AI moves from experimentation to enterprise-wide deployment, two-thirds of surveyed CIOs and CTOs report being held accountable for AI systems they do not fully control, while governance struggles to keep pace at scale, according to a report from IBM Institute for Business Value.
The is is based on a global study of 2,000 C-level technology executives (tech CxOs) finds that the lack of visibility is widespread.
The IBM Institute for Business Value, in cooperation with Oxford Economics, surveyed 2,000 senior executives responsible for their organization’s IT, technology, or AI-related decision-making across 33 geographies and 19 industries from January to April 2026.
Among respondents, 31% are based in the Asia-Pacific region.
The majority of surveyed executives (70%) say teams across the business are deploying technology faster than IT can track.
At the same time, technology leaders face growing pressure to scale AI faster, even as many lack the structures to support it. By 2027, surveyed tech CxOs anticipate a 38% increase in the number of AI agents deployed.
While 80% of respondents report CEO-driven AI transformation mandates, only 11% believe they are fully ready for the scale of AI agent deployment expected in the next year.
Governance is also falling behind, with 77% of organizations surveyed reporting AI adoption is already outpacing current governance capabilities.
“For CIOs and CTOs, the challenge now is scaling AI systems that operate continuously and autonomously, often within governance models and architectures designed for a far slower, more predictable environment,” said Matt Lyteson, CIO of IBM.
“It is no longer just about deploying AI faster. It’s redesigning how organizations control, govern and invest in it and embedding control and visibility from the start, so they can scale with confidence,” said Lyteson.
Analysis shows that in organizations relying on manual governance, incident risk increases as AI adoption scales, whereas those that embed control directly into their AI systems experience 25% fewer incidents.
Most (59%) of tech CxOs surveyed cite security and compliance concerns as top barriers to scaling AI agents.
Surveyed organizations experienced an average of 54 AI agent incidents last year, in which an unintended and/or harmful occurrence required human correction.
According to respondents, 17% of those AI agent incidents reported were high severity, requiring more than four hours to contain — 37% resulted in data exposure or security breaches, 33% caused cascading system failures, and 17% triggered compliance issues.
AI spend is projected to grow from just under 15% of IT budgets in 2025 to nearly 25% by 2027 – a 71% increase in two years, raising the stakes for CIOs and CTOs.
Yet, 84% of tech CxOs have not fully operationalized AI financial management, and 85% still lack full visibility into real-time AI spend.
Analysis finds that organizations that build control into their AI systems deploy 16x more AI agents than those relying on manual governance, deliver 18% higher operating margins, and spend 4x less of their AI budget.
Analysis also shows that organizations with strong financial discipline: deploy 2.4x more AI agents with no higher AI/IT budget, and are 3x more likely to say they are fully prepared for AI scale.
Surveyed organizations that designed for adaptability early – keeping workloads portable and models replaceable rather than locked into hard dependencies – reported a 10% higher return on AI investment in 2025.
