New global research from Thoughtworks, a global technology consultancy that integrates design, engineering and AI to drive digital innovation, finds that 89% of Chief Information Officers (CIOs) agree they are now more responsible for redesigning workforce workflows and labor models than for managing core IT infrastructure.
The study, based on a survey of 3,200 CIOs across 10 countries, shows how far the CIO remit now extends beyond traditional technology management. As AI becomes embedded across the enterprise, technology leaders are being drawn more deeply into questions about how work is designed, where decisions sit and how responsibility is shared across the business.
That broader responsibility comes as organizations are still working through how enterprise AI should be governed. Almost nine in 10 CIOs (88%) report that AI adoption within their organization is happening faster than governance structures can adapt. 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.
“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. Training matters, but it’s only one part of building an organization that can use AI effectively at scale.”
Complicating matters, the survey also found that influence over AI decisions is distributed across the business. Globally, 23% identify the CEO as having the greatest influence, followed by central IT or technology leadership (21%), the executive leadership team (11%) and dedicated AI roles (10%).
AI budget ownership is similarly distributed, with no single model dominant. 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 has to connect data ownership, system ownership and business outcomes,” said Shayan Mohanty, Chief Data and AI Officer at Thoughtworks. “As adoption grows, total spend can rise even while tokens get cheaper. We need to understand what that spend produces and make deliberate choices about which models we use and where inference runs.”
That distribution of budgets and decision-making can also create accountability tensions. Nine in 10 CIOs (90%) believe central IT would still ultimately be held responsible for security breaches or compliance failures caused by AI tools purchased independently by business units.
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%).
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: 36% say the CAIO acts as an extension of the CIO’s centralized strategy, while 35% say the role operates independently with equal or greater enterprise influence. Some 29% describe the CIO/CAIO relationship as a source of organizational friction or unclear boundaries.
“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.”
Taken together, the findings point to a CIO role that now extends well beyond technology infrastructure. Workforce design, distributed AI decision-making and enterprise governance now intersect, while organizations are taking different approaches to how leadership responsibility should be divided.
“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 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 full report, Thoughtworks Global CIO Survey 2026: Who governs enterprise AI?, explores how organizations are approaching enterprise AI governance, leadership, workforce capability and the changing role of the CIO.
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About Thoughtworks
Thoughtworks is a global technology consultancy that integrates design, engineering and AI to drive digital innovation. For over 30 years, Thoughtworks has helped organisations solve complex business problems with technology as the differentiator.
Methodology
The research featured in this report was conducted by Censuswide, in partnership with Thoughtworks, among a sample of 3,200 CIOs across the UK, USA, Canada, Australia, Germany, Brazil, India, Saudi Arabia, UAE and Singapore.
The data was collected between July 1 and July 10 2026. Censuswide is a member of the Market Research Society (MRS) and the British Polling Council (BPC) and a signatory of the Global Data Quality Pledge. They adhere to the MRS Code of Conduct and ESOMAR principles.
Questions & Answers
Q: Who conducted the research on how CIOs govern enterprise AI?
A: The research was conducted by Censuswide on behalf of Thoughtworks, among 3,200 CIOs across 10 countries: the UK, USA, Canada, Australia, Germany, Brazil, India, Saudi Arabia, UAE and Singapore. The data was collected between July 1 and July 10 2026. Censuswide is a member of the Market Research Society (MRS) and the British Polling Council (BPC) and a signatory of the Global Data Quality Pledge. They adhere to the MRS Code of Conduct and ESOMAR principles.
Q: Are CIOs’ responsibilities changing?
A: Yes. Thoughtworks’ research suggests that the CIO remit extends beyond the original core duties. The study indicates that 89% of CIOs say they are now more responsible for redesigning workforce workflows and labor models than for managing core IT infrastructure. The Thoughtworks survey also found that 70% of organizations have already hired a Chief AI Officer, however there is no clear consensus on how the role should interact with the CIO function. The full report explores how AI has reshaped enterprise roles and where CIOs can tap into the value of their new core remit.
Q: What do CIOs feel most responsible for when it comes to AI systems?
A: Accountability doesn’t always align with responsibility. According to research commissioned by Thoughtworks, 37% of CIOs felt personally accountable for security incidents from AI, 35% felt accountable for data privacy breaches from AI, and 34% felt accountable for brand or reputational damage from AI misuse. Nine in 10 CIOs surveyed believe central IT would still be held accountable for security or compliance failures caused by AI tools purchased independently by business units. The report examines how clearer decision rights and accountability can reduce that gap.
Q: Who is making decisions about enterprise AI?
A: Thoughtworks’ survey indicates there is no single dominant model for AI leadership or budget ownership emerging across organizations. Most models being used are distributed, where responsibility for AI decisions is divided across central IT, business units, executive leadership and dedicated AI roles. The challenge is making responsibilities clear without pulling every decision back into central IT. The full report explores how those roles can work together more effectively.
Q: Does stronger AI governance mean centralizing AI decisions?
A: Based on the survey, Thoughtworks’ perspective is that AI decisions can stay close to the teams best placed to make them. The success of this is dependent on responsibilities, guardrails and routes for escalation being made clear. The full Thoughtworks report sets out practical ways to make distributed governance cohesive, safe and manageable, whilst reducing any central bottlenecks.
Q: What does the survey tell us about how leaders should respond to the economics of AI?
A: AI costs are shaped by more than the price of individual tokens. Model choice, agentic workflows and the scale of AI use all affect what organizations ultimately spend. Thoughtworks’ view is that leaders need both visibility into that consumption and a way to connect it to the value being created. The report explores why AI economics is becoming part of the governance challenge.
Q: What has the survey identified as what leaders could do differently as AI decision-making becomes more distributed?
A: As Al decision-making is becoming more widespread across the enterprise, C-suite leaders need clearer ways to align governance, accountability, workforce design and investment. The Thoughtworks report identifies ways to support improved AI management across organizations, including outlining clear AI guardrails across business units, redesigning workflows and labor models to define the new processes, embedding cross-functional leadership and better managing AI economics. The full report outlines these methodologies in further detail.