Turn distributed AI ownership into coordinated action
As AI reshapes enterprise, technology leaders have been pushed into new territory: balancing rapid adoption against lagging governance, split budgets and accountability for outcomes they can't fully control.
To help navigate this complexity, Thoughtworks surveyed 3,200 CIOs globally. The results reveal how CIOs are navigating the tension of distributed AI, and what it means for C-suite leadership, enterprise governance and the redesign of work.
CIO responsibilities now extend well beyond core IT into workforce design and decisions about how AI is used across the business. As our survey reveals, fragmented ownership and governance that struggles to keep pace with adoption can leave accountability disconnected from authority.
The survey shows where the pressure points are. Drawing on experience from Thoughtworks’ CIO, CTO and Chief Data and AI Officer, the report also explores practical ways to clarify responsibilities, redesign work and manage the economics of AI.
As Al decision-making spreads across the enterprise, C-suite leaders need clearer ways to align governance, accountability, workforce design and investment.
Drawing on the findings and Thoughtworks’ experience, the report identifies practical priorities for cutting through the complexity, including:
Keep AI decisions close to the teams best placed to make them, while making accountability, guardrails and escalation routes explicit.
Make clear how work is divided between people and AI, where human judgment remains essential and who is responsible for decisions and outcomes.
Clarify where CIO, CTO, CAIO and CFO responsibilities meet, so shared decisions don’t fall between functions.
Make AI consumption visible across the enterprise and connect spending to the value it creates. Budget for agentic workflows, not just individual tokens.
There is no single dominant model. Thoughtworks’ survey shows authority over AI is already 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.
Accountability doesn’t always align to responsibility. 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.
Eighty-nine percent of CIOs surveyed agree they are now more responsible for redesigning workforce workflows and labor models than for managing core IT infrastructure. That puts technology leaders increasingly close to decisions about how work itself is designed, not just the systems that support it.
The report explores what this means for the CIO and the wider leadership team.
Not necessarily. Thoughtworks’ view is that many decisions can stay close to the teams best placed to make them, provided responsibilities, guardrails and routes for escalation are clear.
The report sets out practical ways to make distributed governance more coherent without recreating a central bottleneck.
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’ perspective 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.
