The disappointing return on AI in most companies is not a failure of the technology. It is a failure of leadership that released a budget and never said where to dig. The companies now seeing a return are not the ones that spent the most. They are the ones whose leaders decided, before a single token was spent, which problem the AI was there to solve.
You approved the budget. You may have approved a large one. And now, sitting in front of a board that wants to see the return, you have a dashboard of usage and very little else to point to. If that is the quiet position you are in, this is for you, because the reason is not the one you have been told.
The gold rush nobody learned to mine
There is a picture I keep returning to: the gold rush. Everyone wanted in. So everyone bought a shovel. What almost no one did was learn to be a miner. A shovel does not find gold. You do not dig a hole in your back garden and strike a vein. You study the ground, you find where the gold actually runs, you buy the right piece of land, and then the shovel matters. Dig anywhere else and all you have is a hole and a sore back.
That is precisely what happened across the corporate world. Leadership bought the shovels. The budget went up, the tokens were purchased, the memo went out: everyone use AI, we are subsidising the tools, start digging. What was missing was the only thing that mattered. No one was told where to dig. No one was shown how to use the tool. No one was given the problem worth solving. An unlimited budget of tokens pointed at nothing in particular is not a strategy. It is a slush fund with a fashionable name.
You measured the tool. You never measured the leadership.
This is where the conversation about measurement turns on its head. Everyone wants to talk about putting the right measures around AI use. The harder question is the one no one asks: what were the measures on the leadership? Because a budget was spent, a great deal of money was spent, and no target was set for the people who spent it. The tool was measured. The leader was not.
Consider where the accountability actually sits. The finance chief is there to protect the company’s money. The chief executive is there to protect the company overall. The technology chief is meant to hold the strategy and the plan. The information chief is meant to guard how the organisation’s time and resources are used. When a year of spending produces a dashboard and no return, that is not the tool underperforming. That is four seats at the top that set no goal, protected no outcome, and held no one, including themselves, to a result.
The generation that never had to earn a return
There is a deeper reason this keeps happening, and it is uncomfortable. A whole generation of senior leaders built their careers in an era of nearly free money. For decades, capital cost almost nothing. You could finance a project on borrowed money at close to zero and never feel the weight of it. In that world, inefficiency hides easily, and you can spend your way past a problem rather than solve it. AI removed that cover. It asks a leader to know exactly where the value is and to go and get it, and a leader who has never had to earn a return in that way is suddenly exposed. This is the same failure I keep naming: set low goals and automate the obvious and you have bought maintenance, not transformation.
The leaders getting a return did the unglamorous work first
The leaders who are getting the return did something unglamorous first. They looked honestly at their own operation, found where it was actually broken, and pointed the AI there. And here is the part most miss entirely: every AI project is a culture project before it is a technology one. The tool does not transform a company. The decision about where to aim it does, and that decision is leadership work that cannot be delegated. The most common failure I see is a proud leader who handed the project to a likeable person and stepped back to admire it from a distance. That is not delegation. It is abdication.
This is the moment to move, not retreat
None of this means the money is lost or the moment has passed. AI budgets are being cut across the market right now, and most leaders are reading that as proof the technology failed. It is the opposite. It is proof it was deployed without direction, and it is the clearest signal yet that the leaders who move now, with a plan and a target, will pull away from the ones still digging holes at random. The uncomfortable truth is that the partners you have relied on to guide this were often the ones selling you shovels by the hour.
So when the board asks why the AI spending has not produced a return, the honest answer is not that the technology disappointed. The honest answer is harder, and it is the beginning of getting it right. You did not lead your AI project. You just bought more shovels.
Frequently asked questions
Why do most AI projects fail to deliver a return?
Most AI projects fail because leadership released a budget without deciding which specific problem the AI was meant to solve. The technology performs; the direction was missing. Companies that see a return identify where the value actually is before spending, rather than funding broad, unfocused use.
Is cutting the AI budget the right response to poor results?
Cutting the AI budget treats a leadership failure as a technology failure. Poor results usually mean the tool was deployed without a target, not that AI cannot deliver. The leaders who move now, with a clear problem and a measurable goal, tend to pull ahead of those who retreat.
Who is responsible when an AI investment produces no measurable value?
Accountability sits with leadership, not the tool. When spending produces a usage dashboard and no return, it reflects a leadership team that set no goal, protected no outcome, and measured the tool instead of measuring its own decisions.
What separates companies that get value from AI from those that do not?
The companies that get value did the unglamorous work first: an honest look at where their operation is genuinely broken, then pointing AI at that problem. It is a culture and leadership decision before it is a technology one, and it cannot be delegated.
Thomas Anglero is a Strategic AI Advisor, keynote speaker and author of Intro to Artificial Intelligence. He has delivered over 450 keynotes across 30 countries for organisations including IBM, the WHO, the World Government Summit and the European Commission. He founded the IBM Watson AI Lab for Cancer at the Oslo Cancer Cluster and closed over $500 million in enterprise transformation deals as CTO and Chief Innovation Officer at Cognizant.
If you are leading your organisation through this, I work with a limited number of senior leaders each quarter.