When AI learns, humans must learn differently

By: Nisha Gopinath

The World Economic Forum estimates that nearly 44% of workers’ core skills will change by 2027, which means that reskilling is no longer a choice, but a prerequisite for relevance. AI is heightening demand for hybrid capabilities, i.e., combining technical proficiency with deeply human skills such as judgment, creativity, resilience, and learning agility. 

At the same time, recent IBM-IndiaAI research highlights the scale of the gap: today, only about 30% of employees possess the level of AI literacy businesses say they require. That figure will need to nearly double by 2030. This growing disconnect is forcing enterprises to fundamentally rethink how learning happens at work.

Skills as the new organisational currency

Skills need to be visible, portable, and continuously updated. When enterprises treat skills as the currency of growth, they can match talent to opportunities more fluidly – across projects, roles, and career stages – creating more dynamic pathways for growth and mobility. In practice, this could mean using internal talent marketplaces to match employees to projects based on skills, allowing employees to build capability through real work rather than waiting for the “next role” to learn something new.

For HR, this signals a move from administering learning programs to architecting an ecosystem where skill acquisition, application, and progression are embedded into everyday work.

Work itself must be redesigned, not just people

In the agentic AI era, the future of work is about augmenting human capability with intelligent systems. As AI becomes embedded into work, enterprises should actively redesign jobs around distinctly human strengths, i.e., judgment, creativity, problem-solving, and ethical oversight. This requires expanding roles and creating opportunities for employees to apply their skills meaningfully in collaboration with AI. 

Redesigning work is essential not only for productivity but for learning itself. Employees learn fastest when skills are applied in real, AI-augmented contexts.

This means revamping operating models, workflows, and decision rights that embed human–machine collaboration into how work gets done. When augmentation, not automation, becomes the organising principle, learning evolves from being intermittent to continuous, contextual, and outcome-driven.

AI as an HR intelligence layer

AI’s true value in HR lies in enabling intelligence at scale. It gives leaders real-time visibility into existing capabilities, helps them understand what’s missing and plan for future requirements.

AI can help personalise employee learning pathways, recommend opportunities aligned to individual skills, and match talent to projects dynamically. It can also inform workforce planning decisions by anticipating which skills will be critical to sustain the enterprise’s growth, not just which roles to fill.

Without this intelligence layer, skills-based transformation may remain aspirational rather than operational. 

Entry-level talent as AI-native talent accelerators

Entry-level professionals are uniquely positioned to become AI-native employees who adapt faster, challenge traditional ways of working, and scale new capabilities across the organisation. By helping these employees learn as they work and designing roles that prioritise growth, enterprises can turn early-career talent into a competitive advantage.

Investing in early-career talent will be key for enterprises to build the skills, innovation and leadership pipeline they need for the future.

From talent scale to skill leadership: India’s opportunity

IBEF reports suggest that India accounts for 28% of the global STEM talent pool and 23% of the world's software engineering professionals. Further, our nation is also home to roughly 16% of the world’s AI talent and a fast-growing pool of 600k+ AI professionals, as per the India Skills Report 2026.

With its unique combination of talent, technology and scale, India is well-positioned to become a global leader reshaping how capability is built, deployed and continuously renewed in an AI-driven economy.

About the author: Nisha Gopinath is the Vice President and Head of Human Resources (HR) for IBM India & South Asia. She is responsible for the people strategy, employee services & engagement and skilling & development of IBMers in the region. Since joining IBM in 2011, Nisha has held strategic leadership positions in India and internationally, spanning various business units and functions. In her previous role, she served as the HR leader for IBM’s Global Delivery Centers, for multiple regions across the world. In the course of her career, she has also spent considerable years at IBM headquarters in New York.