2026 State of AI Infrastructure Report

NEW survey report dives deep into how organizations are confronting complexity, harnessing cloud, managing energy demands, and closing the AI skills gap.

What 600 Leaders Reveal About Building the Foundation for AI Success

As organizations move from AI pilots to production, they’re uncovering four pressures that weren’t visible before: rising infrastructure complexity, cloud environments stretched by new workloads, unexpected power and cooling demands, and operational skill gaps that slow day-to-day progress. These realities are creating a clear divide between teams that advance and teams that stall—driven by choices about architecture, operating model, and where to invest next.

98%

face a skills gap related to AI infrastructure

93%

are working to reduce AI’s energy footprint

65%

say their AI environments are already too complex

54%

delayed or cancelled an AI project in the past 24 months

What Successful AI Teams are Doing

Explore the strategies helping teams build AI that scales and adapts to what comes next.

97%

say cloud is essential to scaling AI

72%

of enterprises are working with partners to build and run AI infrastructure

63%

have begun consolidating or modernizing their environments to reduce complexity

57%

improved time-to-results after modernizing AI data pipelines

QUOTE

We face challenges every day and must learn to deal with them — integration, scalability, being able to adapt… AI is such that we are learning every day.

IT decision maker
Pharma/Life Sciences

AI Infrastructure Has Become the Make-or-Break Factor

AI workloads strain traditional environments. Most systems weren’t built for distributed data, multimodal concurrency, or continuous inference — and complexity has become the #1 drag on AI ROI.

Winning Formula: Leaders simplify, consolidate, and build unified data access — not additional layers.

65%

report excessive infrastructure complexity

3+

month delays in time-to-value with complexity

54%

have postponed or cancelled AI initiatives

Cloud Is the Fastest Path to Early, Predictable AI Outcomes

Cloud has become the default starting point for AI — not because it’s the final answer, but because it removes the biggest early blockers: access to GPUs, variable scale, fast experimentation, and ease of iteration. Teams starting in cloud report smoother onboarding and fewer early failures.

97%

say cloud is critical to scaling AI

70%

use cloud for AI data operations

69%

use cloud for AI experimentation and development

AI Is Exposing Power, Cooling, and Efficiency Gaps That Block Progress

AI introduces power and thermal demands that most infrastructure budgets and facilities were never designed for. Energy consumption, cooling capacity, and inefficient data movement have become real operational constraints — often limiting progress long before compute capacity or GPU availability. These gaps are already impacting deployments today, driving up costs and reducing the return on new AI investments.

Winning Formula: Leaders treat power and efficiency as first-order design requirements — maximizing utilization and eliminating waste before it compounds.

93%

are actively working to reduce AI’s energy footprint

65%

of infrastructure sits idle while still consuming power

47%

cite energy and cooling as their top inefficiency

41%

report efficiency gains from recent investments

Reduce your costs and carbon footprint by investing in energy efficiency of your infrastructure.

Business decision maker
Consumer Services

Partnerships Are the Force Multiplier Behind AI Success

The most successful organizations aren’t trying to operationalize AI alone. They’re combining internal expertise with proven ecosystems — cloud providers, GSIs, platform partners, and specialists — to reduce risk, accelerate deployment, and build repeatable AI operating models. Partnership isn’t a dependency. It’s a structural advantage.

Report

Download 2026 State of AI Infrastructure Report

Get the complete findings, data visualizations, and recommended actions from all 600 respondents.

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