarity. 

8.2 Phase 2: Pilot 

Start with high-volume workflows like recruitment or onboarding. Measure KPIs such as time-to-hire, cost-per-hire, and satisfaction. 

68% of companies report improved job accuracy during AI pilots. 

8.3 Phase 3: Scale 

Scale gradually with governance, bias audits, and structured change management. 

AI deployment must be iterative, not disruptive. 

Disciplined scaling differentiates strategic transformation from fragmented tool adoption. 

9. Challenges of AI in HR 

Despite rapid momentum, adoption is far from universal. 17% of organizations still have no plans to implement AI in HR, reflecting hesitation around risk, readiness, and ROI clarity. Even among adopters, concerns remain significant. This signals a critical leadership gap: technology is advancing faster than organizational capability. 

For CHROs, the real challenge is not whether to use AI, but how to implement it responsibly at scale. AI systems influence hiring decisions, performance evaluations, compensation modeling, and employee monitoring. Without strong guardrails, the same systems designed to drive efficiency can amplify bias, compromise privacy, or erode employee trust. 

This is why forward-looking HR leaders are prioritizing: 

• Clear AI governance frameworks 
• Bias detection and mitigation protocols 
• Data privacy and compliance safeguards 
• Transparent communication with employees 
• Structured AI upskilling for HR teams 

10. Will AI Replace HR?

“AI will not replace humans — but humans who use AI will replace those who don’t.” — Sam Altman, CEO, OpenAI 

The fear isn’t new. Every technological leap has sparked the same question: Will machines take over? The broader debate around AI stealing jobs often frames the future of work as a zero-sum game: humans versus machines. In HR, that anxiety feels personal. But here’s the reality: AI doesn’t replace HR. It reshapes it. 

AI can screen thousands of resumes in seconds. It can flag skill gaps, predict attrition risk, and automate interview scheduling. What it cannot do is read nuance in a candidate’s life story, sense cultural alignment in a conversation, or coach a struggling employee through uncertainty. The future of HR is not “AI vs Humans.” It is AI-powered Humans. As Alim Dhanji, Chief People Officer at TD SYNNEX puts it, “AI is an enabler; it cannot replace the human element in HR. Judgment, empathy and understanding context are areas where AI falls short.” 

11. Measuring ROI of AI in HR

One of the most searched queries around AI in HR is simple: “How do we measure ROI?” Because experimentation is exciting. But leadership cares about outcomes. According to IDC, 92% of organizations plan to increase their AI investments, with AI spending projected to grow at 1.7x the rate of overall digital technology spending in the next three years. 

Organizations investing in AI and automation in HR are increasingly tracking impact across four dimensions: 

11.1. Time Savings 

• Reduced manual data entry 
• Automated interview scheduling 
• Instant candidate screening 

A global enterprise reduced recruiter screening time by 42% after implementing AI-assisted shortlisting. That translated to thousands of hours saved annually. 

11.2. Quality of Hire 

AI-driven candidate matching improves role-skill alignment.
This directly impacts: 

• Retention 
• Performance ratings 
• Early productivity 

With strong talent analytics, organizations can now correlate hiring inputs with performance outcomes, something impossible at scale before. 

11.3. Internal Mobility 

AI-based skill mapping identifies who can move where. 

Instead of external hiring, organizations now redeploy internal talent. That reduces hiring costs, onboarding time, and cultural friction. 

This is where AI workforce planning becomes strategic, not administrative. 

11.4. Upskilling Velocity 

Companies adopting AI powered workforce upskilling report: 

• Faster certification completion 
• Higher learning engagement 
• Clearer role transition pathways 

A product head from an enterprise client once said: “Earlier, we were guessing who might fit a future role. Now we can see it. Skills tell the story.” 

That visibility is ROI. 

12. How Tekstac GenAI Labs Accelerates HR Automation at Scale

While many organizations talk about implementing AI in HR, very few know where to begin.  

This is where Tekstac’s GenAI Labs bridges the gap between experimentation and enterprise-ready execution. Instead of introducing AI as a standalone tool, Tekstac approaches HR automation as a structured capability-building journey. 

Let’s take a closer look at how this works. 

12.1 Resume Shortlisting: From Manual Screening to Intelligent Filtering 

Inside Tekstac’s GenAI Lab, HR teams learn how to build AI-assisted resume shortlisting workflows that: 

• Accept anonymized candidate data 
• Use structured prompts for contextual evaluation 
• Apply skill-based filtering criteria 
• Generate ranked candidate lists 
• Allow recruiters to review, refine, and provide feedback 

12.2 Personalized Outreach at Scale 

One of the overlooked areas of AI in HR is candidate communication. Generic outreach emails often result in low response rates and weaker employer branding. 

Through our GenAI Lab, HR teams learn how to: 

• Draft AI-assisted personalized outreach emails 
• Adjust tone to match brand voice 
• Test messaging inclusivity and clarity 
• Automate follow-ups 
• Track engagement patterns 

This dramatically improves candidate experience, a key metric in modern digital HR transformation. 

12.3 Scheduling Simulation: Eliminating Bottlenecks Before They Happen 

Interview scheduling may seem operational, but at scale it becomes a coordination challenge across recruiters, hiring managers, and candidates often across time zones. 

Inside Tekstac’s GenAI Labs, HR teams simulate AI-driven scheduling workflows that: 

• Identify optimal interview slots 
• Integrate calendar data 
• Detect scheduling conflicts 
• Analyze turnaround times 
• Predict bottlenecks

What makes this powerful is the simulation layer. This reduces risk during full-scale 

The measurable impact typically includes: 

• 50–60% reduction in screening and scheduling effort 
• Improved consistency in candidate shortlisting 
• Faster response cycles 
• Reduced candidate drop-offs

13. The Future of AI in HR

The AI in HR market is projected to reach $25 billion by 2031. Agentic AI adoption will accelerate dramatically. The transformation is structural. 

Organizations that approach AI with clarity, governance, and human-centered leadership will not just modernize HR, but they will redefine it. 

The next wave of AI in HR will include: 

• Enterprise-wide skills intelligence ecosystems 
• Predictive workforce simulations 
• AI-augmented performance management 
• Autonomous workflow orchestration 
• Integrated talent marketplaces 

14. AI in HR: For 2026 and Beyond

AI in HR 2026 is not about tools. It is about redesigning how organizations hire, develop, engage, and scale talent. On one side are fragmented pilots and unclear governance. On the other hand, organizations are executing disciplined AI-driven workforce transformation with measurable ROI. The divide is widening. Artificial intelligence in HR will not define the future; how leaders implement it will.  

If you’re looking to turn AI strategy into measurable outcomes, explore Tekstac’s platform demo.

FAQs on AI in HR 

1. What are the top AI in HR certifications for CHROs and HR leaders?

Here are some of the most recognized AI certifications suitable for senior HR leaders: 

• MIT Sloan School of Management – AI: Implications for Business Strategy
  Best for CHROs looking to understand AI at a board and enterprise strategy level. 
• INSEAD – AI for Business
  Focused on AI transformation, leadership alignment, and implementation strategy. 
• Wharton School – AI for Business
  Strong for leaders who want to link AI investments to business and talent outcomes. 

2. Is AI going to eliminate HR jobs or finally prove HR’s value? 

This question often misses one critical point: AI isn’t just another HR tech tool. It’s built on machine learning, which means it improves over time. Many industry leaders anticipate a shift from partial automation to near-full workflow automation within the next 5 years. That doesn’t mean humans disappear. It means humans focus on approval, judgement, and complex decisions. HR teams will likely become leaner operationally, but stronger strategically. 

3. How to implement AI responsibly in HR? 

Responsible AI in HR means using AI in ways that are ethical, transparent, and aligned with organizational values. Before adopting any AI tool, CHROs should ensure it’s evaluated and approved, safeguarding security and compliance. AI use must respect privacy and data protection, with internal policies that prevent input of sensitive or confidential information.  Organizations should be transparent about how AI is used, maintain clear documentation for traceability, and have oversight to catch errors, bias, or risk.  

20 Inspiring HR Women Leaders in India Driving Talent Strategy

For decades, human resources was viewed as a company’s administrative backbone. Today, it is the central nervous system. As the corporate landscape shifts toward a skills-first approach, talent strategy has become the most critical infrastructure for sustainable company growth. Leading this transformation are women leaders in India who are redefining what modern HR looks like. 

We aren’t just measuring representation; we are measuring impact. Across India’s rapidly scaling tech ecosystems and Global Capability Centres (GCCs), women leaders are no longer just participating in the dialogue around diversity and talent; they are rewriting the entire playbook. 

As American author Harriet Beecher once said, “Women are the real architects of society.” In today’s corporate ecosystem, HR leaders are the architects of culture.” In this blog, we are spotlighting 20 women leaders in India transforming HR narrative.

Women in HR: The Data as of Now

The push for gender parity and inclusive leadership is no longer just an initiative; it is a macroeconomic imperative. 

• The Leadership Shift: Women now hold 20% of C-suite leadership roles in Corporate India, up from 13% in 2016, according to Avtar & Seramount’s Best Companies for Women in India list. 
• The HR Landscape: Women make up approximately 67% of the HR workforce. Their high emotional intelligence and ability to resolve complex conflicts position them perfectly to manage the modern, dynamic workforce. 
• Closing the Gap: For the first time, attrition rates between men and women have equalized, largely driven by industries like Pharma, IT-enabled services, and Global Capability Centres (GCCs). 

The Rise of Women Leaders in GCCs

We are witnessing a remarkable rise of women ascending to leadership roles specifically within Global Capability Centres. Leaders in these environments bring unique perspectives that are reshaping the corporate landscape, fostering innovation, and driving agile work cultures. By combining technological efficiency with human sensitivity, they are ensuring that the future of tech is built on a foundation of diverse, skills-first capabilities. 

20 HR Women Leaders in India Shaping the Future of Talent

Here are 20 inspiring women leaders in India who are breaking the mold and redefining talent strategy: be it from IT, Pharma or GCC sectors.

1. Sindhu Gangadharan 

MD, SAP Labs India

Rising from a software developer in 1999 to the first woman to lead SAP Labs India as MD, Sindhu is a global tech visionary. She serves as the Chairperson of NASSCOM and sits on the boards of Siemens India and Titan, blending deep technical capability with human-centric leadership. 

Connect on LinkedIn 

2. Anuprita Bhattacharya 

IT Country Head, Merck IT India

With roughly 17 years of experience steering digital innovation, Anuprita leads one of Merck’s most critical global digital hubs. Her strategic push for skills intelligence recently empowered her teams to deliver breakthrough AI-driven lab solutions, proving that modern HR is directly tied to tech infrastructure. 

Connect on LinkedIn

3. Priya Singh 

Associate Vice President – Global Head Technical Learning CoE,  Zensar

Priya spearheads global talent acquisition and technical learning with a focus on capability building. She is known for developing robust talent pipelines and creating safe spaces for cross-functional leadership, acting as a strong advocate for women navigating the tech industry. Her leadership has been associated with several marquee achievements, including CEO Excellence Award 2024, Brandon Hall Gold & Silver Awards – 2022, 2023, among many others. 

Connect on LinkedIn 

4. Anindita Ganguly Nayak 

Head of Learning & Talent Development, KPMG

As one of the renowned women leaders in India, Anindita brings over 25 years of experience and focuses on enterprise talent and developing robust learning architectures designed to foster continuous professional growth and dynamic skills intelligence. She develops robust learning architectures designed to foster continuous professional growth and dynamic skills intelligence. 

Connect on LinkedIn 

5. Amrita Choudhury 

VP – Learning, Talent & Organization Development, AXA Global Business Services

Amrita brings over 18 years of strategic HR leadership, functioning as an ICF-ACC certified coach and NLP Practitioner. She is renowned for driving large-scale HR automation and technology adoption to ensure workforce capabilities directly support global business goals. As a Gartner Peer Ambassador, she actively contributes to global HR communities, staying ahead of evolving workforce trends and sharing insights on building human-centric HR ecosystems.  

Connect on LinkedIn 

6. Shree Vikas 

HR Director – Head of L&OD, Rakuten

A key driver of technological upskilling in high-paced SaaS environments, Shree cultivates an internal culture heavily focused on continuous improvement and building an agile talent infrastructure for the modern tech landscape. 

Connect on LinkedIn 

7. Mangalapreetha Sairaman 

Senior VP, Indium Software  

With over 20+ years of experience, Mangala designs and executes highly impactful learning initiatives, seamlessly equipping engineering and product teams with cutting-edge, future-focused capabilities. She was awarded Learning Leader of the Year 2024 in L&D Event conducted by UBS Forums and awarded Under 40 Trailblazer by Business World. 

Connect on LinkedIn 

8. Jyothi Sridhar 

VP – Global Technical Training Head, L&D, HR, Mphasis

With over 25 years in the learning space, including major stints at Accenture and Infosys—Jyothi is dedicated to bridging the technical skills gap. She leads global training programs that drive technological excellence and future-proof engineering workforce. 

Connect on LinkedIn 

9. Dr. Shalini Singh 

Senior VP – Capability, Culture & Leadership Transformation, NAB

With over two decades of shaping executive talent, Dr. Singh has established massive Learning & Development Centers of Excellence. Her data-backed strategies and impact have earned her multiple Brandon Hall and Ragan Platinum Awards, establishing her as a heavyweight in global operational capability.  

Connect on LinkedIn 

10. Vijayalakshmi Subramaniam 

Head – Human Resources, Delta Technology and Management Services Pvt. Ltd

With a robust career spanning more than 25 years, Vijayalakshmi has led HR initiatives across the US, Europe, and Asia. She is a respected thought leader in building highly competitive employee value propositions and seamlessly integrating human capital systems. 

Connect on LinkedIn 

11. Shubhra Singh 

Global L&D Head, Sonata Software  

A prominent voice in modern HR, Shubhra architects agile, global learning strategies. A frequent speaker on leadership transformation, she champions continuous learning, adaptability, and emotional intelligence to accelerate holistic business transformation. 

Connect on LinkedIn 

12. Sirisha Voruganti 

CEO & MD, Lloyds Technology Centre India

A powerhouse engineer with prior leadership stints at JP Morgan and Mastercard, Sirisha is a recognized trailblazer for women in tech. Her exceptional impact on the industry is highlighted by recent top-tier accolades, including the NASSCOM Trailblazing Women in Tech Award (2024), Impact Leader of the Year at the GCC Summit (2025), and Winner of Trailblazer GCC (2024).  

Connect on LinkedIn 

13. Debolina Dutta

HR Professor, IIM Kozhikode

With over 35 years of combined industry and academic experience, she is currently shaping future leaders as faculty at IIM Kozhikode. A former Sr VP at Schneider Electric and an ICF-certified executive coach, she frequently publishes impactful research in the Harvard Business Review.

Connect on LinkedIn 

14. Divya Sathyan

VP, People & Culture, Zafin

Bringing over 25 years of HR expertise to the table, Divya drives a people-centric, high-growth culture in the SaaS space. An IIM Calcutta alumna recognized among the Top 250 Great Managers in India, she excels at aligning talent infrastructure with global business objectives. 

Connect on LinkedIn 

15. Aparna Vishwasrao 

CHRO, USV Private Ltd 

With over 25 years of strategic HR experience across Fortune 500 companies and startups, Aparna has earned accolades like the ‘Iconic Women Award’ (2020) and the ‘Top 101 HR Minds in India’ (2019). She is instrumental in aligning talent infrastructure with long-term organizational scaling. 

Connect on LinkedIn 

16. Tracy Zacreas 

Deputy Vice President – Global Head – L&D, Tata Technologies

With 24 years of work experience, Tracy drives the global learning infrastructure, focusing heavily on continuous upskilling in emerging areas like GenAI and software-defined vehicles. She plays a critical role in ensuring legacy workforces remain agile and future-ready during rapid industry transformations. 

Connect on LinkedIn 

17. A Annapurna 

Director – Global Learning and Talent Development, Fime  

Bringing over 20 years of expertise in HR transformation, Annapurna orchestrates global learning frameworks. She is also the founder of Emotionalytics & Co. and is highly regarded as a certified OD professional for her focus on emotional intelligence and leadership development. 

Connect on LinkedIn 

18. Keerthi Kariappa 

Transformational Coach | Advisor | Speaker 

An ICF-ACC certified coach and Chief Customer Officer at RippleHire, Keerthi brings over two decades of experience, including heading Customer Success at LinkedIn India. She leverages deep coaching to drive cultural shifts and authentic leadership growth.  

Connect on LinkedIn 

19. Ruchi Bhatia 

Founder, HRGurukul 

Founder of HRGurukul and a former Employer Branding Lead at IBM, Ruchi brings 25 years of industry experience to the table. This IIM-C alumna is repeatedly recognized as a Top 100 Future of Work Influencer and a leading voice in talent strategy. 

Connect on LinkedIn 

20. Ruhie Pande 

Group CHRO, Sterlite EdIndia Foundation

With two decades of experience across diverse sectors, Ruhie is an ICF-certified coach holding an MSc in Occupational Psychology from Birkbeck, London. She is frequently recognized among India’s most influential HR leaders for her data-driven empathy and strategic focus on D&I. 

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The Future of HR Women Leadership in India

As we celebrate International Women’s Day, it is vital to recognize women leaders in India, within all sectors. They are the architects of our future workforce. By blending high emotional intelligence with data-driven decision-making, and by prioritizing continuous upskilling, they are ensuring that our organizations are not only high-performing but genuinely inclusive. 

At Tekstac, we understand that building a transformative, skills-first organization requires diverse perspectives at the helm. We are incredibly proud of the strong representation of women leaders within our own ranks who continuously drive our company growth. 

Top 25 Skills-first Leadership Pioneers Shaping India’s Future Workforce

As organizations accelerate through AI adoption, evolving business models, and continuous disruption, one reality is becoming clear: skills, not roles, are now the true currency of work. Traditional talent models built around static job descriptions, rigid hierarchies, and tenure-based progression are struggling to keep pace with rapid technological and market shifts. In this environment, skills-first leadership have emerged as critical leaders driving skills-first transformation, bringing a clear mindset to workforce transformation. 

Why Skills-first Leadership Matters Now 

Skills-first talent leaders go beyond implementing new tools or learning platforms. They drive a fundamental shift in how talent is understood, developed, and valued. For these future-ready leadership India exemplars, hiring moves from pedigree to potential. 

As Josh Bersin, global HR and L&D thought leader, explains: 

“Skills are becoming the new organizational currency. Companies that understand, develop, and deploy skills dynamically will outperform those still managing jobs and titles.”

Top 25 Skills-first Leadership Champions in India

Building on this shift, Tekstac presents the Top 25 skills-first leadership champions in India, who are translating intent into impact. Together, these workforce transformation leaders are shaping up a workforce model designed for resilience and relevance.

1. Vivek Ranjan 

CHRO, Zensar

With over 26 years of global HR leadership experience, he has led diverse workforces, scaled businesses, and built high-performance cultures across geographies. As Zensar’s CHRO, he leads global HR transformation, cultivating a distinctive culture to evolve into a fully skills-based powerhouse. His earlier career includes 12 years in the UK, where he built and scaled European HR operations for multinational IT organizations, delivering best-in-class employee experiences.

👉 LinkedIn 

2. Ankur Berry 

Global HR Head, Coforge 

Ankur Berry brings 23+ years of global HR leadership, managing 10,000+ workforces across 25 countries. His integrity-driven approach emphasizes inclusive upskilling, building skills-first cultures that prioritize capability over credentials. Recognized as a Top 50 Influential HR Tech Leader, he champions humane talent development for multinational agility.

👉 LinkedIn 

3. Dr. Raju Mistry

Former Global Chief People Officer, Cipla

Raju Mistry is a widely recognized HR leader whose work has been acknowledged across platforms such as Forbes Best Employers and ETHRWorld Top 50. She combines strong L&D strategies with data-led people analytics, an approach that also earned her recognition as a SHRM 2025 award winner. Her inclusive people practices have consistently contributed to Great Place to Work certifications. 

👉 LinkedIn 

4. Dr. Sumit Mitra

CEO, Tesco Business Solutions & Tesco India

A visionary leader with over 20 years of experience, Dr. Sumit Mitra oversees a global workforce of 20,000+ colleagues across India, Hungary, and Central Europe. He is renowned for transforming Global Capability Centers (GCCs) into engines of innovation and strategic value. Under his leadership, Tesco’s global operations have integrated cutting-edge AI and data-led retail solutions, setting benchmarks for excellence in the retail-tech landscape.

👉 LinkedIn 

5. Dr. Mohan Bellur

Director – Human Resources, Bosch Global Software Technologies (BGSW)

With a career spanning over three decades, Dr. Mohan Bellur is a specialist in navigating large-scale organizational transformations and cultural shifts. He leads HR strategy for one of the world’s largest software hubs, focusing on the intersection of technology, talent, and leadership. His expertise in industrial relations and strategic workforce planning has been pivotal in scaling Bosch’s engineering excellence and fostering a culture of continuous learning.

👉 LinkedIn 

6. Shweta Mohanty 

Head of People & Culture, India, SAP

With 23 years of expertise, Shweta Mohanty leads SAP India’s HR, pioneering initiatives to build a skills-based organization. Her D&I advocacy (Girls Power Tech) builds diverse, skilled talent pools. She expands learning models enterprise-wide.

👉 LinkedIn 

7. Ayaskant Sarangi 

CHRO, Mphasis

Leading global HR for 25+ years, Ayaskant integrates talent management, L&D, and analytics for performance breakthroughs. As Executive Council member, he operationalizes skills-first strategies worldwide. He elevates people as strategic assets.

👉 LinkedIn 

8. Srilata Kolachana

Director of Learning and Development, APAC, CGI

With over 25 years of cross-functional expertise, Srilata leads the L&D strategy for the APAC region, driving talent transformation for a massive, diverse workforce. She specializes in building high-performance cultures through agile learning frameworks and leadership development initiatives. Her work focuses on bridging the gap between digital disruption and human capability, ensuring talent readiness across one of the world’s most dynamic markets.

👉 LinkedIn 

9. Lakshmanan M

EVP (Former CHRO), L&T Technology Services 

Having transitioned from a strong foundation in the public sector to executive leadership at L&T, he excels at engineering skills-focused transformations. A recognized NHRDN leader and keynote speaker, he is dedicated to building future-ready workforces that bridge the gap between traditional engineering and digital innovation. 

👉 LinkedIn 

10. Ritu Chakrabarti

AVP and Global Head of Learning and Development, LTIMindtree

A seasoned leader with over 25 years of experience, Ritu orchestrates global learning strategies that align with large-scale organizational priorities. Having held leadership roles at Wipro and Accenture, she is a specialist in navigating complex IT talent ecosystems. She was named one among the Top 50 UK Woman Leaders by Santander and a recipient of global awards from ATD and Brandon Hall.

👉 LinkedIn 

11. Satyadeep Mishra 

CHRO, R Systems

A dynamic HR leader with 20+ years of experience, Satyadeep specializes in driving organizational transformation across global tech and product engineering firms. Previously a core leader at Reliance Jio and Bajaj Finserv, he is an expert in scaling digital talent, performance management, and building robust leadership pipelines. At R Systems, he leads the people strategy for a global workforce, focusing on high-growth culture and tech-driven HR innovation.

👉 LinkedIn 

12. Varun Salaria

Director & India Lead – Learning, Talent and OD, Publicis Sapient

With over 2 decades of experience across the IT and digital business transformation sectors, Varun spearheads the talent development strategy for Publicis Sapient in India. He is a specialist in crafting high-impact “Power Skill” frameworks and leadership development programs that align with rapid technological shifts. His expertise lies in building agile, learner-centric cultures and leveraging data-driven insights to enhance organizational performance and employee experience.

👉 LinkedIn 

13. Priya Aneesh 

Senior Director, PwC 

A 25-year HR veteran, Priya fosters “Diversity in Thought” via data-driven L&D, championing women’s empowerment and cultural agility. Her transformative initiatives integrate business strategies with talent upskilling. She coaches teams for excellence.

👉 LinkedIn 

14. Deepak Kumar Arora

Vice President – Head Learning & Development, Birlasoft

With 28 years of experience across giants like Capgemini and Genpact, Deepak is a veteran architect of global learning ecosystems. He specializes in re-engineering L&D strategies through mergers and divestitures, integrating AI-powered coaching and NextGen learning platforms. At Birlasoft, he leads the “Early Edge” initiative, focusing on transforming first-generation talent and building “human-centric” leadership capabilities, emphasizing empathy and resilience as the ultimate superpowers in an AI-driven world.

👉 LinkedIn 

15. Dr. Manoj Apte

Global Head – Learning & Development, Persistent Systems 

A PhD-holding leader with a unique background in testing quality management and process engineering, Dr. Manoj Apte brings a rigorous, analytical approach to talent transformation. At Persistent Systems, he has engineered high-impact learning journeys that bridge the gap between technical expertise and leadership excellence. He recently received the ‘Transformative L&D Leader’ award from ETHR part of the ETHCA.

👉 LinkedIn 

16. Divya Amarnath

Vice President – Talent Development, Goldman Sachs

With 23+ years across 10 countries, Divya designs learning ecosystems for 200,000+ employees, coaching BU leaders on $400M+ accounts. Her Train-the-Trainer programs build skills at scale across 129 nationalities. She engineers organization-wide proficiency.

👉 LinkedIn 

17. Mahendran Dilli

Executive Vice President – People & Talent, Indium Software

Mahendran advances skills-first frameworks in software innovation, optimizing talent for testing and engineering excellence. His operational expertise builds adaptive teams ready for digital shifts. He bridges skills gaps with precision.

👉 LinkedIn 

18. Mahesh D

Strategic L&OD Leader, Rakuten

Mahesh is a high-impact architect of organizational capability, currently leading a global L&D ecosystem for 8,000+ employees across 12 countries. With 22+ years of experience, he built Rakuten’s first internal digital university, improving skill proficiency by 40%. Recognized as one of the “100 Most Talented Training & Development Leaders in Asia,” he is a specialist in creating “Tech Bridge” programs that align engineering excellence with business innovation.

👉 LinkedIn 

19. Hemant Kumar Ravi

Vice President – People Experience & Talent Transformation, Infogain 

A strategic HR leader with over 18 years of experience across IT, Consulting, and FMCG, Hemant leads large-scale HR modernization for a global workforce of 5,000+. Previously a leader at EY, he is an expert in leveraging data science and people analytics to design future-ready talent ecosystems. His work at Infogain focuses on building “human-first” digital engineering cultures, integrating AI-enabled HR technology, and spearheading global leadership hiring.

👉 LinkedIn 

20. Madhavi Juttiyavar

Global Head Learning and Development, Mastek

With over 30 years of experience, Madhavi is a strategic L&D leader known for building scalable talent engines in the IT services sector. Having held key roles at Mastek for the last 26 years, she specializes in aligning global competency frameworks with business growth. At Mastek, she drives digital-first learning initiatives, focusing on hyper-personalization and GenAI upskilling to ensure the workforce remains agile.

👉 LinkedIn 

21. Lalith Sharma 

President & CHRO, Inspira

With 24+ years of strategic leadership across the IT and BFSI sectors, Lalith is a powerhouse in HR transformation and change management. Having spent 17 years at Sify Technologies, where he rose to CHRO, he is an expert in integrating AI and digital solutions into employee experience. At Inspira, he oversees global human capital across India, USA, ASEAN, and MEA, focusing on business-aligned workforce planning and building resilient, high-performance cultures for the cybersecurity and data analytics industry.

👉 LinkedIn 

22. Mary Andrews 

Associate Vice President – Global Talent Leader, Sutherland Global Services 

With over two decades of experience, Mary is a highly decorated L&D strategist and certified Master Facilitator. A specialist in building end-to-end learning ecosystems, she is renowned for co-curating full-stack digital technology training and high-impact executive coaching programs. Her career is marked by prestigious industry recognition, including L&D Leader of the Year 2024 (6th CHRO Confex, Bangalore), Next Gen L&D Luminary (GWFM & People Decode, August 2023) and Top 20 L&D Transformation Leaders (Transformance Forums, December 2022). 

👉 LinkedIn 

23. Tanuja Pereira 

AVP, Head – Learning and Development, Hexaware Technologies

With 20+ years in the IT industry, Tanuja is a future-focused leader at the intersection of tech fluency and human-centered design. At Hexaware, she architects data-driven learning ecosystems that integrate directly with business agility. She is renowned for building specialized Centers of Excellence (CoEs) in Cloud, AI/ML, and Agile, leveraging strategic partnerships with giants like AWS, Microsoft, and Google.

👉 LinkedIn 

24. Rajesh Chandran S

Sr. VP – Global Head – Talent Acquisition, L&D, Happiest Minds Technologies

A powerhouse leader with a over 3 decades of overall experience, Rajesh brings 14 years of sales and P&L experience into the heart of HR. This commercial lens allows him to lead Talent Acquisition and L&D at Happiest Minds with a sharp focus on business growth and quality of hire. He is an expert in AI-based automation and process enablement, specializing in workforce management and large-scale IT recruitment.

👉 LinkedIn 

25. Rajkamal Vempati

Group Executive & Head Human Resources, Axis Bank

With 27+ years of experience across premier financial institutions, Rajkamal is a transformational leader known for reimagining traditional banking HR. Since joining Axis Bank in 2015, she has pioneered industry-leading initiatives like “Gig-A-Opportunities” (alternate work models), “Come As You Are” (LGBTQ+ inclusion), and “HouseWorkIsWork” (valuing homemakers’ skills).

👉 LinkedIn 

The Road Ahead for Skills-first Leadership in India

Embracing skills-first leadership at the organizational core isn’t optional, it’s survival in India’s talent tsunami. These leaders driving skills-first transformation offer actionable blueprints: invest in micro-learning, analytics-driven upskilling, and diverse pipelines. Follow their LinkedIn wisdom, replicate their wins, and position your team for 2030 dominance.  

What’s your next skills initiative? Tag a skills-first talent leader below and spark the conversation!