We believe, the narrative around artificial intelligence often focuses on the models themselves: the parameters, the capabilities, and the benchmarks. However, the physical reality of AI is a story of concrete, steel, and massive power generation. The recent news that OpenAI is negotiating a 20-year lease on a 10-gigawatt data centre campus in Ohio underscores the staggering scale of the infrastructure required to sustain the AI boom.
This proposed facility, backed by Nvidia and developed by SoftBank's SB Energy, represents a paradigm shift in construction finance. We are no longer talking about standard data centres; these are multi-billion dollar mega-projects that are creating a new asset class entirely. The Ohio campus alone is estimated to represent a $500 billion scale investment over its lifespan, with the first phase expected to be operational by 2028.
For the AEC sector, this represents a fundamental shift in how we think about infrastructure investment and project delivery. The scale and complexity of these projects demand specialised expertise in power systems, thermal management, and industrial construction. The firms that can master these capabilities will find themselves at the forefront of a generational infrastructure boom.
The scale of this build-out is difficult to overstate.
According to Goldman Sachs research, the baseline model implies "$765 billion in annual AI CapEx in 2026, growing to $1.6 trillion in annual CapEx in 2031."
This capital expenditure is not just going into silicon; a significant portion is directed towards the physical infrastructure required to house and power these chips.
The Financial Architecture of the AI Boom
The financing of these mega-projects is evolving as rapidly as the technology itself. We observed a wave of major financial announcements recently that highlight this shift. Broadcom, in partnership with Apollo and Blackstone, launched a $35 billion platform specifically to finance AI infrastructure. Simultaneously, a consortium including KKR, the Kuwait Investment Authority, Nvidia, and Vistra formed a new company dedicated to funding and building AI data centres.
This influx of private equity and sovereign wealth into data centre construction indicates that the market views AI infrastructure as a foundational, long-term asset. The sheer volume of capital required has even led major financial institutions like Goldman Sachs and JPMorgan to explore compute futures trading, treating processing power as a tradable commodity akin to oil or wheat.
For the AEC sector, this represents a generational opportunity. The construction of these facilities requires highly specialised engineering, particularly in power management and cooling systems. The International Energy Agency (IEA) notes that "Data centres accounted for 4% of total U.S. electricity use in 2024. Their energy demand is expected to more than double by 2030." Managing this energy demand is a critical engineering challenge.
The Engineering Challenge
The shift towards AI-specific data centres fundamentally alters the design and construction requirements. Traditional data centres are designed for standard cloud computing workloads, but AI training and inference require significantly higher power densities.
MIT Sloan research highlights that "Data centers could account for up to 21% of overall global energy demand by 2030 when the cost of delivering AI to customers is factored in."
This increased power density necessitates advanced cooling solutions, such as direct-to-chip liquid cooling, which in turn requires specialised plumbing and mechanical engineering. The construction costs reflect this complexity. Industry forecasts for 2026 suggest that the average global cost to build a modern data centre will increase to approximately $11.3 million per megawatt.
Furthermore, the location of these facilities is increasingly dictated by access to power rather than proximity to population centres. The Ohio project, for instance, involves a significant investment in natural gas generation to meet the 10 GW demand. This integration of power generation and data centre construction creates complex, multi-disciplinary projects that require a holistic approach from AEC firms.
The Competitive Landscape
The Ohio project is just one piece of a much larger infrastructure puzzle. Across the United States and globally, similar mega-projects are in development. The involvement of major financial institutions and technology companies signals that this is not a temporary trend but a fundamental shift in how computing infrastructure is financed and developed.
For AEC firms, this competitive landscape presents both opportunities and challenges. Firms with expertise in power systems, thermal management, and large-scale industrial construction are well-positioned to capture significant market share. However, the rapid pace of development means that firms must quickly build capabilities in AI-specific data centre design and construction.
The financing landscape also suggests that project delivery timelines are accelerating. With billions of pounds in committed capital, developers are incentivised to move projects from conception to operation as quickly as possible. This puts pressure on AEC firms to deliver faster without compromising quality or safety.
The Global Expansion
Whilst the Ohio project captures headlines, the AI infrastructure boom is truly global. Similar mega-projects are in development across Europe, Asia, and other regions. The UK, for instance, is positioning itself as a hub for AI infrastructure investment, with several data centre projects in development. This global expansion creates opportunities for AEC firms with international capabilities and experience in complex infrastructure projects.
The competition for these projects is intense. Firms that can demonstrate expertise in power systems, thermal management, and rapid project delivery will have a competitive advantage. Moreover, the ability to navigate complex regulatory environments and secure the necessary planning permissions is increasingly important. AEC firms that can combine technical excellence with regulatory expertise will find themselves well-positioned to capture market share in this rapidly growing sector.
The AI infrastructure boom also has implications for supply chains and material sourcing. The demand for specialised components, such as advanced cooling systems and power distribution equipment, is driving innovation in these sectors. AEC firms that can work effectively with suppliers and manage complex supply chains will be better positioned to deliver projects on time and within budget.
Takeaways
• A New Asset Class: AI data centres have evolved into a distinct asset class, attracting massive investments from private equity and sovereign wealth funds, fundamentally changing the financing landscape.
• Unprecedented Scale: Projects like the 10 GW Ohio campus represent hundreds of billions of dollars in investment and require specialised engineering capabilities in power management and thermal systems.
• Power is the Limiting Factor: The immense energy demands of AI models are driving the integration of power generation and data centre construction, making location and energy access critical factors.
• Accelerating Timelines: The volume of committed capital is driving rapid project development, putting pressure on AEC firms to deliver faster without compromising quality.
• AEC Opportunity: The AI infrastructure boom presents a generational opportunity for AEC firms capable of delivering complex, high-density facilities with expertise in power systems and thermal management.
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All content reflects our personal views and is not intended as professional advice or to represent any organisation.
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