With the acceleration of generative AI, companies are moving from curiosity to real implementation. But who’s driving that transformation? And what does it mean for how teams are structured and how talent is evaluated?
We brought together leaders from Qonto, Pennylane, and Mindmetrics for a round table on exactly this topic:
Together, they shared how their teams are building AI-powered cultures, from launching internal agents to redesigning onboarding and hiring processes. Here are the key takeaways.
In most cases, AI adoption starts in tech or data teams, where there’s comfort with experimentation. But true transformation happens when AI is made accessible to non-technical teams.
At Pennylane, engineers initially explored AI use cases. But the real shift came when they gave business users access to tools like Dust, enabling them to build and deploy their own AI agents. This democratization helped embed AI in daily workflows.
At Qonto, AI enablement wasn’t imposed top-down. Instead, the company launched an internal audit asking employees about their pain points, specifically the tasks they disliked or wanted to automate.
This helped Qonto develop practical AI use cases with high adoption across teams. Today, over 80% of employees use AI agents weekly.
“We believe that for AI to be valuable, it has to come from people’s real needs.”
— Samy Aumar, Qonto
As AI adoption matures, it’s not just enhancing existing roles, it’s creating new ones.
From AI coaches and internal tool builders to emerging roles like “AI agent onboarding specialists,” companies are beginning to rethink how to support widespread AI usage across the business.
“One role I see emerging in the next few years is an AI agent onboarding specialist.”
— Pierre-Marie Servel, Mindmetrics
None of the speakers said AI literacy is a hard requirement in hiring, yet. But curiosity about the topic increasingly signals adaptability, openness, and a growth mindset.
At Qonto, a new question about AI use has been added to early-stage interviews. It helps assess whether a candidate is proactively exploring tools that could improve their work, regardless of technical background.
“We’re not filtering out people who don’t use AI, but we are trying to understand if they’re curious about it.”
— Samy Aumar, Qonto
By automating tasks like meeting notes, interview summaries, or simple data queries, AI has reduced the volume of basic requests landing on tech teams. This frees up time for engineers to focus on complex, strategic problems that better serve the business.
“We saw the impact immediately, our tech teams could focus on projects that had more value for the business and for them.”
— Remi Gourmel, Pennylane
The clearest message from this round table: AI won’t replace your team, but it will reshape how they work. The companies that benefit most are those that empower employees, embrace experimentation, and focus on real, team-led use cases.
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