Most chief executives I meet cannot name it. They can produce activity: pilots run, licenses purchased, employees trained, a partnership announced. None of that is a result. Survey after survey finds that most corporate AI programs deliver disappointing measurable returns.
In fairness to CEOs, the cards are often stacked against them. A company is an information system, and the quality of information degrades at every level it passes through. Going up the chain, uncomfortable findings and early warning signs get discarded; what often arrives is a clean, but incomplete, summary. Going downwards, management directives are often diluted, re-interpreted, re-purposed, or quietly “pocket-vetoed”—nodded through in the meeting and left to die. The result? A company of 10,000 ends up knowing less than a company of 10.
Now, AI can expose and accelerate radical visibility in organizations at a depth and speed that far surpass any human capacity and any business intelligence system. Every company keeps two sets of records. One is official: quarterly reports, project updates, performance reviews, polished at each level until it is clean and coherent. The other is what actually happened: meeting transcripts, chat threads, edit trails, sales notes, code check-ins. Managers have always worked from the first, because the second was too numerous and scattered to read. No longer. Every company writes down the most critical issues, the hottest debates, and the truth about itself every day. Almost none of them read it. A CEO-level agentic system can wake up that “dormant data.”
What did my boss AI find in its first weeks? A priority project reported on track every week, with no code committed in five. A customer marked highly likely to renew, while the account manager had not called in two months. A draft contract nobody could have made profitable, as reading relevant sales notes, the signed terms, and product requirement documents together showed free customization promised in a room but never written down.
AI’s second contribution is to surface hidden good news that might have been under the radar. Chief among these is talent and identifying star performers.
This is what an AI-native chief executive is: not someone who just signs off on an AI budget, but someone who puts his own meetings, calendar, and blind spots under the machine’s scrutiny first. I regularly ask my agent what I got wrong in a meeting, whether my time went where I said my priorities were, and what people are afraid to tell me. Subordinates answer those questions politely. The machine can tell me the blunt truth.
So: no more cosmetics. We should use AI to address businesses’ hardest problems in the building: the ones on the CEO’s desk. Then, the words the CEO proudly proclaims on the next earnings call will have three parts: a business number that moved, the person who moved it, and the compute that did the work.
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