Two-Thirds of Tech Leaders Lack Full Control Over AI Systems

Enterprise AI deployment is creating a widening accountability gap, with two-thirds of technology leaders now responsible for systems they cannot fully control, according to new research from IBM's Institute for Business Value.

The global study of 2,000 CIOs and CTOs reveals that 70% report business teams deploying technology faster than IT can track. Meanwhile, organizations expect to increase AI agent deployments by 38% by 2027, yet only 11% of technology executives believe they are fully prepared for that scale.

The research, first reported by IBM, surveyed senior technology decision-makers across 33 countries and 19 industries from January through April 2026. It found that 77% of organizations say AI adoption already outpaces their governance capabilities, even as 80% face CEO mandates to accelerate AI transformation.

Incidents rise with manual governance

Surveyed organizations experienced an average of 54 AI agent incidents in the past year requiring human intervention. Of the high-severity incidents that took more than four hours to contain, 37% resulted in data exposure or security breaches, 33% caused cascading system failures, and 17% triggered compliance issues.

Organizations relying on manual governance see incident risk increase as AI scales. By contrast, those that embed control directly into AI systems experience 25% fewer incidents, according to the analysis.

Security and compliance concerns rank as the top barrier to scaling AI agents for 59% of technology leaders surveyed.

Financial visibility lags behind spending growth

AI spending is projected to climb from under 15% of IT budgets in 2025 to nearly 25% by 2027—a 71% increase in two years. Yet 84% of technology executives have not fully operationalized AI financial management, and 85% lack real-time visibility into AI spending.

Organizations that build control into their AI systems from the start deploy 16 times more AI agents than those using manual governance, deliver 18% higher operating margins, and spend four times less of their AI budget, the study found.

Companies with strong financial discipline deploy 2.4 times more AI agents without higher budgets and are three times more likely to report full preparedness for AI scale.

Design for adaptability

Organizations that designed for adaptability early—keeping workloads portable and models replaceable rather than locked into dependencies—reported 10% higher return on AI investment in 2025.

"It is no longer just about deploying AI faster," said Matt Lyteson, CIO of IBM. "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."

Why it matters

As AI systems operate continuously and autonomously, the traditional governance models built for slower, more predictable technology deployments are proving inadequate. Technology leaders face mounting pressure to accelerate AI adoption while simultaneously losing visibility and control—a combination that increases operational risk and makes financial management nearly impossible. Organizations that redesign their approach to embed control and financial discipline from the beginning are achieving dramatically better outcomes, suggesting the gap between leaders and laggards will widen rapidly.

The full study and recommendations are available from the IBM Institute for Business Value.