"Don’t Be Fred": What Microsoft, Mercedes and Moderna say about AI leadership
Senior leaders are the biggest lever for AI adoption. Four voices from Tier-1 companies explain why leading by example beats strategy.
There is one line that surfaces again and again in the leadership pool raydaa curates: "Don’t be Fred." Brice Challamel coined it, and he doesn’t mean a specific person, he means a posture. Fred is the manager who delegates AI strategy instead of sitting at the tool himself. Fred is the executive who talks transformation without ever being seen prompting. Fred is everywhere, and Fred is the bottleneck of AI adoption.
Lead by example: senior leaders must embody the change
Brice Challamel, for years Head of AI Products & Platforms at Moderna and now Head of AI Adoption at OpenAI, has a very clear position on what has to shift first in AI adoption: leadership behavior. If senior leaders don’t use AI themselves, the transformation never lands in the workforce. The logic is sober: people read what leadership does, not what it says.
Senior leaders need to embody the change, not delegate it. They need to sit at the tool themselves.
Trust culture: the company must have your back
Amy Coleman, Chief People Officer at Microsoft with 220,000 employees worldwide, describes a quiet but central aspect of AI adoption: the right to become a beginner again. AI tools change workflows so fundamentally that even experienced people temporarily fall back into a learning posture. If leadership doesn’t actively protect that transition phase, uncertainty turns into avoidance, and AI tools stay on the shelf.
The company needs to have our back while we learn how to become beginners again.
Measuring AI success: output, not headcount
Marco Argenti, CIO at Goldman Sachs, draws a clear line between AI hype and AI productivity: success is not measured in headcount saved but in additional capacity for projects that weren’t feasible before. That reframing is one of the most important adoption levers: it removes the fear that AI replaces jobs and replaces it with a growth perspective.
Suddenly I have 120 percent capacity. 130 percent. That’s how we measure AI success: impact on delivery timelines and output.
What this means for AI programs today
The three voices outline a pattern: AI adoption doesn’t scale through tool rollouts or mandatory training. It scales when senior leaders are visibly using AI themselves, when staff are allowed to inhabit a learning posture, and when AI success is framed as growth rather than cost cutting. That’s harder than a tool rollout, and at the same time the only path on which AI investment actually turns into value. The same pattern shows up in Stefan Lehmann (Mercedes-Benz), at BASF, Otto, and many more voices in the raydaa pool.
These three voices are part of the 698 leadership voices we curate weekly at raydaa for AI program leads and strategy teams in the DACH region. If you want to know who is making the most important statements in your industry and for your role right now, start with raydaa for free and get your first briefing on Tuesday.