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Copilot adoption at Engie: from unused licences to power users

Downloads | AI case studies

Engie raised Copilot adoption by putting an AI coach inside Copilot and having staff practise weekly on use cases matched to their jobs. Rémi Hottois, Head of Global Expansion at Mendo, Engie’s partner on the work, shared the story at aiblLIVE London 2026.

Coached staff became power users much faster than colleagues left to progress naturally. Engie then agreed to fund licences for more people. Here is how it worked.

Engie and Mendo in numbers

  • 36% of employees actively use GenAI, and for most of them use is shallow.
  • 2 to 4 months of weekly practice inside Copilot came before each team’s review.
  • 5 to 10% is the agent adoption Hottois sees in big companies, even consulting firms.

All figures as stated on stage by Rémi Hottois. The 36% and 5 to 10% figures were cited without a named source.

Why was Copilot adoption low at Engie?

Engie is a very traditional company, and many people resisted change. It had rolled out the Microsoft ecosystem to its teams, but few used it in depth. Hottois says top-down training, built on use cases leaders think should work, misses many people because it does not fit their job or level.

How does an AI coach inside Copilot work?

It gives each user a personal learning path inside Copilot. Use cases are matched to their GenAI maturity, job and industry, and they practise regularly in the tool itself. Beginners go back to basics, including risks and critical thinking. A Mendo team adds onboarding and webinars.

Taking data out of their own usage, we can actually measure the gap, and that gap is actually relevant to the team.

Rémi Hottois, Head of Global Expansion, Mendo

How do you measure Copilot adoption properly?

Track which use cases people run, not how often they log in. Mendo uses a small language model it fine-tuned to sort activity in Copilot and ChatGPT into general use cases, within GDPR limits. Each team then sees what it uses against what it could use. Time saved per use case is estimated with teams.

What results did Engie see?

An A/B comparison showed coached staff became power users far faster than those progressing naturally, within about three months. Hottois did not give exact figures. Engie agreed to free up budget to equip more people, and is now using its usage data to decide which agents to build first.

Agents won’t respond at first to 100 percent of what your users will expect.

Rémi Hottois, Head of Global Expansion, Mendo

Key takeaways

  • Measure depth, not logins. Track the use cases each team runs.
  • Train inside the tool. Weekly practice beats one-off courses.
  • Use a control group. Compare coached and uncoached staff.
  • Build agents with feedback loops. Link users to the people who build them.

About the speaker

Mendo logo

Rémi Hottois is Head of Global Expansion at Mendo, a French scale-up that has supported GenAI adoption for five years and is now entering the UK. He spoke on the AI Infrastructure track at aiblLIVE London on 20 October 2026.

What’s in the full case study

If your GenAI licences are not turning into real use, this is a method to borrow. The full PDF goes deeper than this page, in the speaker’s own words.

  • The rollout, step by step, from weekly practice to team-by-team reviews.
  • How usage is measured with a small language model, within GDPR.
  • How Engie is moving to agents, and why agent adoption needs its own plan.
  • Five actions to take back to your own organisation.

For CIOs, CHROs, digital workplace and L&D leads running Copilot or GenAI rollouts. Five pages, about a seven-minute read.

Turn licences into real AI use

Copilot adoption at Engie: from unused licences to power users
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