Tech Depth vs Domain Context: The Make-or-Break Choice for Enterprise GCCs

Global capability centres (GCCs) in India have become the fastest-moving test bed for a problem enterprises everywhere are wrestling with: how do you teach people, and machines, to do a job before the job itself changes?

Vishnupriya Raghavan, who leads NIIT's Enterprise Tech business and has supervised hundreds of enterprise AI rollouts as a training partner, observes that the runway for programme design that used to take four to eight weeks, from requirement-gathering to rollout, has virtually vanished. 

"There is no time for a lengthy build cycle that risks training staff on a technology that has already changed by the time the course is delivered,” the Senior VP and Business Head, Enterprise IT Business, at NIIT’s immersive technology learning division, StackRoute, tells AIM.

That compression is reshaping what the skills and talent development company builds and how it measures training success. Rather than simply issuing a certificate, NIIT now designs programmes around outcomes it can track for months afterwards, proposal win rates, and client conversion figures. 

Raghavan believes tracking outcomes has now become essential. "You can't say that you're ready to run a marathon by writing an MCQ test," she notes, arguing that mentors should analyse and introspect student performance even after the course ends.

Inside GCCs, the gap between capability and the demand for specialised technology skills is only widening. According to a recent report by Quess Corp, while AI, data, and analytics sector emerged as the fastest-growing capability area, it also recorded the largest supply-demand gap of between 36–40%.

Addressing the Skills Gap

Global systems integrators have long built layered career paths because staff rotate between clients and projects. However, GCCs, by contrast, were historically built to hire at market rate for a single, end-to-end mandate. 

That model is under strain now that a lead engineer's brief has expanded well past feature delivery. "Deterministic software is becoming reasoning systems," Raghavan notes, leaving GCCs to build competency programmes they were never structured to run in-house, on a timeline that keeps shrinking.

This is also, in effect, why NIIT has restructured itself. The company recently folded two of its technology-training arms, StackRoute and RPS Consulting, into a single Enterprise Tech business built specifically to manage large-scale workforce transformation rather than standalone courses.

NIIT has been focusing on building its enterprise to build digital fluency, strengthening workforce capabilities, and supporting digital transformation efforts. In the fourth quarter of fiscal year 2026, NIIT's enterprise segment accounted for 63% of the company's total revenue, helped by 64 new enterprise clients over the past year, while technology programmes grew 20% year-on-year to make up 72% of overall revenue during the entire year. 

“Companies used to come to NIIT asking it to teach AI as a standalone subject. Now, AI is woven into every part of the curriculum, with the company increasingly engaging clients on governance and organisational change alongside technical skilling,” Raghavan adds. 

The Missing Context

Beyond supporting layered digital transformation, a training function alone cannot absorb the culture and outcomes expected of a GCC business unit.

"The biggest missing piece in enterprise AI today is just the missing context," comments Shivali Goyal, Co-founder and CEO of Trupeer AI, a workflow automation startup that converts screen recordings into edited videos, guides, and a searchable knowledge base. She compares an AI agent entering a company to a new hire with no access to internal processes, applications, or policy. Tools that perform well in a demo often fail once deployed because staff end up feeding the same context back into the system repeatedly.

That is precisely the gap GCCs feel hardest during process transitions—work that traditionally required someone from a parent company's headquarters to sit inside an Indian centre, document a process by hand, and train staff on it directly. "That process today is so broken," she notes, describing transitions that took months now happening in days.

The scale case is a business process outsourcing company Trupeer catered to that needed to train 140,000 staff on a new HR system across six languages—a rollout Goyal says would ordinarily take 12 months, completed in under three using recorded video content translated automatically rather than rebuilt for each market.

Governance also needs to keep pace. Role-based access control (RBAC), which restricts system access based on a user’s specific job role, is being carried over from conventional software rather than invented for AI. "RBAC is extremely important, and even more important, I would say, in AI than it was in traditional SaaS," she notes, since without it a query in one department can surface information that belongs to another. 

NIIT and Trupeer are attempting to make GCCs AI-ready from differing directions. 

NIIT's is closing a mentorship and governance gap as GCCs lack a single owner tracking whether competency programmes actually changes behaviour over time. Meanwhile, Trupeer is giving AI systems and new staff context on how a company actually works.

For fast-moving GCCs, closing at once is becoming critical.