There is a version of this story that writes itself. A decorated technology executive with three decades at the biggest names in enterprise cloud joins a fast-growing AI infrastructure company to lead its European expansion. Competent hire, sensible career move, routine press release.

Emma Cloney does not appear to be interested in that version.

by Kasun Illankoon, Editor in Chief at Tech Revolt

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Appointed in April 2026 as Senior Vice President of International Sales and Strategy and General Manager for Ireland at Core42, the Abu Dhabi-headquartered G42 company, Cloney is operating at the centre of one of the defining technology fights of the decade: who controls the AI infrastructure that European governments and enterprises will run their most sensitive workloads on. It is not a question of product preference. It is a question of sovereignty, and the answers will shape the continent's digital autonomy for a generation.

Tech Revolt Editor in Chief Kasun Illankoon sat down with Cloney to understand what drew her to Core42 at this moment, what she has carried forward from her years inside Google Cloud and Microsoft, and what she thinks most people still fundamentally misread about where AI is actually heading.

On Choosing the Inside Track

You spent years at Google and Microsoft during their most formative growth phases. What is it about this specific moment in AI infrastructure that made you want to be inside it?

In the early days of cloud, the focus was on enabling digital transformation at scale. Today, AI is moving much closer to the core of business and national strategy, where questions around control, performance, and reliability become critical. The conversation has shifted from access to compute to how AI systems are built, deployed, and governed in production environments.

That framing, governance over access, is not accidental. It reflects a market that has matured past the evangelical phase of cloud adoption into something harder and more consequential. Cloney continues:

Organizations are moving beyond experimentation and defining what it takes to run AI reliably at scale. That is bringing sovereignty, resilience, and infrastructure design into sharper focus. What drew me to Core42 is that it is built specifically for this transition. It takes an AI-first approach to infrastructure, with sovereignty and high-performance compute designed in from the start, and the flexibility to run AI across different environments depending on customer needs.

Where the Real Friction Lives

Sovereign AI sounds coherent on paper. But European organizations are still deeply embedded with US hyperscalers. Where does the friction actually show up in enterprise conversations?

In conversations with enterprise buyers, there is a clear understanding of why sovereignty matters, particularly as AI becomes more central to operations. The challenge is how to introduce it in environments that are already deeply integrated with hyperscaler platforms.

That complexity, she explains, is not ideological resistance. It is operational reality. Dependencies between data and applications, the need to maintain performance, and the imperative not to disrupt systems already running at scale all create genuine drag on transition timelines.

Organizations are looking for solutions that go beyond high-level positioning and provide a clear path to deploy, scale, and manage AI workloads within sovereign frameworks. Enterprises are looking to introduce sovereign capabilities alongside their existing environments, allowing them to increase control without compromising performance or continuity.

It is a persuasive articulation of a hybrid strategy, one that does not ask customers to abandon their existing stacks but to extend sovereign capability across them. For Core42, that positioning has to hold up not just in pitch decks but in delivery.

Lessons Carried Forward From Google Cloud EMEA

What did your time building Google Cloud's EMEA business teach you that you are applying directly here?

One of the key lessons is that sustainable growth is built on local relevance as much as global capability. During the early expansion of Google Cloud in EMEA, there was a strong emphasis on scale and speed. Over time, it became clear that long-term success depends on how well you align with local market dynamics, whether that is regulation, data governance, or industry-specific requirements.

That perspective is shaping how she approaches Core42's expansion in Europe directly.

Establishing our regional headquarters in Dublin is about creating a strong foundation for customer delivery, technical leadership, and partner engagement within the region, rather than operating at a distance. There is also a greater focus on clarity. As AI moves from experimentation into production, organizations are looking for a clear understanding of how infrastructure decisions translate into real outcomes, particularly in areas like performance, control, and compliance.

The Trust Question: Abu Dhabi, Europe, and Sensitive Workloads

Core42 is an Abu Dhabi-backed company asking European governments and enterprises to trust it with sensitive AI workloads. How do you personally make that case?

Trust in AI infrastructure comes down to clarity and control. The focus is on making the fundamentals explicit: where data resides, how it is governed, and how customers retain control over their environments. When those elements are clearly defined and verifiable, the conversation becomes much more practical.

She is candid about where skepticism persists.

Skepticism today is less about capability and more about familiarity. Many organizations have established operating models, and expanding beyond those takes time and consistency. Our role is to support that shift by delivering infrastructure that enables organizations to scale AI with control, confidence, and long-term resilience, forming the digital backbone for AI-native operations.

Why Dublin and Not Frankfurt or Amsterdam

Ireland sits at a strange crossroads: US tech money, EU regulatory jurisdiction, and now sovereign AI ambition colliding in one small country. What does Dublin actually give Core42?

Dublin offers a unique combination of access, alignment, and execution. It sits at the intersection of global technology ecosystems and European regulatory frameworks, which makes it a practical base for engaging both international partners and regional customers. That balance is increasingly important as AI infrastructure becomes more closely tied to compliance, data governance, and cross-border collaboration.

There is also a strong concentration of talent, particularly across cloud, data, and AI, built over years of investment by global technology companies. That creates a mature ecosystem that supports both technical delivery and commercial growth.

What Most People Still Get Wrong About AI

You have been inside two of the biggest platform shifts in enterprise technology. What do most people still fundamentally misunderstand about what is actually happening right now?

Many still view AI through the lens of tools or models, when in reality the bigger change is happening at the infrastructure level. AI changes how systems are designed, how data is used, and how workloads are run at scale. It introduces new demands around performance, cost, and control that existing environments were not built to handle.

She sharpens the point around the production gap, the distance between building AI systems and running them reliably at scale.

There is also a tendency to underestimate the move from experimentation to production. Building models is no longer the primary challenge. Running them consistently, securely, and efficiently across real business environments is where complexity begins. Organizations are not just adopting AI, they are rethinking the foundations that support it. Infrastructure, governance, and operational models are all being reshaped at the same time. The companies that recognize that early will move faster. Those that treat AI as an incremental layer will struggle to scale it in a meaningful way.

The Honest Picture: Women in AI Infrastructure

When you look at where women actually sit inside AI infrastructure companies right now, what does the honest picture look like to you?

The honest picture is that progress is visible, yet it remains uneven. More women are entering technology and advancing into leadership than before, however representation in AI infrastructure is still limited, particularly in technical and decision-making roles. This reflects a combination of factors, from how early pipelines are built to how opportunities and leadership paths are shaped over time.

She frames the next phase as an execution problem rather than an awareness one.

What is changing is the level of awareness. There is a stronger understanding that building and scaling AI systems requires a broader range of perspectives, especially given the impact these systems have on real-world environments. The next phase is about turning that awareness into consistent action: creating clearer pathways into technical roles, supporting progression into leadership, and embedding diversity into how organizations build and scale for the long term.

When you eventually look back on this chapter at Core42, what is the one thing you would need to have built or changed in Europe's AI landscape to feel like the work mattered?

Success, for me, would be helping move AI in Europe from potential into sustained, real-world impact. Sovereignty going from a procurement checkbox to something operationally real: enterprises actually running production AI workloads inside European-controlled environments at scale.

She does not shy away from the ambition.

If we can help build that foundation, where enterprises and governments have the confidence and capability to deploy AI in a way that aligns with their strategic priorities, then that is meaningful progress. Ultimately, the impact will be measured by whether organizations are able to move faster, operate with greater control, and turn AI into something that delivers tangible value, not just experimentation.

What strikes you most about that answer is not its ambition but its specificity. Cloney does not talk about AI in Europe in the abstract. She talks about production workloads, operational control, and organizations that move faster. After 30 years inside the machine, she has learned to distrust grand narratives and trust execution. Whether Core42's European bet pays out will depend on many things beyond any one person's influence. But if the company is to win the credibility it needs in this market, it will need leaders who have watched these platform shifts from the inside, understand where the hard work actually lives, and are not easily impressed by the scale of the opportunity. Cloney appears to be exactly that.