This year’s Super Bowl made one thing clear. Artificial intelligence has fully entered the mainstream conversation. The sheer volume of AI commercials was impossible to miss, and people began commenting on it early in the game. Somehow the huge story of the half-time show seemed to be eclipsed by the sheer number of AI commercials that dominated the game.
That moment mirrors what is happening inside many organizations right now. Awareness is high, investment is real, and attention is widespread. Behavior, however, remains largely unchanged. Gallup data shows overall AI use at work has barely moved, rising from 10% to 12%, with nearly half of U.S. workers saying they never use AI at all. Adoption is also sharply role-dependent. 69% of leaders report using AI, compared to 55% of managers and just 40% of individual contributors, meaning the people setting strategy are operating in a very different reality than the people doing the work.
AI shows up in strategy decks, leadership updates, layoff announcements, and pilot programs. Roadmaps are announced and leaders are appointed to oversee transformation. From a distance, it looks like adoption is accelerating. In reality, Gallup data shows the total number of people using AI at work is essentially flat, with usage increasing mainly among the same group of employees. Adoption is getting deeper in a small group of people, it is not becoming more widespread. (That’s the USA story. It is different in China). Inside the organization in corporate America, many people continue working the same way they always have.
This gap helps explain why digital transformation continues to disappoint. Most digital transformations fail to achieve their intended outcomes, and the majority of AI pilots never scale beyond experimentation. The problem usually sits with how responsibility is distributed.
When AI is owned by a role rather than embedded into how work gets done, distance forms. People observe the effort instead of participating in it and adoption feels optional. Gallup’s research shows the biggest reason for resistance to AI is not actually fear as I would have thought, but a lack of clarity about how AI is useful in someone’s day-to-day work.
Culture answers the question leaders are always asking: how do we get people to actually take accountability for this AI plan of ours?
The Super Bowl ads showed how visibility can arrive without meaning. Repetition creates recognition, but it does not deepen trust or change perspective. Inside organizations, communication alone works the same way. Explaining the vision is not enough if nothing in the environment reinforces new behavior.
In organizations where AI adoption successfully takes hold, leaders treat it as part of operating discipline rather than a side initiative. Expectations are clear. Planning conversations change. Leaders use the tools themselves and make their learning visible. Accountability extends beyond a transformation team and into everyday decisions across the business.
The bottom line is people know that AI is important. But they need clarity about how it affects their work. They need new experiences to change their beliefs. Technology does not transform organizations on its own. If AI remains something to talk about, you will fall behind as your competitor races ahead of you. If it becomes something the organization practices together, it starts to shift beliefs, which activates change and ultimately, gets results.
Elsewhere In Culture
What’s happening at The Washington Post is the talk of the media town. Ashley Parker’s reporting shows how quickly an institution can lose its center when decisions are reduced to spreadsheets and dashboards. Bezos has justified his decisions because he’s basing it all on data. Data can describe behavior, but it cannot define purpose. When leaders optimize only for what is easiest to measure, they begin eroding what is hardest to replace. Institutional memory, collaboration, judgment, and trust fade quietly. The organization may still function, but the culture that made it indispensable starts to disappear.
In my conversation with John Frehse, we kept coming back to the danger of letting metrics become the moral authority. Clicks reward speed and reaction. Algorithms reward volume and outrage. Journalism requires patience, standards, and investment in work whose value compounds over time. When leadership frames every decision as obedience to data, it avoids the harder responsibility of stewardship.
Having said that, is there an opportunity here for these journalists to lean into their craft by going independent? Traditional media has been neutered by revenue goals and political pressure. This could be the best thing to happen to these reporters since grad school. Let’s see if they lean into it.
CEOs are changing all at once, and that’s not a coincidence. When leadership shifts hit companies like Kroger, Workday, The Washington Post, Toyota, PayPal, Disney, Target, and Coca-Cola in what feels like the same breath, it tells us something structural is happening. Boards are operating with a different clock. The margin for learning on the job has narrowed, and the expectation that a CEO can steady the organization while the business model itself is being rewritten has become nonnegotiable. AI gets blamed, politics get dragged in, but the deeper truth is simpler. The system leaders are operating in has become less forgiving, faster moving, and more exposed.
For employees, this wave of turnover lands as uncertainty layered on top of uncertainty. Every new CEO promises focus and clarity, yet frequent leadership change often delivers the opposite. Strategy resets. Priorities shift. Trust pauses while people wait to see which version of the future survives. The organizations that will endure have cultures strong enough to absorb leadership change without losing direction. When they can’t, it means they have been relying too heavily on a single person at the top. In that sense, the CEO turnover is not just the problem, it is a diagnostic.