New global research from Thoughtworks, a global technology consultancy that integrates design, engineering and AI to drive digital innovation, shows that almost nine in 10 (88%) Chief Information Officers (CIOs) say AI adoption within their organization is happening faster than governance structures can adapt.
The study, based on a survey of 3,200 CIOs across 10 countries, points to a widening gap between authority and accountability as AI adoption accelerates across enterprises without formal oversight.
Layered into this, the CIO remit has extended as technology leaders are drawn into questions about how AI workflows are designed. 89% of CIOs agree they are now more responsible for redesigning workforce workflows and labor models than for managing core IT infrastructure. In the UK, this figure increases even further, to 92%.
At the same time, more than a third of CIOs (35%) also say they feel personally accountable for workforce disruption caused by AI adoption, despite not being able to fully influence the outcome.
Complicating matters, the survey also found that AI budget ownership is distributed across the business, with no single model dominant, pointing towards more fragmentation. Some 22% report that budgets are managed centrally by IT, 22% that responsibility is shared between IT and the business, 20% that budgets are controlled independently by business units, 19% that they are managed at executive or board level and 17% that the model is still evolving.
“AI governance is also a workforce design issue,” said Rachel Laycock, Chief Technology Officer at Thoughtworks. “As AI changes how work gets done, organizations need to rethink roles, workflows and decision rights so people know where human judgment is still essential and where AI can take on more of the work.”
The data also exposes a growing concern that AI is moving rapidly past the structures built to manage it, with nine in 10 (90%) CIOs admitting they’re held responsible for AI failures that happen through independently integrated tools across their organization. CIOs also report feeling personally accountable for outcomes they cannot fully influence, including security incidents involving AI systems (37%), data privacy breaches (35%) and brand or reputational damage from AI misuse (34%). In the UK, CIOs were also concerned about regulatory or compliance failures (35%) and being able to show a clear return on AI investment (34%).
“Authority over AI is distributed, but accountability hasn’t always moved with it.” said Mike Sutcliff, CEO of Thoughtworks. “The answer isn’t to pull every decision back into central IT, or to put one executive in charge and assume the problem is solved. Organizations need clearer decision rights, and people need the skills and information to make good decisions as AI becomes part of how the business runs.”
The lack of a single operating model extends to enterprise AI leadership. Seventy percent of organizations surveyed have already hired a Chief AI Officer, with a further 26% looking to do so, but there is no clear consensus on how the role should work alongside the CIO. 35% say the role operates independently with equal or greater enterprise influence, whilst 29% describe the CIO/CAIO relationship as a source of organizational friction or unclear boundaries. The data suggests that many are not yet equipped to manage AI consistently, and without teething problems, across their enterprise.
In the UK, the data indicates we’re lagging behind in the global race. Just 63% of organizations have hired a CAIO, whilst of those that already have, 34% describe the relationship with the CIO as a source of friction.
“At Thoughtworks, our experience has been that AI transformation is a team sport, from defining enterprise AI strategy and architecture to embedding AI into internal platforms and day-to-day operations.” said Xia Jie Jessie, CIO of Thoughtworks. “The question isn’t who owns AI, but how leadership collaborates to create business value responsibly and at scale.”
The full report, Thoughtworks Global CIO Survey: Who governs enterprise AI?, explores how organizations are approaching enterprise AI governance, leadership, workforce capability and the changing role of the CIO.
