Where the Firm Learns Now:

GCCs and the New Operating Model of Knowledge Work

Last week I suggested that 2026 feels odd because our familiar ways of thinking are not aligning with the world as it is today. We keep trying to explain the world with single-cause stories, hybrid work, AI, rates, geopolitics, talent shortages, and each one is true enough on its own. But experienced together, they create a kind of conceptual vertigo.

This week I want to make one of the quieter structural shifts much clearer: the rise of the Global Capability Centre (GCC) as a default design pattern for large organisations.

Not as a footnote to globalisation, but as a clue to where firms are choosing to build themselves.

The GCC as operating-model infrastructure

A GCC in India still gets described, casually, as “offshoring”. That language is a hangover. It carries the intuition of factories and back offices, things moved for cost reasons, tasks reallocated, efficiency extracted.

What is happening now is more interesting and, I think, more consequential.

A modern GCC is increasingly where large organisations build and maintain the machinery of contemporary knowledge work. Not simply running processes, but owning platforms and capabilities that everything else depends on: engineering, data, analytics, cybersecurity, product modules, AI operations, internal tooling. In many firms, these centres are where competence compounds, where people stay longer, systems get understood deeply, and teams develop muscle memory.

The most important effect isn’t always visible as layoffs “at home”. The more common mechanism is that the next wave of roles, especially the ones that form career ladders and leadership pipelines, land somewhere else. It is growth displaced rather than jobs replaced.

That is a very different kind of shift to the one most public debate is set up to recognise.

What actually gets done inside a GCC (in 2026 terms)

It helps to break GCC work into layers, because they are often conflated:

1) Industrialised execution

These are repeatable, verifiable outputs:

• Data engineering and pipeline maintenance

• QA and testing

• Production analytics and dashboards

• Reporting, reconciliations, controls

• Operational risk processes, monitoring

  This is the “cognitive factory” layer: high throughput, high standardisation, measurable outputs.

2) Platforms and orchestration

The systems and workflows that make the firm run:

• Internal tools and automation

• Enterprise workflow design

• MLOps / AI ops (model deployment, monitoring, governance mechanics)

• Cloud and platform engineering

• Integration work across teams and systems

This layer is where capability becomes an asset, because once you own the platform, you shape what is possible.

3) Resilience, controls, and risk infrastructure

The nervous system of the organisation:

• Cybersecurity architecture and operations

• Incident response

• Identity, access, and controls engineering

• Compliance tooling and audit readiness

• Operational resilience programmes

These functions rarely get the glamour, but they have become existential. That pushes them toward scale and continuity.

4) Product and engineering ownership (increasingly common)

This is the significant shift:

• End-to-end ownership of services or product modules

• Feature development tied to global roadmaps

• Data products, model products, and internal “platform as a product” teams

At this point the GCC stops being a support function and becomes part of the organisation’s core building capacity.

The important point is not that every GCC does all of this, but that the direction of travel is clear: these centres are moving up the stack.

Why firms do this: the overlooked economics of coordination

Most people assume the dominant driver is cost. Cost matters, of course. But if cost was the whole story, we would see these centres treated as interchangeable labour pools, constantly shopped around.

Instead we see firms committing long-term capital, large footprints, and leadership attention. That tells you something else is doing the heavy lifting.

The under-discussed driver is coordination economics.

Modern knowledge work, especially in large firms, is not primarily constrained by the ability to hire brilliant individuals. It is constrained by the ability to field coherent, stable, persistent teams that can build complex systems over time.

What kills productivity is not the salary line. It is:

• High churn and short tenure

• Constant re-forming of teams

• Loss of institutional memory

• Weak shared context

• Senior time spent endlessly recruiting and re-aligning rather than building

A large, well-run GCC can reduce that coordination drag because it often offers:

• Greater team stability

• Longer tenures

• Deepening shared context

• Stronger internal labour markets and career ladders

• A culture built around platform stewardship rather than constant reinvention

This is a new organisational physics.

Last week I discussed JPMorgan’s commitment to a Brookfield-developed campus in India, institutional-grade capital, not a temporary lease. Microsoft’s India Development Center is one of its largest R&D centres outside Redmond and contributes materially to core Microsoft products and platforms. Over 130 UK firms operate Indian GCCs employing 200,000 professionals. The shift is real.

And once you see it, the GCC becomes less a “location choice” and more a structural choice about how the firm wants to learn and compound capability.

Note: This is not across the board, and the market is changing rapidly. Tier-1 Indian cities face attrition rates of 20–25% in IT roles; Tier-2 cities like Indore, Coimbatore, and Kochi offer 8–12%. That stability matters increasingly for agentic workflows, where deep institutional knowledge is required to train and govern AI systems effectively.

Separately, infrastructure is creating new centres of gravity. Google’s $15 billion investment in Vizag - gigawatt-scale data centre operations and a new subsea cable gateway - signals that AI-era location decisions are driven as much by power and connectivity as by talent.

A historical rhyme: the invisible move

This has echoes of manufacturing, but the similarity is easily overstated.

Manufacturing relocation was legible:

• Factories shut

• Jobs disappeared from specific places

• Whole local ecosystems unraveled

Knowledge work relocation is quieter. It arrives as “global delivery models”, “platform teams”, “centres of excellence”. It often looks, in the moment, like perfectly reasonable corporate housekeeping.

Which is precisely why it has such power.

The story of the last few decades is full of shifts that were operationally rational and politically unreadable until they were entrenched. Supply chains reorganised; politics arrived later, and often with language that didn’t match the structure of the change.

Something similar is happening now.

Public discourse is still most fluent when the issue is visible and physical: factories, borders, trade in tangible goods. Knowledge work is harder to narrate because it doesn’t vanish in a single closure. It thins. It relocates as future growth. It becomes a missing ladder rather than a headline.

In a way, politics helps to hide the shift, not always deliberately, but structurally, because it tends to focus on what can be pointed at, photographed, and blamed. The more important change is often administrative and slow.

Why this connects to London (and other global cities)

A question that naturally follows is: if GCCs are where so much capability is being built, why do firms still invest so heavily in major hubs?

I think we are watching the “office” split into two functional roles, and the split is becoming sharper:

• Capability hubs (often GCCs): places where execution at scale, platform building, and operational intelligence are concentrated

• Commitment hubs (major global cities): places where client relationships, regulatory accountability, senior arbitration, and legitimacy are concentrated

These are different forms of work. They require different densities, different rhythms, different building types, and different economic logic.

It also helps explain why you can see large commitments to prime space in London alongside large commitments to capability centres elsewhere. The firm is not choosing one geography. It is designing a system with multiple centres of gravity.

The most important mechanism for the West: “missing growth”

If you want one phrase to hold onto, it’s this: missing growth.

The typical effect is not that Western offices empty overnight. It is that:

• headcount growth slows

• junior and mid-level ladders thin

• whole cohorts of roles that used to be created domestically are created elsewhere

• platform ownership and learning accumulate away from traditional hubs

This matters deeply for cities because cities do not just depend on jobs; they depend on:

• ladders

• clustering

• progression

• the density of early-career opportunity

• the social infrastructure of an upper-middle class that compounds skills and civic capacity over time

When you displace growth, you eventually displace the social fabric built on that growth.

That is why this is a city story, not just a corporate efficiency one.

The AI twist

One more nuance is important, even in a GCC operating-model piece.

GCCs are often built to standardise and systematise work. That is what makes them scalable. It also makes parts of them legible to automation. AI does not arrive later as an external disruption; it arrives inside these centres as a force that compresses the very work they were designed to industrialise.

That does not mean GCCs are a short-term fad. It suggests a more complex trajectory:

• growth and consolidation now

• compression of industrialised execution later

• a shift towards orchestration, governance, exception handling, and platform stewardship

This is worth holding in mind because it affects both labour-market expectations and real estate planning in GCC locations too.

But the immediate point remains: today, GCCs are where firms are choosing to build capability at scale.

What this means for commercial real estate

Put all of this together, and you get an explanation for a pattern many of us feel in the market:

Office demand isn’t behaving the way the old models said it should.

Hybrid work is part of the story. Rates are part of the story. But underneath them is a deeper decoupling: organisations are learning to scale capability without scaling domestic space in the way we once assumed.

For CRE, that implies:

• A lower long-run demand ceiling in many Western markets, even if prime assets remain resilient

• More polarisation between buildings that support high-stakes coordination and those designed for routine execution

• Weaker development optionality (less need for large “growth leases” and expansion rights)

• A sharper distinction between cities that host commitment and cities that host capability

And perhaps most importantly:

• the office becomes less a universal container for work and more a specialised instrument for particular human functions.

That is an argument for clarity, not simply optimism or pessimism. We have to deal with the world as it is.

A closing question

If GCCs are becoming operating-model infrastructure, places where competence, continuity, and platform ownership increasingly compound, then we have to ask a question that commercial real estate has not been forced to ask in decades:

Where does the organisation actually learn now?

Because where it learns is where it eventually invests, not just in buildings, but in people, influence, and long-term relevance.

Next week I’ll add the accelerant: AI. Not as a general technology story, but as the force that re-sorts work into execution and judgement, and, in doing so, reshapes both offices and participation in value creation.

For now, one question to leave you with:

If growth is being displaced rather than destroyed, what would it mean to value office markets by “missing absorption” as much as by vacancy?