Dive Brief:
- Despite lengthy cloud adoption efforts, just 14% of enterprises have reached the highest level of cloud maturity, according to a survey published by NTT Data. The technology services company surveyed 2,300 senior decision-makers in 33 countries for its Thursday report.
- With most businesses still in the earliest stages of cloud maturity, where cloud is used for isolated workloads or infrastructure hosting, fewer than half of surveyed leaders said they were fully satisfied with cloud's role in innovation efforts, according to the survey.
- The disconnect between cloud readiness and AI deployment plans is leading most businesses to rethink their cloud spend. Three-quarters of companies expect to increase their cloud spending significantly in the next two years, NTT Data found.
Dive Insight:
Cloud is key to scaling AI adoption, as quality results from advanced models require the right infrastructure and data. But most enterprises have been unable to fully modernize legacy cloud estates, preventing rich datasets from delivering value.
In an effort to attract enterprise customers, hyperscalers have expanded their menu of AI offerings and pitched themselves as the natural providers of AI services.
The focus on enterprise spend is already showing up on their balance sheets. The market for cloud infrastructure services — led by AWS, Microsoft and Google — reached $419 billion last year, according to Synergy Research Group data. The analyst firm credits generative AI services as a major driver for growth.
“Cloud has moved well beyond infrastructure and is now the execution layer for AI,” Charlie Li, president and global head of cloud and security at NTT DATA, said in a release accompanying the report. “Organizations that fail to evolve their cloud foundations risk constraining the growth and value of their AI investments.”
But cloud immaturity is not the only obstacle to enterprise AI. Nearly half of cloud leaders surveyed by NTT Data listed a lack of AI skills as a key blocker to hindering their cloud strategies over the coming year. The skills gaps worsen another problem in cloud: stubborn legacy implementations.
“Many organizations manage complex application estates that are difficult to refactor, integrate or retire,” NTT Data said in its report. “Skills gaps in cloud-native development, automation and DevOps compound the challenge, slowing progress and increasing execution risk as AI places new demands on application architecture.”
