How Doctolib made its commercial organisation self-sufficient on AI agents
An agent platform already deployed at scale, but usage concentrated among a few pioneers. Three months on the ground so that every member builds their own agents, then so that the coaching role moves in-house.
A deployed platform does not make a self-sufficient organisation
Doctolib had already deployed an AI agent platform at scale internally. But within SCOPS, the group's commercial and operations organisation, usage was still carried by a handful of pioneers, with very uneven skill levels across profiles and most people still spectators rather than participants. The challenge was not the tool, it was already there. It was making every member self-sufficient at building their own agents, then moving from individual use to deeper automation, team by team.
of pioneers carried all the usage
An agent platform already deployed at scale internally, but adoption concentrated among a few profiles.
people to make self-sufficient
Five teams with different jobs, and very uneven skill levels from one profile to the next.
rather than participants
Most people used the tool without ever building their own agents.
Doctolib, France and GermanyDoctolib
Doctolib is Europe's leading medical appointment booking platform, operating in France and Germany.
Tandem's engagement covered SCOPS (Sales & Customer Operations), the group's commercial and operations organisation: 26 people across 5 teams, Sales Enablement, Process, Orga & Planning, Automation & Efficiency and Analytics. Five different jobs, therefore five different relationships to the tool, which ruled out any one-size-fits-all training.
Prove value one case at a time, then hand it over
An iterative, pragmatic approach: prove value on one use case, measure, then move to the next, rather than a single mass rollout. And an exit prepared from day one, so that coaching does not depend on Tandem.
A dense month of scoping
37 interviews, 30 internal and 7 external benchmarks with market peers, to target the highest-value scope before training anyone.
A founding all-hands
Generative AI fundamentals, prompting, then a workshop where every member builds their first agent. The link to action is direct: 75 % of the agents attributable to the engagement were created within the following two months.
Team sessions every two weeks
Mapping use cases and debugging with each owner, team by team, to move from the personal agent to business automation.
Co-building agents wired into business tools
Billing anomaly detection with an alert in the team messaging tool, real-time bonus calculation through a dedicated MCP connector, to-do automation, quarterly performance review preparation. Each integration produced a reusable standard for permission inheritance and data partitioning.
From a handful of pioneers to 20 agent builders across 5 teams
In three months, SCOPS went from usage carried by a few pioneers to broad, self-sufficient adoption. 90 % of members now build their own agents, usage grew 35 % in messages and 53 % in conversations between April and June, and around fifty use cases were identified, about ten of them in production and four in pilot. Beyond the numbers, the skill did not concentrate in a few experts: the 53 agents were built by 20 distinct people across the 5 teams. The closing session was run by the internal team, the coaching role was already in-house by the time Tandem left.
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