GCCs step up AI upskilling to meet tight adoption deadlines

India’s Global Capability Centres (GCCs) are increasingly training their own employees in AI instead of hiring talent from outside, as companies struggle with limited supply of specialists, fast-changing skill needs, and accelerated AI adoption timelines. The change is substantial and happening quickly, according to data from workforce intelligence firms.

Internal mobility now fills about 27% of future-tech and AI roles within GCCs according to TeamLease Digital. “Most large-scale GCCs that expanded significantly over the past few years are now focusing on transforming processes and building internal AI capacity,” said Neeti Sharma, CEO, TeamLease Digital.

Another data source, Bharatiya Converge, shows a similar trend. Internal redeployment into AI/ML roles in mature GCCs has risen from roughly 15% last year to 30-45% this year, fuelled by structured capability-building programmes rather than ad-hoc learning. One reason for the shift is the rapid evolution of skill requirements.


“By 2027, nearly 40% of current tech skills will be partially obsolete, not due to job loss, but because of skill fusion and the adoption of AI-aligned skills,” said Roop Kaistha, regional managing director, APAC, AMS. He pointed out that GCCs are responding by creating multidisciplinary, AI-aligned positions internally because existing engineers are often more qualified for hybrid skill requirements than lateral hires.

The expanding scope of mandates now anchored in India is another factor contributing to the change. According to consultancy ANSR, more than 70% of GCCs in India are now in charge of their company’s global AI mandate, which includes model development, platform engineering, fraud analytics, cybersecurity, and integrating AI into various processes and products.

“Instead of competing in a crowded lateral market, GCCs are finding that structured internal development pipelines deliver talent faster, at lower cost, and with far better enterprise context,” ANSR said.

These initiatives have been formalised by large employers. To prepare existing employees for AI-heavy roles, several GCCs have rolled out internal academies, role-based skill stacks, and AI proficiency pathways. For instance, TechMahindra trained tens of thousands of workers in multi-tier AI learning courses.

“A meaningful share of our AI and ML roles today are being filled internally, nearly double that of last year,” said Kunal Purohit, president, Next Gen Services. “Upskilling is no longer measured by participation, it is measured by redeployment,” Bhartiya Converge noted, adding that transitions are growing fastest in analytics automation, AI product enablement and solution consulting.

However, internal mobility varies depending on the type of role. Internal transitions are a good fit for service-end AI roles, such as analytics operations, automation support, and AI product workflows, according to Xpheno. But lateral hiring continues to play a major role in core AI engineering, due to limited availability.

“Only around 6,000 professionals sit in AI engineering across GCCs,” said Anil Ethanur, co-founder, Xpheno, noting that roles such as AI architects, ML platform engineers and systems specialists continue to face sharp supply shortages.

NASSCOM data show about 15% of GCCs have already reached advanced AI capability maturity, and over 30% of technology and internet companies have established AI Centres of Excellence in India, underscoring the growing depth of internal capability-building. As external hiring for AI positions slows, India is positioning itself as a global hub for enterprise-scale AI workforce development, with GCCs increasingly viewing AI talent as something they must develop rather than buy.