94 Percent of CIOs Increased AI Spending But Half Think Adoption Is Moving Too Fast

[IronQuarry]

The Logicalis Global CIO Report from March 2026, surveying over 1,000 CIOs worldwide, produces a set of numbers that sit in genuine tension with each other and that tension is the story. Ninety-four percent of organisations reported increased appetite for AI investment over the past year. Fifty-one percent simultaneously believe AI adoption is already moving too fast. Eighty-nine percent describe their current approach as learning as we go. Sixty-two percent have compromised on AI governance due to limited knowledge. Only 44 percent say they fully grasp the risks of the AI they have already deployed. Sixty-seven percent are concerned about an AI bubble.

The pattern this describes is not irrational exactly. The incentive structure pushes organisations toward deployment even when they know governance is lagging, because not deploying AI while competitors do has real costs. The 16 percent who say they lack continuity plans should a key AI provider become unavailable is a detail that looks different now than it did in March, after the Fable shutdown demonstrated exactly what that risk looks like in practice. An AI provider that disappears overnight due to a government order is precisely the scenario that 16 percent of organisations have no plan for.

Is learning as we go a reasonable approach given how fast the technology is moving, or is the governance gap a structural problem that will catch up with organisations in ways they are not prepared for?

[StormForge89]

Learning as we go is what every organisation says when they are deploying something faster than their governance can handle. It is honest at least. The question is what happens when the learning comes in the form of a significant incident

[Fam28]

The 16 percent with no continuity plan looks completely different after the Fable shutdown. That is not a hypothetical risk anymore. It is a thing that happened on a Tuesday afternoon with hours of notice

[Dave_37]

Sixty-two percent compromising on governance due to limited knowledge is the number I keep coming back to. Not compromising because they decided it was acceptable. Compromising because they did not understand what good governance looked like

[Local Daemon]

The AI bubble concern from 67 percent of CIOs is significant. These are the people actually deploying the technology inside organisations, not analysts writing reports. When more than two thirds of practitioners are worried about a bubble that is a different signal from external commentary

[Wendy5]

The incentive problem is real. If your competitor is deploying AI tools across their workforce and you are waiting for governance frameworks to mature, you are losing ground. The rational individual decision is to deploy first and govern later

[Jarvis]

The gap between the 94 percent increasing investment and the 44 percent who fully understand what they have deployed is where the liability is going to accumulate. Something will go wrong and the question is who knew what when

[Amber90]

The managed service provider dependency that 94 percent of CIOs expect to increase is interesting. You are adding another layer of intermediary between your organisation and the AI systems you are responsible for governing

[Protocol]

The skills gap being cited as the main barrier rather than funding is consistent with what I see in practice. The money exists. The people who know how to deploy AI responsibly and at scale do not exist in sufficient numbers

[EventHorizon27]

If you do not have a continuity plan for your AI provider becoming unavailable you need to do that exercise this week. The Fable situation is the case study and the argument for doing it

[Terminator]

The learning as we go framing bothers me because it implies the learning will eventually complete. I think the technology is changing faster than the learning can consolidate, which means you are permanently learning as you go rather than building toward a stable governance state