July 22, 2026
Two decades into the cloud era, most companies still haven’t gotten it right. A new report from NTT DATA finds that just 14% of organizations have reached the highest level of cloud maturity, even as AI piles fresh pressure onto the systems they never finished modernizing.
The report, titled “Cloud-led innovation in the era of AI: The new rules for driving value with cloud,” was released on March 26, 2026 and is based on a global survey of more than 2,300 senior decision-makers across 33 countries. The headline finding is a paradox: 99% of organizations say AI is increasing their demand for cloud investment, but 88% say current investment levels are actually putting their AI, cloud-native, and modernization initiatives at risk.
Fewer than half of organizations said they’re satisfied with either the impact of their cloud investment or their modernization progress, a gap the report frames as ambition running ahead of reality.
“AI is accelerating faster than enterprise cloud maturity”
Charlie Li, President and Global Head of Cloud and Security at NTT DATA, put it directly: “Cloud has moved well beyond infrastructure and is now the execution layer for AI. Organizations that fail to evolve their cloud foundations risk constraining the growth and value of their AI investments. Our clients who are succeeding are treating cloud as a value creator, not a technology initiative.”
The organizations the report calls “cloud evolved,” meaning the most advanced in adoption, impact, and business performance, are significantly better positioned actually to capitalize on AI than everyone else. That gap is the core tension running through the findings: AI needs a modern cloud foundation to deliver value, but most companies haven’t built one.
Six rules NTT DATA says will separate the winners
The report lays out six imperatives for turning cloud into an actual value engine rather than a cost center.
The first is that cloud and AI strategy can’t be planned separately anymore. Chief AI Officers are 22% more likely than CIOs and CTOs to say AI is increasing cloud investment needs, and AI skills are now cited as the single biggest gap in cloud teams.
The second is that architecture choices are no longer neutral. Companies are increasingly blending public, private, hybrid, and sovereign cloud models, and sovereign cloud adoption specifically is projected to grow 50% over the next two years.
The third goes straight at the modernization problem: half of respondents say legacy applications and data platforms are actively holding back innovation, and modernization is now the top cloud priority for the next two years.
Fourth, a platform-led approach is becoming close to mandatory. More than half of organizations cite cloud cost management as a real challenge, and the report expects a threefold increase in the use of fully managed cloud platforms as a result.
Fifth, the metrics companies use to judge cloud success need to change. Only 47% of self-identified cloud leaders used AI in their last cloud migration project, compared with 35% of everyone else, showing that even the more advanced organizations are still catching up on this front.
Sixth, security remains the top cloud investment priority. Still, confidence is split sharply down the middle: 68% of cloud leaders are highly confident in their security posture, compared with just 36% of everyone else. Leaders are also far more likely to have clearly defined roles, responsibilities, and regular audits in place.
What it adds up to
The report’s underlying message is that the cloud has quietly changed jobs. It’s no longer just infrastructure sitting underneath the applications a business runs. It’s now the layer that determines whether an AI strategy can actually work at scale. Companies that haven’t modernized their legacy applications and data platforms aren’t just carrying old technical debt; they’re capping how much value their AI investments can realistically deliver.
Where We Fit In
The gap NTT DATA describes, between AI ambition and cloud readiness, is exactly where legacy applications and outdated data platforms tend to get exposed. Primotech cloud modernization services are built around closing that gap without forcing a company into a risky, all-at-once rebuild, working through assessment, architecture redesign, and phased migration so legacy systems get modernized in stages rather than replaced overnight.
For companies still weighing public, private, hybrid, or sovereign cloud options, Primotech cloud migration and consulting team can help map out which mix actually fits the workloads in question, then handle the underlying infrastructure so internal teams aren’t stretched managing a transition on top of daily operations.
If legacy applications or data platforms are the reason your AI initiatives aren’t delivering the value you expected, Primotech can help figure out where modernization should start.
