From talent factory to AI powerhouse: India at a defining inflection point

India’s shift from being a talent hub to potentially becoming an AI-execution powerhouse is a steep road, and it can be done, say David Martin, managing director & senior partner, global lead, people & organisation, and Ashish Garg, APAC leader, people & organisation practice, BCG.

India is at an inflection point moving beyond its historical position as a global talent provider to emerging as a strategic node in the world’s AI delivery network.

This transition will need shift in long-term vision and investment, value creation, and enterprise integration of GenAI, the executives said in an interview with ET. Edited excerpts:


What kind of AI adoption is needed among the workforce in India? What distinguishes countries and companies that are moving from experimentation to true enterprise scale AI integration?

Ashish Garg: India’s AI journey is notable not just for adoption, but for the intensity and speed of uptake. According to BCG’s AI at Work 2025 report, India has one of the highest GenAI adoption rates globally—with ~92% of employees using GenAI weekly, significantly above the ~72% global average. This grassroots energy is driven by India’s digitally fluent young workforce and deep experience in the tech sector.

But frequency of use alone does not equate to enterprise-scale impact. Our research makes clear that the real value lies in embedding AI into how work gets done, not just whether people are using AI tools. Integration and value capture are what differentiate leaders.

The survey also shows that only 43% of Indian employees feel adequately trained. The organisations scaling impact are those offering structured, role-specific AI training, not just tool access.

India has accomplished what many countries are still working toward—widespread, bottom up AI adoption. The distinguishing factor for moving to enterprise scale impact is systematic integration: workflows, skills, and leadership alignment that capture value beyond usage.

Given the uneven pace of leadership engagement across markets, what global best practices help frontline managers become effective AI enablers?

David Martin : There are five practices that help frontline managers become effective AI enablers. First, leaders must model everyday AI use to normalise adoption and build confidence; visible support can lift positive sentiment sharply. Second, redesign workflows, not just deploy tools—organisations that do so see better decisions and higher value creation. Third, link AI use to clear performance outcomes. Fourth, provide role-specific, practical training rather than generic sessions. Finally, create a safe, feedback-driven culture that encourages experimentation.

The payoff comes less from adoption alone and more from embedding AI into how work actually gets done.

Given that Shadow AI is on the rise, what India-specific frameworks can help manage safe and compliant AI usage?

Ashish Garg: The AI at Work 2025 data shows that 54% of employees globally use or use AI tools without formal approval—a classic Shadow AI trend with real risks for data privacy, compliance, and quality if left unmanaged.

Leading organisations are establishing centralised centres of excellence (CoE) to oversee AI governance, training, model audits, and policy rollouts. CoEs are increasingly owning AI safety and scaling frameworks across functions.

BCG’s AI at Work 2025 report shows employees are more likely to benefit from GenAI when they receive clear guidance. Indian companies should embed ‘safe usage’ playbooks into core functions—especially customer-facing and compliance-heavy roles.

India’s GenAI momentum requires Shadow AI to be managed through smart governance—not over-restriction. Tiered policies, CoEs, embedded training, and adaptive monitoring ensure safety, trust, and business alignment.

Given the uneven pace of leadership engagement across markets, what global best practices help frontline managers become effective AI enablers?

David Martin: BCG’s AI at Work 2025 data shows a clear leadership adoption gap: while ~85% of senior leaders and ~78% of managers use GenAI regularly, only about 51% of frontline employees do—largely because only ~25% of frontline workers say they receive sufficient guidance from leadership on how to use AI effectively

To close the AI adoption gap, five leadership practices stand out. Leaders must model everyday AI use, signal confidence and lift employee optimism—which BCG finds can raise positive sentiment from 15% to 55%. Organisations that redesign workflows, not just deploy tools, see stronger training investments, smarter decisions and higher value creation. Clear, outcome-linked goals ensure AI use drives impact rather than experimentation. Managers need role-specific guidance, not generic training, to apply AI meaningfully. Above all, a safe, learning-oriented culture that encourages feedback reduces anxiety. Real ROI comes from reshaping how work gets done, not simply increasing usage.

Indian employees are optimistic yet anxious about AI’s impact. What should organisations prioritise first: reskilling, communication, or job redesign, to build trust and confidence?

Ashish Garg: Indian employees, like many globally, show mixed sentiment toward AI: enthusiasm about its potential to augment their work, paired with anxiety about change and the unknown. BCG’s report reflects this nuance—high usage and optimism coexist with concerns around clarity on future roles and readiness.

BCG’s research shows that trust and adoption are driven not by tools alone, but by how organisations enable people to work with AI—through clarity, capability, and role evolution. Employees who feel heard, trained, and carried through change are significantly more likely to report positive AI impact and lower fear of displacement.

We also believe that the impact on job creation is nuanced. If no action is taken, many jobs in specific areas may become redundant. However, newer jobs, which are in narrow cross sections of industry, process and products/platforms will emerge. Business leaders need to actively identify these emerging roles and create potential matches.

I think instead of trying to prioritise, consistent messaging from leadership, targeted reskilling and upskilling, redesigned (or newer) roles will manage anxiety and create more conducive environment to employees in this transition.