Wharton@Work lands on the number that keeps coming up in board meetings: fewer than one in ten companies capture meaningful AI value at scale, a figure BCG and MIT independently arrive at. Usage isn't the holdup. In the Wharton/GBK study the piece draws on, 82 percent of executives now use generative AI at least weekly, and roughly three in four say their early deployments are already paying off. The money is moving. The payoff isn't keeping pace.
Our founder Jeremy Korst, co-author of the Wharton/GBK study the piece draws on, names the work plainly: getting "from AI aspiration to AI actual." His sharper line is the one we keep coming back to: "even if we have the best idea and the best technology, if we can't get the right people to adopt and act on it, the rest is irrelevant." The technology is the easy part. Adoption is where the value is won or lost.
The data exposes a split the org chart hides. Almost half of executives report significant ROI from their early AI investments; just 27 percent of the middle managers actually running those programs say the same. On speed it's no better: executives are roughly twice as likely as their managers to believe they're outpacing competitors. Executives and the messy middle are not describing the same company.
That gap is the story. The Wharton piece's argument, and ours, is that AI pays off when the work itself is redesigned and the people doing it are carried along, not when another tool gets bought. It lands exactly where the Flywheel does: the value sits in the Core, the people and organizational design, not the technology layer wrapped around them.
So what: If your executives are confident and your managers aren't, believe the managers. That gap between the corner office and the messy middle is the most honest read you have on whether the investment will ever pay off.