Most surveyed technology leaders are accountable for systems they don’t fully control; Only 11% of respondents say they’re completely prepared for the scale of AI agent deployment; Organizations that design control into their AI systems achieve significantly stronger performance outcomes
ARMONK, N.Y.–A new IBM Institute for Business Value study reveals that as 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.
The global study* of 2,000 C-level technology executives (tech CxOs) finds that the lack of visibility is widespread. The majority of surveyed executives (70%) say teams across the business are deploying technology faster than IT can track.
C-level technology executives study
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, 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.”
As AI scales, operational and security risks are growing
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; 17% triggered compliance issues.
Organizations that redesign AI control and investment see stronger outcomes
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
- spend 4x less of their AI budget
Analysis shows organizations with strong financial discipline:
- deploy 2.4x more AI agents with no higher AI/IT budget
- 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. The full study, including recommendations for technology leaders on redesigning structures that govern speed, control and investment, can be found at: https://www.ibm.com/thought-leadership/institute-business-value/en-us/c-suite-study/cxo
The study also features executive perspectives on how technology leaders are adapting to the complexities of scaling AI across the enterprise. See quote addendum below.
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. The survey was designed to gather insights on how organizations are managing the financial, operational, and governance challenges associated with scaling AI. Additional analysis was conducted to identify organizations that have built the structural capabilities to scale AI effectively by segmenting organizations based on preparedness and efficiency and assessing governance maturity.
The IBM Institute for Business Value, IBM’s thought leadership think tank, combines global research and performance data with expertise from industry thinkers and leading academics to deliver insights that make business leaders smarter. For more world-class thought leadership, visit: www.ibm.com/ibv. To receive more insights, subscribe to the IdeaWatch newsletter: https://ibm.co/ibv-ideawatch.
IBM is a leading provider of global hybrid cloud and AI, and consulting expertise. We help clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. Thousands of government and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM’s hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently and securely. IBM’s breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and consulting deliver open and flexible options to our clients. All of this is backed by IBM’s long-standing commitment to trust, transparency, responsibility, inclusivity, and service.
Related Posts
