REPORT

The State of AI Infrastructure 2026: Can Systems Withstand AI Scale?

When AI growth outpaces infrastructure

As AI moves into production, continuous and machine-driven AI workloads are pushing enterprise databases beyond what they were designed to handle. Based on new global research, this report reveals how close organizations are to hitting their infrastructure limits—and why AI scale is becoming a defining risk for resilience, performance, and cost in 2026.

Inside the report

AI scale is rapidly increasing

Always-on inference, autonomous agents, and real-time decisioning are increasing demand in ways traditional databases were never designed to absorb.

Infrastructure limits are closer than expected

Many organizations believe AI growth will push their systems past capacity sooner than planned—potentially within the next two years–with compute becoming an ever-increasingly scarce resource.

Scale is reshaping resilience risks

As AI becomes embedded in core operations, scale issues surface as outages, latency, and rising costs rather than gradual degradation.

Key findings.
Real implications.
One report.

Much enterprise infrastructure could collapse because of AI growth — and its survival won’t be shaped by tools, but by architecture built to last.
One-third expect AI-driven infrastructure failure in less than a year, and know they need more than routine maintenance to avoid that fate.
More than a third say databases are emerging as a primary bottleneck under sustained AI load, and will likely be the first layer to fail.
AI is becoming a material driver of outages, which comes with not only six-figure downtime costs but an inevitable erosion of customer trust and loyalty.
Leadership is underestimating the accelerating infrastructure risk, largely making reactive rather than proactive investments in AI.

See what AI scale really demands from infrastructure

Read the report to learn how AI is reshaping enterprise systems and why elastic, resilient infrastructure is now a business imperative.