About six in ten organizations say their AI strategy is transforming the business. IDC’s 2026 MaturityScape Benchmark AI Survey measured whether their capabilities match that claim, and for roughly five in six they do not yet.
How did IDC measure AI maturity?
The May 2026 survey covers 1,900 organizations across 20 markets and asks two kinds of questions. The first is a self-assessment of the organization’s approach to AI, which IDC used to sort respondents into two groups.
- Survivors describe either no enterprise AI strategy, with projects run independently by teams, or a strategy limited to select functions or business areas. Their descriptions correspond to the first three maturity stages.
- Thrivers describe an enterprise AI strategy that either implements AI in every part of the business to transform the operating model, or advances AI use cases to redefine products and services. Their descriptions correspond to the top two stages.
The second is a set of detailed capability questions across four dimensions: strategy, governance, people, and technology. IDC scores those answers to place each organization in one of five stages. Comparing the two shows how closely what leaders say matches what their organizations can do.
What are the five stages of AI maturity?
The stages run from Ad hoc to Optimized, and the top stage is what IDC calls the AI-fueled organization.
- Ad hoc: Disconnected pilots, with no enterprise strategy or central AI leader.
- Opportunistic: An informal oversight group shapes a strategy around a few high-return use cases.
- Repeatable: A center of excellence with a dedicated AI leader builds an enterprise roadmap, and governance becomes formal.
- Managed: AI reshapes the operating model, and new AI-powered products and revenue streams appear.
- Optimized: Autonomous agents become more prevalent, and governance is enforced in real time.
Where do most organizations sit on the AI maturity model?
Half of organizations sit at Opportunistic, and 61.3% sit in the two least mature stages. Only 12.8% have reached the two most mature stages. Of those, 3.1% sit at Optimized and the other 9.7% at Managed.
The average hides a split. The worldwide mean score edged up from 2.39 in 2025 to 2.43, while the share at Optimized rose from 0.4% to 3.1%, nearly eightfold. IDC reads that as a leading cohort beginning to separate from the pack, with the broad middle advancing slowly.
What happens when self-description meets the scorecard?
Of the 1,149 organizations that described themselves as Thrivers, about 60% of the sample, only 15.1% scored at Managed or Optimized. By IDC’s assessment, that leaves roughly five in six still operating like Survivors: the other 84.9% landed at Ad hoc, Opportunistic, or Repeatable.
The label still carries some signal. Thrivers are about 1.5 times as likely as Survivors to reach the top two stages, which IDC credits to having a coordinated enterprise strategy. Both shares are modest, though, and confidence and capability track only loosely: 10.1% of Survivors score into the top two stages anyway.
Why does AI ambition outrun AI capability?
In IDC’s analysis, strategy is the easiest dimension to declare and the hardest to deliver at scale. The shortfall shows up in the dimensions that are harder to overstate. IDC points to governance that hasn’t been formalized into enforceable controls, data and platform foundations that cannot support production at scale, and a workforce that hasn’t been brought along through reskilling and change management. That is how an organization can carry the narrative of an AI-fueled enterprise while its execution still resembles the Opportunistic stage.
The dimension scores point the same way. Technology is the least mature dimension, with 66.5% of organizations in its two least mature stages. People maturity clusters at Opportunistic (51.2%). Governance is furthest along and is where Thrivers pull ahead most: 20.1% of Thrivers reach the top two stages on governance, versus 12.2% of Survivors. Even so, 57.2% of all organizations still sit in its two least mature stages.
IDC’s Andrea Siviero, Vice President of AI-Fueled Business Strategies, describes the pattern as strategy outpacing delivery, with talent the main barrier.
How do you move up the AI maturity model?
Start by testing your own organization against the four dimensions:
- Who owns AI at the board level, and how often do they report to it?
- How many of your governance controls are enforceable today?
- Could your data and platforms carry your next use case into production?
- What share of your workforce has been reskilled for AI work?
Here’s the full report: IDC MaturityScape Benchmark: AI-Fueled Organization Worldwide, 2026.
The distance between the stage you describe and the stage you score is specific to your organization, and so are the moves that close it. IDC Quanta pairs your own documents and data with IDC’s research to help you define practical steps from where you are to Managed or Optimized.
