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This is the third issue of our India Rising Perspective by Zinnov: “Engineering Europe’s Future with India”. I’m super excited that I have the opportunity to share this series with you, and thankful for the contribution by the Zinnov team.

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India’s rise as the world’s 3rd largest economy is not unfolding in isolation. It is being shaped through deep and strategic partnerships with Europe’s leading enterprises. Across Germany, the UK, and broader EMEA, companies are strengthening their global competitiveness by building long-term capability in India.

This story is no longer about outsourcing or cost efficiency. It is about engineering velocity, AI-driven transformation, workforce reinvention, and collaborative operating models that integrate India into the core of European enterprises.

To understand how this capability corridor is being built — and what it means for Europe’s future — we turn to one of the region’s leading advisors on Global Capability Centers and enterprise transformation.

In this series, Mohammed Faraz Khan, Partner at Zinnov, will share insights from across EMEA on how European organizations are designing, scaling, and transforming their Global Capability Centers in India — and how this partnership is reshaping competitiveness on both sides.

The author of today’s issue of the India Rising Perspective - Engineering Europe’s Future with India is Mohammed Faraz Khan, Partner at Zinnov.

Faraz spearheads Zinnov’s GCC Setup and Transformation practice for the EMEA region and is based in London. He advises Fortune 500 and mid-market European organizations on designing, scaling, and optimizing Global Capability Centers to accelerate globalization and unlock long-term value.

With deep expertise spanning workforce transformation, collaborative operating models, productivity enhancement, and innovation enablement, Faraz works across industries including Industrial & Engineering, Automotive, BFSI, Software & Internet, Energy, and Semiconductors. He is actively shaping the GCC narrative in EMEA and has been featured in leading publications such as The Economic Times and Fortune India.

Through this series, Faraz brings a practitioner’s lens to the evolving Europe-India partnership — grounded in enterprise transformation, AI enablement, and strategic capability building.

Enjoy the third issue of our series!

Part 3 of India Rising Perspective - Engineering Europe’s Future with India
By Mohammed Faraz Khan

In a Siemens Healthineers lab, AI isn’t something you interact with. It’s something you rely on.

It operates quietly in the background—interpreting scans, correlating patient data, and supporting clinical decisions in real time. Systems like AI-Rad Companion aren’t standalone tools; they are embedded into the product itself, designed to function seamlessly within clinical workflows, not alongside them.

That distinction is often overlooked—and it matters.

Much of today’s AI narrative is shaped by what is visible: copilots, assistants, and conversational interfaces. These are important, but they represent only one layer of how intelligence is being deployed.

In many of Europe’s most critical industries—healthcare, manufacturing, energy—the more consequential applications of AI are not interfaces at all. They are deeply integrated into machines, infrastructure, and operational systems. They don’t announce themselves. They don’t require interaction. But they continuously shape outcomes.

This is where AI shifts from being a tool to becoming infrastructure.

And that shift raises a more fundamental question: if the most impactful AI is the least visible, where is this intelligence actually being built—and who is shaping it?

Across European enterprises, AI adoption is not unfolding evenly. The shift, is less about widespread deployment and more about selective embedding into engineering and product systems.

This unevenness becomes clearer when we look at how capability is distributed. Within Germany GCCs for example, only 27% of centers currently have AI/ML capabilities, while more established domains such as cloud and cybersecurity have seen broader adoption- according to Zinnov’s Germany GCC report.

This is not simply a question of lag. It reflects how AI evolves in industrial contexts. Unlike cloud or security — which scale horizontally across systems — AI in these environments is domain-specific, system-integrated, and inherently harder to standardize.

As a result, capability does not diffuse evenly. It concentrates- across domains and regions too.

Nearly 80% of Germany GCC AI capability is clustered in Bengaluru and Pune, creating dense hubs of engineering and AI expertise.

These clusters play a critical role. By bringing together domain expertise, engineering depth, and platform development, they allow AI initiatives to move beyond isolated pilots and into scalable, production-grade systems.

For a long time, the value of GCCs in India was built around scale and execution.

That foundation has already begun to evolve. Zinnov’s analysis shows that in 2015, nearly 70–80% of GCC work was execution-focused, whereas today a significantly larger share sits in expertise-driven and frontier work, bringing India’s portfolio closer to that of headquarters.

AI is now accelerating this shift.

Zinnov’s latest GCC AI Opportunity Report highlights that more than 55% of GCC work portfolios are under displacement pressure, as AI compresses the journey from expertise to automation.

This does not simply reduce work — it changes how work is structured and where value is created.

Tasks that once required years of experience — diagnosing failures, interpreting patterns, optimizing systems — are increasingly being codified into models and embedded directly into products.

As that happens, the mix of work begins to shift.

There is a growing need to combine execution with what the report describes as “grey hair” capability — deep domain expertise combined with technical fluency — especially in areas where systems, data, and engineering intersect.

This is where the role of India’s GCCs is evolving.

Rather than being concentrated in execution alone, these centers are increasingly taking on work that sits across engineering, data, and domain context — complementing their existing strengths.

That shift is visible in how organizations are approaching AI.

At Deutsche Bank, for example, its India GCC has adopted a startup-style incubator model (“AI Forward”), training over 20,000 employees and embedding AI specialists within teams to prototype solutions in live environments. The focus is not just adoption, but ownership — with the bank targeting a growing share of product and platform responsibility from its GCCs.

Across industries, similar patterns are emerging:

Even in organizations like Ericsson, the challenge is no longer building isolated AI models, but creating structures that allow those capabilities to scale across domains.

What this points to is a broader shift.

AI is not just changing how work is done.
It is reshaping how different types of work come together to create value.

What emerges from these patterns is not a relocation of innovation, but a redistribution.

For European enterprises, this model reflects both necessity and design:

Zinnov’s analysis shows that India’s GCC portfolio has already shifted significantly toward expertise-driven and frontier work — in some cases approaching parity with headquarters.

India’s role in this model is not to replace Europe’s strengths, but to extend them — particularly in areas that require scale, continuity, and integration across engineering and AI.

The next phase of AI in Europe will not be defined by what is most visible. It will be defined by what is most deeply embedded — inside products, systems, and infrastructure.

And increasingly, that work is being built across a network.

Sources: Zinnov

If you want to explore more on this topic or have questions, please reach out to the author via LinkedIn.

Disclaimer: Any use of the data or graphics require prior approval from Zinnov.

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