The AI confidence gap: What senior leaders actually think
There's the AI confidence companies perform in public. And there's the AI confidence they actually feel.
There’s a version of AI leadership that lives on LinkedIn. Bold transformation announcements. Keynotes about being “AI-first.” Press releases heralding the future.
At one of our recent Senior Leader Community events, we surveyed Chief Digital Officers, Chief Technology Officers, and Chief AI Officers. Decision-makers from organisations that collectively employ hundreds of thousands of people. What emerged was a picture of genuine ambition sitting alongside genuine doubt, and some of the most honest thinking on AI we’ve collected.
The number that tops the conversation
When we asked leaders to rate their confidence in the ROI of their current AI investments on a scale of 1 to 5, the average came in at 3.5.
Not 5. Not even 4.
More than one in five scored it a 1 or 2, effectively saying they have no confidence the money being spent is producing results, yet. The gap between public positioning and private conviction is one of the most interesting findings in the full report. AI is simultaneously the most talked-about priority in every boardroom, and the investment whose payoff most leaders genuinely can’t see clearly yet.
Hiring AI talent isn’t just hard. It’s structurally hard.
Seven in ten respondents rated hiring AI talent a 7 or above out of 10. The average senior AI hire now takes 90 to 120+ days to close, and that’s before a candidate even has competing offers on the table.
The reason isn’t compensation, and it isn’t competition from hyperscalers. It’s simpler and more stubborn than that: there just aren’t enough experienced people in the market. The roles organisations say they need most didn’t exist three years ago. And the report reveals something close to a paradox in where the money is actually going to solve this. Which is where it gets uncomfortable for a lot of leadership teams.
Pilots are everywhere.
Scale is rare.
Nearly every organisation we spoke to has a successful AI pilot running somewhere. Almost none has cracked what comes after it.
When we asked what was materially harder than expected, the top answer wasn’t the technology or the models. It was change management, getting people, not systems, to work differently.
And here’s the finding that should give technology leaders pause: the report identifies a specific internal group as the primary source of resistance to AI transformation. It isn’t frontline workers worried about their jobs. It isn’t middle management protecting their turf. We’ll let the report tell you who it actually is.
What 2027 looks like
Despite the friction, these leaders aren’t pessimistic about where this goes. More than a third believe AI will transform their entire operating model. Not just one function. Team sizes are expected to shift dramatically over the next two years, and the CIO/CTO role itself is being quietly redefined.
There’s also a trend the majority of respondents believe the market is dangerously underestimating, one that has nothing to do with chatbots, and everything to do with what happens when software stops needing a front end at all.
The honest picture
Real investment. Real ambition. Genuine uncertainty. And a talent market that cannot yet supply what organisations need to close the gap between pilots and scale.
The full AI Leadership Pulse Report breaks down exactly where the resistance is coming from, what’s actually eating budgets versus what leaders wish was, the team structure most are quietly moving toward, and the leadership behaviour that separates the organisations pulling ahead from the ones stuck in pilot purgatory.
