The executives are not the villains of this story. They are the people with the authority to approve things they do not fully understand, inside a culture that treats approval as progress.
That is a dangerous arrangement for any technical project. AI makes it worse because the distance between an executive decision and the system's failure modes can be unusually wide. The people who approve the work may not see how it fails. The people who see how it fails may not have the authority to slow it down.
The result is not usually corruption or bad intent. It is a system that rewards confident progress reports and makes uncomfortable questions feel political.
The Visionary
The Visionary has seen the keynote. They have read the analyst report. They have talked with the vendor's executive counterpart. They believe, genuinely, that AI is transformational and that the organization needs to move faster.
The belief is not necessarily wrong. The trouble begins when it turns into a mandate without specifics.
"We need to be doing more with AI." More of what, exactly? Which users? Which workflow? What result would justify the expense? What risk is acceptable? What work should stop to make room for this work?
The mandate does not answer those questions. The team has to answer them on the fly, usually by interpreting "more" as "everything." That is how the Scope Creep Kraken gets fed. A useful experiment becomes a platform. A platform becomes a company-wide program. Nobody can say exactly when the change happened because every step sounded like a reasonable response to the previous one.
The Visionary sets direction. Someone else still needs to define the destination.
The Sponsor
The Sponsor attaches their name to an AI initiative.
That is valuable. Executive sponsorship gets work funded, removes organizational blockers, and gives a team permission to operate across boundaries. Many good projects would never begin without it.
The problem is that sponsorship creates a political stake in the initiative's success. The Sponsor cannot easily ask, "Is this actually working?" because the question can sound like an admission that they backed the wrong idea.
So the initiative continues. Not always because it works, but because the Sponsor's credibility is attached to it. The team learns to report progress instead of problems. Usage goes up, so the project is said to be gaining traction. The pilot is still running, so the project is said to be learning. A new budget is approved, so the project is said to be scaling.
Those statements may all be technically true. None of them answers whether the project should continue.
A sponsor needs a way to be visibly supportive of honest results, including a decision to stop. Without that permission, the team has a reason to protect the sponsor from bad news.
The Budget Approver
The Budget Approver signs off on the AI spend.
They approve the pilot budget because the pilot is cheap. They approve the rollout budget because the pilot worked. They approve the expanded budget because the rollout is "showing traction," a phrase that means whatever the team needs it to mean.
The Approver often lacks the technical depth to judge whether the spending is proportional to the value. The team often lacks the incentive to say that it may not be. The result is a chain of approvals in which each decision is justified by the previous one, even though the scope, usage, and risk have changed.
A cheap pilot can prove that a workflow is possible. It does not prove that the workflow will remain affordable at larger scale. A working rollout can prove that people use a tool. It does not prove that the usage creates enough value to justify expansion.
The Budget Approver needs more than a spend total. They need a plain account of what the system does, who uses it, what it costs, what failure looks like, and what evidence would justify the next tranche of money.
Give the project a stop button
All three executives are doing their jobs. The Visionary sets direction. The Sponsor champions initiatives. The Budget Approver funds promising work.
The system works when those people have the information needed to make good decisions. AI strains the system because it widens the gap between authority and understanding.
The counter is practical: for every AI initiative, name the executive who can stop it.
Not who approved it. Not who appears in the launch announcement. Who can stop it when the results are weak, the costs climb, or the risks become unacceptable?
Write down that person's authority and the conditions that trigger a review. If the answer is "nobody," the initiative has no oversight, regardless of how many sponsors it has.