Organizations that consider themselves more mature in their use of AI are also much more likely to have someone formally responsible for it.
Devolutions’ 2026 AI Maturity Benchmark found that half of Early-stage organizations had no clear owner or relied on individual adoption, while 55% of Advanced organizations had a dedicated AI role or team.
Devolutions, an IT management software vendor, based the benchmark on 616 IT professionals worldwide. Respondents rated their own organization’s AI maturity on a 0-to-100 scale and were split into three groups: 267 Early-stage respondents, 255 AI Adopters and 94 Advanced respondents. The report cautions that the relationships it identifies are associations, not evidence that any one practice causes greater maturity.
The full ownership breakdown shows a progression that is harder to see from the endpoints alone. The share of organizations where IT leadership drove AI or a dedicated AI role or team was in place rose from 21% among Early-stage organizations to 53% among AI Adopters and 89% among Advanced organizations.
Support runs ahead of formal ownership
Leadership support appears earlier on the maturity curve than formal ownership. About 60% of Early-stage organizations reported at least some leadership support for AI, rising to about 95% among AI Adopters and 100% among Advanced organizations. Yet only 53% of the middle group had reached the point where IT leadership drove AI or a dedicated AI role or team was responsible.
The middle group also shows how ownership changes before becoming fully formalized. Informal IT ownership rose from 22% among Early-stage organizations to 34% among AI Adopters, then fell to 7% among Advanced organizations.
Meanwhile, the share with no clear owner or individual-led adoption dropped from 50% to 11% and then 2%. Devolutions describes informal IT ownership as a bridge between scattered experimentation and more formal responsibility.
Greater maturity did not coincide with a narrower AI toolset. Early-stage organizations used an average of 1.9 of the seven tools Devolutions measured, compared with 2.7 among AI Adopters and 3.8 among Advanced organizations. Nearly half of Advanced organizations, 47%, were also building or customizing AI tools internally, compared with 13% of Early-stage organizations.
Other research finds similar ownership pattern
The ownership association also appears in independent 2026 research, although the studies measure maturity differently. McKinsey’s “State of AI trust in 2026” survey, based on responses from approximately 500 organizations, found an average responsible-AI maturity score of 2.6 among organizations with explicit accountability, compared with 1.8 where no function was clearly accountable.
McKinsey’s measure focuses specifically on responsible AI across strategy, risk management, data and technology, governance and agentic AI controls, while Devolutions asks respondents to assess their organization’s broader AI maturity. The figures are therefore not directly comparable, but both studies show an association between clearer accountability and higher maturity on their respective measures.
Devolutions also found formal measurement becoming more common as maturity increased. Just 0.4% of Early-stage organizations said they tracked AI benefits through formal KPIs and reporting, compared with 9% of AI Adopters and 47% of Advanced organizations. Even at the highest maturity level, more than half had yet to formalize that measurement.
The benchmark therefore shows AI ownership varying alongside other organizational characteristics: leadership support is stronger, responsibility is more formal, AI use is broader and measurement is more structured at higher maturity levels. What the survey does not establish is which of those changes drives the others.