Uptime Institute has published its Five Data Center Predictions for 2026, outlining how digital infrastructure is expected to evolve amid accelerating growth. The report examines deeper structural shifts in data center design, financing, and operations, highlighting artificial intelligence as a major growth driver while noting continued uncertainty around the pace and scale of future build-outs.
Uptime Institute’s Five Data Center Predictions for 2026 report offers a forward-looking assessment of how digital infrastructure is likely to evolve as the industry enters another phase of rapid expansion.
The report by Uptime Institute looks beyond near-term trends to examine structural shifts shaping data center design, financing, and operations, with artificial intelligence emerging as a powerful but still unpredictable accelerant. While AI is driving unprecedented investment that could underpin digital infrastructure growth for decades, the pace and ultimate scale of build-outs remain uncertain, complicating long-term planning for operators, developers, and investors.
According to Uptime Institute, critical digital infrastructure continues to expand strongly across regions, but AI-driven demand is reshaping assumptions that once guided capacity planning and resiliency strategies. Andy Lawrence, executive director of research at Uptime Institute, noted that while growth remains robust, uncertainty about how AI workloads will evolve is creating new challenges. Operators must balance the need to support high-density compute environments with concerns around power availability, grid constraints, and operational resilience.
One of the central themes of the 2026 outlook is the consolidation of the AI ecosystem. Large-scale AI compute and high-density infrastructure are increasingly concentrated among a relatively small group of hyperscalers and well-capitalized enterprises. This concentration reflects the immense capital, power, and technical expertise required to deploy and operate next-generation AI platforms, potentially widening the gap between large and smaller infrastructure players.
Power availability is another major constraint highlighted in the report. AI-driven load growth is intensifying pressure on electricity grids that are already stretched in many markets. While some developers are proposing on-site power generation to bypass grid limitations, Uptime Institute warns that lengthy timelines for deploying large-scale power infrastructure will remain a bottleneck. As a result, access to reliable power is becoming a defining factor in site selection, lease negotiations, and long-term competitiveness.
Accepting Higher Risks to Availability?
The report also points to rising emissions as global data center power demand is projected to grow by 75 to 125 gigawatts through 2030. To meet this demand, many operators are expected to rely more heavily on gas turbines for primary power. In this context, carbon capture technologies – long discussed but rarely deployed at scale – may finally become both practical and economically viable for some operators seeking to reduce greenhouse gas emissions without compromising reliability.
As facilities scale up to support higher densities, resiliency remains non-negotiable despite rising costs. The expense and complexity of building redundant capacity in high-density environments have renewed scrutiny on traditional resiliency models. However, Uptime Institute suggests that customers, investors, and grid operators are unlikely to accept higher risks to availability, reinforcing the need for robust design even as economics tighten.
Finally, the Uptime Institute report anticipates that AI-driven automation within data centers will move from pilot projects into production environments. Technologies such as reinforcement learning, hybrid digital twins, and early industrial copilots are expected to support closed-loop optimization and operator decision-making. While rules-based systems will handle routine workflows, human oversight will remain essential for the foreseeable future.
Executive Insights FAQ
Why is AI creating uncertainty in data center planning?
AI workloads are growing rapidly, but their long-term scale and utilization patterns remain difficult to predict.
Who is leading large-scale AI infrastructure deployment?
High-density AI compute is increasingly concentrated among a small number of large, well-capitalized organizations.
What role does power availability play in future growth?
Grid constraints and long deployment timelines for power infrastructure are becoming key limiting factors for new data centers.
Why is carbon capture gaining attention now?
Rising emissions and increased reliance on gas turbines are making carbon capture more viable as a mitigation strategy.
How will AI automation change data center operations?
AI tools will increasingly support daily operations, but human oversight will remain critical in the near term.
