Data center operators are expected to increase behind-the-meter power arrangements and explore colocated battery storage as the average wait time for a grid connection in primary data center markets exceeds four years.

Natural gas is projected to play a major role in alleviating grid constraints in the U.S., both for temporary bridge power and increasingly for permanent on-site power generation. This can be evidenced by surging global turbine orders. However, it is worth noting that some of the largest data center tenants are averse to natural gas solutions as they are not viewed as sustainable.

Natural gas as a solution is less prominent in EMEA and APAC. In these regions, renewables such as solar and wind are seeing increased utilization. In EMEA for instance, projects combining renewables and private wire transmission can reduce the cost of power for tenants by 40% compared to the grid.

Due to utility interconnection delays, some data center operators are moving beyond PPAs to directly fund their own energy generation. Additionally, a number of markets have implemented ‘bring your own power’ mandates (Ireland, Texas, et al.), which is fueling this trend.

The industry is expanding at a relentless pace, resulting in extended lead times, limited availability of skilled trades and escalating development costs.

Between 2020 and 2025, the average global data center construction cost increased from $7.7 to $10.7 million per MW, equating to 7% CAGR. For 2026, JLL is forecasting the average global cost will increase 6% to $11.3 million per MW.

Speed to power is the primary criteria driving site selection, followed by community support, latency and proximity to customers. However, as project sizes get larger, variations in construction costs may weigh more heavily in location decisions.

Note: the figures in the chart only include the cost to construct the shell and core. Tenants are typically responsible for the tech fit-out which can cost as much as $25 million per MW for AI infrastructure.

The global data center sector is estimated to grow at a 14% CAGR over the next five years, which could result in 100 GW of new capacity coming online including hyperscale, colocation and on-prem facilities. This equates to $1.2 trillion in real estate asset value creation and a need for roughly $870 billion of new debt financing.

The figures above do not include the $1 to $2 trillion that tenants will spend to fit out their space with GPUs and networking infrastructure, meaning that total data center expenditures over the next five years could approach $3 trillion. Taken all together, it is safe to say that we are in the midst of an infrastructure investment supercycle.

New data center projects are getting larger and more expensive to build. As a result, the sector continues to consolidate due to the immense development costs coupled with the increasing sophistication required to build and operate modern data centers.

These expanding barriers to entry are removing some of the speculation from the development queue and accelerating viable projects backed by credible companies. For these groups, debt markets will remain open for business.

The data center sector currently sits at the beginning of one of the largest infrastructure investment supercycles seen in the modern era. The interconnected nature of data centers means the AI-fueled expansion is reshaping a number of sectors including power, technology and real estate.

The transition from AI training to inference will redistribute workloads from centralized clusters to distributed regional hubs, fundamentally altering capacity planning and geographic deployment strategies.

Energy infrastructure has emerged as the critical bottleneck constraining expansion. Grid limitations now threaten to curtail growth trajectories, making behind-the-meter generation and integrated battery storage solutions essential pathways for sustainable scaling.

Investors and developers must balance speed to market with capital efficiency while navigating supply chain constraints and evolving demand patterns. Industry leaders must transform these converging forces into competitive advantages. The winners of this generational investment supercycle will be those who can anticipate demand inflection points while maintaining flexibility to adapt as AI models and use cases evolve.