AI is moving from helping executives prepare for decisions to influencing the decisions themselves. Recent research found that 62% of executives use AI to make decisions. Its influence is growing faster than the processes for deciding when its advice deserves trust.
A CEO can question a finance director’s assumptions or ask legal counsel where an opinion came from. AI can be questioned too, but its fluent answers often hide the quality of the information beneath them. Advice based on incomplete or outdated data may sound as convincing as advice grounded in the business as it stands today.
That fluency can shift authority quietly. 70% of leaders say they second-guess themselves when their judgement conflicts with AI. When an answer feels certain, executives may be less inclined to challenge it, precisely when challenge matters most. Disagreement around a boardroom table can expose trade-offs. If AI’s recommendation is treated as a settled answer, that discussion may never happen.
AI as an adviser
Executives must constantly judge when to act. Move too soon and they may miss crucial information; wait too long and the opportunity may pass. AI appears to ease that tension as 88% of executives say it helps them make decisions faster.
But a faster answer does not necessarily mean the business has reached a sound decision faster. AI can analyse information in moments, yet it cannot make yesterday’s data current or reconcile two systems that disagree about the same customer or transaction. A recommendation can be sound for the information supplied and still be wrong for the moment in which it is used.
The question is therefore not simply how quickly AI responds, but whether the evidence behind its response is ready to support action. Otherwise, speed can bring confidence before it brings clarity.
Speed vs accuracy
If AI is to accelerate decisions without accelerating uncertainty, confidence must begin with the information on which its recommendations are built. 91% of executives say access to real-time insights would make them more confident. But more data alone will not help. What matters is whether the information relevant to a decision is trustworthy, properly contextualised and reflective of what is happening across the business.
That is an executive concern, not merely a data team concern. Leaders need to know where the information informing a recommendation came from, whether systems agree on what it means and whether AI can see changes as they happen. They should also be able to ask what evidence is missing and why a recommendation has changed. Real-time data streaming cannot guarantee the right recommendation, but it can give AI a more current picture of the organisation.
Confidence also depends on how AI enters the decision. Organising evidence, suggesting options and recommending a course of action each demand different levels of scrutiny. So do the decisions themselves. A reversible operational adjustment should not follow the same process as one affecting jobs, regulatory obligations or long-term strategy. For consequential choices, the board should agree in advance who owns the final judgement and what would trigger a pause or a fresh review.
AI’s place in the boardroom is becoming permanent. Faster analysis is valuable when executives can understand the evidence beneath a recommendation, trust that it reflects the business now and apply scrutiny proportionate to the stakes. Confidence should come from information worthy of the decision being made.
- The writer is Solutions Engineer Director, Confluent, an IBM company