Europe’s AI build, and the power it cannot find.

Leads KKR’s global digital-infrastructure investing from New York, with a portfolio spanning CyrusOne, Global Technical Realty, MetroNet, Hyperoptic, On Net Fibra, Pinnacle Towers and a Singtel data-centre joint venture, among others. One of the most influential capital allocators in the sector.

His core view is that generative AI is accelerating demand faster than efficiency gains can offset it. Even with more efficient models, the aggregate appetite for compute, storage and networking keeps climbing. He projects US data-centre power rising from roughly 18 GW today toward double or triple that within three to four years, against around 6 GW each in Europe and Asia.

KKR has put that thesis to work through a $50bn partnership with Energy Capital Partners to develop AI infrastructure, deliberately combining data centres with power generation and transmission rather than treating them as separate problems.

He has been blunt about inefficiency in the market, describing a great deal of stranded, inefficient capital and arguing that the opportunity is to re-evaluate the entire ecosystem from the molecule to the rack and beyond, integrating power, facilities, connectivity and capital under one roof.

His message is consistent: meeting AI demand requires scaled capital paired with deep sector expertise, and the winners will be integrated platforms that speak the combined language of power, data and AI.

Leads global digital-infrastructure fund strategies at DigitalBridge, the pure-play digital-infrastructure investor that rotates capital across data centres, fibre, towers and edge platforms at global scale. Her remit puts her at the centre of how the asset class is financed.

Her central theme is the migration of data centres from niche alternative real estate to core infrastructure, and what that reclassification does to how investors weigh risk and reward. The asset that was once a specialist play now sits in the same conversation as power and transport.

She frames the scaling challenge in stark terms: the sector is moving from capital pools measured in tens of billions toward the trillion-dollar commitments that AI-era infrastructure will require, and the structures that worked at the smaller scale do not simply extrapolate.

DigitalBridge’s pure-play positioning underpins her narrative. Rotating capital across data centres, towers, fibre and edge gives her a cross-sector read on where returns are compressing and where capex intensity is testing investor patience.

She is a strong voice for the global-funds question of who actually finances AI, and for how fund structures and return expectations are adapting to a market that needs far more capital than it has ever absorbed before.

Owns capacity for Oracle Cloud Infrastructure, running an organisation of more than eighty people and a capex envelope above $10bn spanning GPU and server hardware, data-centre management and power signalling. A direct line into how hyperscale capacity decisions actually get made.

His mandate is long-term capacity planning and deployment: forecasting and securing the GPU and server hardware that OCI needs, then landing it in regions where the power and grid can actually support it.

Power signalling sits at the heart of the role. Aligning Oracle’s cloud regions with available power and grid constraints is now as much a part of capacity planning as the hardware itself, particularly for AI-heavy regions where demand outruns supply.

The scale of the capex envelope, north of $10bn annually, makes his decisions a meaningful signal for the whole supply chain, from chip vendors to colocation partners to the utilities being asked to connect new load.

He is the natural voice for how a major cloud provider thinks about where and how to build or lease new capacity, and what it expects from operators, equipment makers and regulators to keep pace with AI.

A long hyperscaler career spanning global and EMEA operations and infrastructure strategy at Microsoft Azure, followed by senior cloud expansion and operations roles. His whole arc has been about hyperscaler geography and capacity strategy.

His domain is the question every market wants answered: how cloud providers choose new region locations, weighing latency, power availability, risk and regulation before committing to a geography.

On panels he tends to focus on the trade-off at the heart of expansion, balancing resilience, sustainability and sheer speed to market as new availability zones and regions are rolled out under intense demand pressure.

That operator-side perspective makes him valuable for understanding what hyperscalers actually need from data-centre partners, and why some markets clear the bar for a new region while others stall.

A practical note for any published use: his current platform affiliation has shifted across a hyperscaler career, so the exact employer is worth confirming at the point of quoting.

CTO at Digital Realty, responsible for technology strategy, platform architecture and ecosystem development across one of the world’s largest colocation footprints. A technical voice with a platform-strategy lens.

His central argument is that AI is not only a remote, hyperscale training story. Digital Realty’s strategy leans into AI inference workloads near city centres, close to the users and data that reasoning models increasingly serve in real time.

He sees customers wanting private, enterprise-controlled AI environments integrated with open interconnection and cloud on-ramps, rather than depending solely on public-cloud AI. The pitch is helping them understand their workloads and place the right infrastructure in the right location, while staying compliant and secure.

He is personally bullish on agentic AI and reasoning models, and on the dual effect they will have, transforming customer workloads while also driving efficiency improvements in the underlying infrastructure.

He is a strong technical and platform-strategy voice on where AI inference sits, why interconnection density is decisive, and how the major colocation platforms position themselves between the hyperscalers and the enterprise.

Leads NVIDIA’s EMEA strategy and partnerships across AI, cloud and data centres. His vantage point captures what the dominant AI-silicon supplier needs from the infrastructure being built around its hardware.

In 2025 he spoke to NVIDIA’s partnership with CoreWeave and Bulk Infrastructure on one of the largest liquid-ready AI deployments in Europe, framing it as the kind of build the next generation of GPUs demands.

His framing was pointed: NVIDIA needs partners building the latest large-scale, liquid-ready AI data centres, and specialist AI clouds deploying leading infrastructure, to meet customer demand. The hardware roadmap is only as useful as the facilities able to host it.

That project illustrates a broader strategy, working with specialist AI clouds and Nordic operators to secure the power, cooling and density that next-generation GPUs require, rather than assuming existing colocation will simply absorb them.

He is the natural silicon-vendor voice on what an AI-grade facility really looks like, and on why the right operator partnerships, not just the right chips, decide who can deploy at the frontier.

A veteran data-centre design and construction leader who has been a senior engineering lead at Meta and earlier ran design, procurement and construction delivery for Microsoft’s global cloud infrastructure. He now advises Fidelis New Energy on multi-gigawatt zero-carbon power projects.

He describes his focus as enabling sustainable construction and energy solutions through hyperscale designs that drive industry-wide decarbonisation, treating the build itself as a lever on emissions rather than an afterthought.

Through work with the iMasons Climate Accord, his teams have achieved around 40 per cent reductions in the embodied carbon of concrete using new materials and design choices, a meaningful figure given how much of a campus’s footprint is poured before a server is ever installed.

His current advisory work connects multi-gigawatt zero-carbon power, including hydrogen and carbon-capture projects, to the future data centres and AI campuses that will need firm clean energy at scale.

He is an ideal voice for the intersection of hyperscale construction and zero-carbon power, particularly on embodied carbon, low-carbon building methods, and integrating large-scale renewables directly with data-centre development.

At Intel she served as Chief Product Sustainability Officer and led data-centre platform strategy; in early 2025 she became Chief Sustainability Officer at HP, carrying platform-level sustainability thinking into a broader OEM role.

Her consistent argument is that sustainability must be designed into silicon and platforms from the outset rather than bolted on afterward. The decisions that shape a data centre’s energy profile are made years earlier, at the chip and platform level.

She has pushed for transparency on product-level carbon footprints and for tools that let customers tune the balance between performance and energy efficiency in data-centre CPUs and platforms, putting real levers in operators’ hands.

A core theme is aligning silicon roadmaps with emerging AI, cloud and edge workloads while still hitting aggressive corporate net-zero and circularity targets, rather than treating performance and sustainability as opposing goals.

She is an excellent voice on the link between silicon and sustainability, and increasingly on how that thinking extends from the data centre out to end-user devices through her work at HP.

Leads the OTT and edge ecosystem at HGC Global Communications, managing relationships with over-the-top players, cloud providers and partners that run on HGC’s network and edge platforms. A useful counterweight to the hyperscale-campus narrative.

His remit centres on EdgeX by HGC, an edge digital-infrastructure suite that bundles edge data centres, network, cloud connectivity and managed services to give OTTs and enterprises low-latency access points across Asia and beyond.

The strategy is about proximity. As content, gaming and interactive workloads push toward the user, the value moves to distributed infrastructure that sits close to demand rather than concentrating everything in remote mega-campuses.

His job is to grow that ecosystem through partnerships with content, gaming and cloud platforms that need distributed reach, particularly across the dense and fast-growing APAC markets.

He is a strong case study for edge and OTT-driven ecosystems, and a natural complement to any treatment of regional edge hubs and the infrastructure behind interactive and immersive workloads.