As corporate AI moves beyond pilots and experimentation, infrastructure designers and operators face a series of big challenges spanning power, resiliency, sustainability and automation
Uptime Institute today announced the release of its Five Data Center Predictions for 2026 looking beyond the more obvious trends of 2026 and examining some of the latest developments and challenges shaping the digital infrastructure industry. The 2026 predictions focus on the continued growth of the industry and related challenges, while also recognizing AI as a powerful, transformative accelerant to growth. While AI is the key driver for a wave of investment that will underpin digital infrastructure for decades to come, the speed and ultimate size of the build-outs are unclear at this time.
“Critical digital infrastructure continues to expand strongly,” said Andy Lawrence, Executive Director of Research, Uptime Institute. “At the same time, our research shows uncertainty about how AI will reshape demand. This is complicating both capacity planning and resiliency strategies. We are also seeing increasing fragmentation in the design and deployment of data centers and expect investment and innovation in carbon capture technologies, in AI, and automation in the data center itself.”
Key findings from the 2026 Five Predictions report include:
- The AI ecosystem is taking shape – with large model AI compute and high-density infrastructure increasingly concentrated among a smaller number of large organizations.
- Developers will not outrun the power shortage – AI-driven load growth will intensify pressure on already constrained grids, creating power problems, while many developers are proposing to use onsite power generation, and lengthy timelines for large scale power deployments will prove a constraint.
- Operators look to carbon capture as emissions soar – The projected 75-125 GW growth in global data center power demand through 2030 will drive greater reliance on gas turbines for primary power. For some, carbon capture will finally emerge as a practical and even economic solution to lower greenhouse gas emissions.
- Scale adds new challenges, but resiliency will still be essential – The high costs and complexity of building high density infrastructure have thrown a spotlight on the value and cost of maintaining expensive redundant capacity. But customers and investors are unlikely to tolerate increased risks and threats to availability – nor are grid operators or operators.
- AI automation in the data center moves from pilots to production – AI-driven automation within the data center will gradually transition from experimental use to supporting daily operations. Reinforcement learning, hybrid digital twins, and early industrial copilots will support closed-loop optimization and operator decision-making, while rules-based systems will handle routine workflows. But for now, humans will remain in the loop.
