India’s AI race has the wrong finish line

India’s GCC story has been one of the clearest expressions of the country’s technology success. As global demand grew, companies built larger teams, deeper capabilities, and bigger delivery footprints in India. More work meant more skilled capacity, and scale became a measure of success.

It was therefore natural for GCC success to be judged through operational measures such as cost efficiency, productivity, throughput and headcount. Those measures showed whether a centre was doing more, faster and at greater scale.

Those measures are not wrong. The risk is in treating them as the finish line.

The numbers across India’s technology sector already hint at why. The industry is expected to cross $315 billion in FY26, while direct employment grows just 2.3% to around 6 million. NASSCOM also estimates that 20-40% of work across technology organisations is already being done through AI.

AI raises the potential of what GCCs can deliver. The question is no longer only how efficiently a GCC operates, but how closely that efficiency connects to a business outcome.

Can GCCs create significantly more enterprise value without organisational size increasing at the same rate? If yes, AI could change what scale means for GCCs altogether.

Size becomes a byproduct

For much of the GCC journey, more responsibility often meant a larger centre. As GCCs moved from execution into engineering, product, data and innovation, size remained an important proxy for ambition. The next phase requires a different measure.

A GCC should increasingly be judged by the value it creates rather than how large it becomes. If an organisation is X in scale and Y in revenue today, could it imagine becoming 0.25X and 5Y tomorrow?

That is not an argument for shrinking GCCs. It challenges the assumption that greater enterprise value must require proportionately more people and organisational mass.

A future GCC may become far more consequential without becoming dramatically larger. Size becomes a byproduct of the value created rather than the ambition itself.

Efficiency matters, but it cannot be the end measure

The easiest AI gains to measure are operational ones. A process that once handled 500 transactions can handle 800. Work that took four weeks can be completed in two. Those are real gains and should continue to be measured.

The problem begins when measurement stops there. A team can become dramatically faster without the business becoming dramatically better. Automating one part of a process can simply move the bottleneck elsewhere. It is like building a flyover on a congested road. Traffic moves faster through one section, only to pile up further ahead.

The same applies to GCCs. An operational metric tells us how efficiently work is being done. A business metric tells us why that efficiency matters. If a team is measured only on volume and turnaround time, the incentive is to produce more, faster. If it is also accountable for the business outcome, efficiency gains direction.

AI can make old processes faster. The larger opportunity is to ask whether those processes should work that way at all. Running faster creates value only when the organisation is clear about the direction in which it is running.

The next advantage is enterprise context

India’s mature GCCs have an advantage that goes beyond talent availability. Decades of working inside global enterprises have created deep domain knowledge. Many GCCs now work across functions, while senior talent increasingly owns problems and outcomes rather than simply executing predefined tasks.

That gives GCCs a horizontal view of the organisation that individual functions do not always have. This becomes more valuable as AI moves deeper into the enterprise. AI works better when it can connect knowledge and context across organisational boundaries.

A GCC that sits across multiple parts of the business can therefore offer more than additional capacity. It can become a place where enterprise context is brought together and turned into innovation.

The closer a centre gets to influencing business outcomes, the harder it becomes to judge it only through activity, utilisation or cost.

From outpost to nerve centre

That changes the role of the GCC itself. The traditional GCC could be thought of as the fuel tank of a car. A larger tank allowed the organisation to travel further. The next-generation GCC needs to be woven through the vehicle itself.

That means bringing product, technology, data, strategy and business understanding together inside a centre that is culturally integrated with the wider enterprise.

In some organisations, the nerve centre is already beginning to shift. Not because work is being moved to India by default, but because talent, domain knowledge and enterprise context make it logical for more consequential work to sit here. The significance of the GCC then stops being how much work it absorbs. It becomes how much of the enterprise it can influence.

The real measure of progress

India’s GCC ecosystem spent decades proving that global enterprise capacity could be scaled through talent. That foundation does not become irrelevant in an AI-led world. It becomes the starting point for something more ambitious.

Operational efficiency will remain part of the scorecard. It should. But the ambition cannot end there. The more meaningful measure is whether those gains move the GCC closer to a business outcome, whether that is revenue, cost, customer value, innovation or another enterprise priority.

Enterprise value may no longer need to grow in lockstep with headcount, footprint and organisational complexity. The opportunity is therefore not to replace the strengths that built India’s GCC model, but to build on them while expanding the aperture of what a GCC can own and influence.

If India’s GCCs can make that shift, they will not simply have found a more productive version of the old model. They will have begun to define what comes after talent-led scale by building on the strengths that got them here in the first place. Domain context, operational discipline and talent remain the foundation. The next step is to connect those strengths to greater ownership, influence and business value.

(The author is EVP and MD, Publicis Sapient India. Views are personal.)