A tech leader standing in a conference room explaining AI scaling and governance strategies to seated employees. — As AI deployment scales, CIOs must redesign governance to bridge the “control gap.”

New IBM Study Reveals CIOs and CTOs Face Growing AI Control Gap as Enterprise Deployment Scales

A global IBM study reveals that two-thirds of tech executives are being held accountable for AI systems they do not fully control as enterprise deployment outpaces governance. While AI spending is projected to nearly double by 2027, only 11% of CIOs and CTOs feel completely prepared for the looming scale of autonomous AI agent deployment.

RMN Digital Enterprise Desk
New Delhi | June 12, 2026

Navigating the AI Control Gap: A New Challenge for Tech Leaders

As artificial intelligence shifts from the experimental phase to enterprise-wide deployment, a significant disconnect has emerged between executive accountability and operational oversight. According to a new study by the IBM Institute for Business Value, 66% of surveyed CIOs and CTOs report being held responsible for AI systems they do not fully control.

This “control gap” is driven by a rapid, often uncoordinated, adoption of technology across business units. The study, which surveyed 2,000 C-level technology executives across 33 countries, found that 70% of respondents believe teams within their organizations are deploying technology faster than IT can track.

It’s like flying a plane at 10,000 feet, being told to climb to 12,000, replace both engines mid-flight and ensure zero turbulence. No one would choose to pilot that plane – but that’s exactly what companies are doing today.

— Afonso Eça, Executive Board Member, Banco BPI

The Scaling Crisis: Speed vs. Governance

The pressure to scale is immense, with 80% of tech executives reporting AI transformation mandates driven directly by their CEOs. By 2027, these leaders anticipate a 38% increase in the number of AI agents deployed. However, the infrastructure to support this growth is lagging behind; 77% of organizations admit that AI adoption is already outpacing their current governance capabilities.

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The risks of this gap are not merely theoretical. Organizations relying on manual governance experienced an average of 54 AI agent incidents last year, where unintended or harmful occurrences required human intervention. Of these incidents, 17% were classified as high severity, leading to data exposure, security breaches, and cascading system failures.

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.

— Matt Lyteson, CIO, IBM

The Financial Stakes of AI Integration

The financial commitment to AI is accelerating, with spend projected to grow from 15% of IT budgets in 2025 to nearly 25% by 2027. Despite this massive 71% increase in investment, visibility remains a primary concern. The study found that 85% of tech leaders lack full visibility into real-time AI spend, and 84% have yet to fully operationalize AI financial management.

The Path Forward: Designing for Control

The research suggests that the most successful organizations are those that move away from manual oversight in favor of “built-in” control. Organizations that embed governance directly into their AI systems report:

25% fewer incidents compared to those using manual governance.
18% higher operating margins.
16x more AI agent deployments than their peers.

To bridge the gap, IBM suggests that leaders must prioritize modular architectures and workload portability to avoid being locked into specific dependencies. By designing for adaptability early on, organizations reported a 10% higher return on AI investment in 2025.