I just ended a call with one of the nation’s biggest financial institutions, who asked me if I could create a series of experiences to “bring our teams together around AI using storytelling.”
Hmm. Interesting challenge. They explained that the firm offers dozens of trainings on tools, prompting, vibe coding, agent development and so much more. So everyone is working at their own pace, on their own projects and are lost figuring out:
· how to integrate their individual work into team workflows
· if their working on the right thing
· if they’ll get rewarded or fired for their learning pace or token use
· whether they’ll be recognized for their work, in the absence of a bigger
strategy.
The result? No one understands how to work together in AI.
Two forces are converging in organizations at the same time: employees have largely retuned to physical offices, and AI is being deployed across the enterprise. Leaders who treat these as separate initiatives are missing the real challenge in front of them.
After years of distributed work, teams are relearning in-person collaboration while simultaneously determining where AI fits into their daily responsibilities. The result is a workforce split between enthusiasm and skepticism — and a growing number of employees who feel expected to acquire new capabilities without a clear roadmap for how.
This is not a technology rollout. It is a culture shift in how people learn, collaborate, and define success.
Culture is built from what employees observe every day: who gets recognized, which behaviors are rewarded, and how leadership responds when someone takes a risk or falls short. Those moments become the narratives employees share with one another — and those narratives determine whether AI adoption accelerates or stalls.
Executives have a narrow window to shape that narrative before assumptions take hold.