The numbers are striking: 60% of CIOs globally plan to invest in agentic AI over the next 12 months. But the Logicalis 2026 Global CIO Report, which surveyed more than 1,000 technology leaders across organisations with 250 to 5,000 employees, paints a more complicated picture underneath that headline figure.

Ambition is not the problem. Readiness is.

The Investment Rush Is Real

The appetite for AI among enterprise technology leaders has never been higher. The Logicalis report found that 94% of CIOs reported an increased appetite for AI over the past year, and more than half (53%) believe generative and agentic AI will fundamentally disrupt their existing business models within two years.

Agentic AI, systems that can plan, act, and adapt autonomously across business workflows, is moving out of pilot programmes and into production. CIOs are watching competitors automate whole process chains, and they are under pressure to keep pace.

The Governance Gap Is Just as Real

For all the investment intent, the infrastructure to support that investment is lagging badly:

• 66% of CIOs say employee training around AI risk management and responsible AI is inadequate
• 66% are not fully confident their organisation’s AI governance model can keep pace with deployment speed
• 62% report having already compromised on governance due to limited knowledge
• 44% say they fully grasp the risks of AI adoption, meaning 56% admit they do not

That last figure deserves a pause. More than half of the senior technology executives planning to deploy AI agents say they do not fully understand the risks they are taking on.

This is not a minor footnote. Agentic AI systems do not just answer questions. They take actions. They call APIs, update records, send communications, and make decisions across business systems. The governance question is not theoretical; it is operational.

Security and Governance Are the Top Concern

When asked about their leading concern regarding enterprise AI, 48% of CIOs cited lack of security and governance as the primary worry. Not cost. Not technical complexity. Not integration challenges. The thing keeping CIOs up at night is whether they can actually control what their AI systems are doing.

That reflects a significant shift from 12 months ago, when most enterprise AI conversations centred on capability. The conversation has moved to control: what AI should do, what it is allowed to do, and how you know when something goes wrong.

Data Governance as the New Control Plane

The Logicalis report frames data governance as the central mechanism for managing agentic AI. As AI moves from responding to requests to taking autonomous actions, the question of what data an agent can access, what it can modify, and what audit trails exist becomes critical.

An AI agent with access to CRM data, billing systems, and customer communications can create significant value. Without governance guardrails, it can also create significant liability. The distinction between those two outcomes is mostly a function of how well the organisation thought through the infrastructure before deployment.

What This Means for Business

For business leaders outside IT, this research tells a clear story: the window for getting ahead with AI agents is closing fast. Sixty per cent of your peers are already moving. But moving fast without the right foundations is how you end up with an AI problem instead of an AI solution.

A few practical implications:

Skills before agents. Two-thirds of CIOs say their teams are not adequately trained on AI risk. Before deploying agents across business workflows, build the understanding that lets people work alongside them safely. EDNA Learn’s AI and data courses are designed exactly for this: giving teams the foundational literacy to operate in an AI-augmented environment. Explore EDNA Learn.

Governance is not overhead. The 62% who say they have already compromised on governance due to limited knowledge are creating compounding technical and compliance debt. What is expensive to build now is far more expensive to retrofit after an incident.

Understand the risks before the rollout. If you are in the 56% who do not fully understand the risks of AI adoption, that is the starting point, not the model selection or the vendor negotiation. A fractional AI advisor can help business leaders map risk before it becomes a problem. Learn about Omni Advisory.

The organisations that will extract lasting value from agentic AI are not necessarily the fastest movers. They are the ones who build governance, training, and operational infrastructure alongside the technology rather than after it breaks.

The gap between ambition and readiness is real. But for the organisations willing to close it properly, it is also an advantage.