Only 14% of Firms Are Cloud‑Ready for AI, Yet 88% Warn Underfunding Threatens Projects

Context Cloud maturity refers to how well an organization uses cloud services across its operations, from basic adoption to advanced, integrated strategies. For AI to scale, firms need a cloud environment that can handle large data volumes, provide strong governance, and support production‑grade workloads. Without this foundation, AI models often suffer from poor data quality and unreliable performance.

Key Facts A recent NTT DATA survey found that just 14% of respondents are at the “cloud evolved” stage, the optimal level for AI success. Meanwhile, 88% of IT leaders said they worry that a lack of cloud investment will jeopardize their AI and modernization projects. Charlie Li, president and global head of cloud and security at NTT DATA, noted that cloud initiatives are underfunded, prompting CIOs to divert AI budgets and spend money on pilots that fail to deliver value.

What It Means The gap between cloud readiness and AI ambition creates a cycle where money is moved from cloud to AI, weakening the very infrastructure AI depends on. This can lead to wasted pilots, inaccurate models, and higher long‑term costs as firms later need to fix cloud shortcomings. Aligning cloud and AI budgets is essential to avoid repeating costly experimentation.

What to watch next Monitor whether enterprises increase cloud spending to match AI goals or continue to see pilot failures that prompt a reassessment of investment priorities.