{"id":833104,"date":"2025-12-15T14:56:39","date_gmt":"2025-12-15T13:56:39","guid":{"rendered":"https:\/\/www.devoteam.com\/success-story\/longchamp-copilot-deployment\/"},"modified":"2026-02-05T10:44:36","modified_gmt":"2026-02-05T09:44:36","slug":"longchamp-copilot-deployment","status":"publish","type":"success-story","link":"https:\/\/devoteam.info\/en-dk\/success-story\/longchamp-copilot-deployment\/","title":{"rendered":"Copilot Deployment at Longchamp: From 10% to 98.6% Adoption in 6 Months"},"content":{"rendered":"\n

No budget, no sponsor, 10% usage. That was the starting point for the Copilot<\/a> project at Longchamp<\/a>. Six months later: 98.6% satisfaction, 3.4 hours saved per week per user, and exploding internal demand.<\/p>\n\n\n\n

How did a luxury house transform a timid test into measurable success? The answer lies in one principle: applying its own codes to transform AI from a consumer product into a luxury product. Renaud Beaufils, Chief Data Officer at Longchamp, and Christelle Vertus, Customer Success Manager at Devoteam, reflect on adoption through practice, without fanfare or excessive promises. Just concrete training, a restricted community that created desire, and results that ultimately convinced management.<\/p>\n\n\n\n

Here’s the behind-the-scenes story of a Copilot deployment that proves that when it comes to AI, method matters more than technology.<\/p>\n\n\n\n

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The snapshot<\/h2>\n\n\n\n
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1<\/strong><\/p>\n\n\n\n

Longchamp initiated a low-budget pilot with minimal executive sponsorship to test the operational efficiency of generative AI within a luxury environment.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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2<\/strong><\/p>\n\n\n\n

The primary challenge lay in transforming a timid test with low adoption rates into a measurable success that could justify further investment without sophisticated tracking tools.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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3<\/strong><\/p>\n\n\n\n

The solution relied on a pragmatic strategy that prioritised hands-on practice and created internal desirability through exclusive, restricted user communities.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

A Pragmatic Launch Context<\/h2>\n\n\n\n

Unlike the spectacular announcements sometimes shared on LinkedIn, the Copilot project at Longchamp wasn’t born from immediate management conviction. Instead, the company seized a Microsoft funding opportunity to test the technology with minimal initial budget and no strong sponsorship at launch.<\/p>\n\n\n\n

The business context was clear: a fast-growing company with a recruitment deficit and overloaded teams. Objectives centred on ROI<\/a> and efficiency gains. As Renaud Beaufils explains: “In luxury, the main challenge remains operational efficiency rather than pure innovation.”<\/p>\n\n\n\n

The starting point presented challenges: 50 licenses available, 40 assigned, but a usage rate of around 10%. A classic scenario where the tool is distributed without the necessary support for adoption.<\/p>\n\n\n\n

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Renaud Beaufils and Christelle Vertus during the Devoteam Microsoft AI Experience<\/em> event<\/p>\n\n\n\n

An Action-Oriented Training Strategy<\/h2>\n\n\n\n

Faced with no dedicated budget and weak sponsorship, the team adopted a direct and pragmatic approach. Rather than multiplying theoretical awareness sessions, priority was given to immediate hands-on practice.<\/p>\n\n\n\n

“We didn’t try to convince people or explain the technology at length. We went straight to training,” explains Renaud Beaufils. The goal was to let users discover the tool themselves, develop their own use cases, and then support them with additional content.<\/p>\n\n\n\n

Prompting training formed the foundation of this approach, a choice that proved pivotal going forward. Christelle Vertus emphasises the importance of this practical approach:<\/p>\n\n\n\n

“Users need to test concretely and see how the solution responds to their specific needs.”<\/p>\n\n\n\n

The adoption plan wasn’t fixed but constantly evolved based on field feedback and emerging needs. Team workshops identified priority use cases and business issues to address, followed by POCs and feedback sessions.<\/p>\n\n\n\n

The Power of Exclusivity and Communities<\/h2>\n\n\n\n

A key success factor often underestimated: creating a sense of belonging. “Creating a relatively restricted group at the start generated a desirability effect among other employees,” observes Renaud Beaufils. This selective approach sparked interest and the desire to join the program.<\/p>\n\n\n\n

Community recruitment happened progressively and iteratively. Managers were consulted to identify profiles that were curious and inclined to challenge their habits. But the team also implemented an adjustment process based on actual usage data, evolving the pilot group composition to maintain high engagement levels.<\/p>\n\n\n\n

A community on Teams and SharePoint was then created to distribute content, share use cases, and capitalise on knowledge of each team’s business issues. These Champion or Ambassador communities can evolve over time, enriched by new teams expressing their desire to get involved.<\/p>\n\n\n\n

Features That Transform Daily Work<\/h2>\n\n\n\n

Copilot adoption varied by business profile. Retail teams, accustomed to managing large amounts of data with limited tools, showed high adoption rates. Internal training teams, project management, and human resources also identified high-value use cases.<\/p>\n\n\n\n

For project management, benefits are tangible, including the generation of meeting minutes, RFP preparation, and project plan development. “Automatic minutes compensate for the lack of communication that existed before, particularly when no one formally took notes,” explains Renaud Beaufils.<\/p>\n\n\n\n

Presentation creation also illustrates productivity gains. Using structured prompts that precisely define needs, target audience, and key messages, it’s possible to generate professional-quality presentations in a fraction of the time usually required.<\/p>\n\n\n\n

Translation represents another major use case for Longchamp. This feature, which translates complete presentations with approximately 95% accuracy, proves particularly relevant for a company that must train teams in its international factories. Real-time translation in Teams also addresses concrete multilingual collaboration needs.<\/p>\n\n\n\n

However, some profiles didn’t adopt the tool as anticipated. IT teams, particularly developers, showed more limited adoption, partly due to a mistrust of generated code quality and confidence in their own expertise.<\/p>\n\n\n\n

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We measured an average of 3.4 hours saved per week.<\/p>\n\n\n\n

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Renaud Beaufils
Longchamp<\/p>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

KPIs That Convinced Management<\/h2>\n\n\n\n

The major challenge was proving ROI without initially having sophisticated measurement tools. The team relied on three main KPIs: time saved, adoption rate, and user satisfaction.<\/p>\n\n\n\n

The decisive KPI for unlocking budgets was time saved, measured by surveying the equipped population. “With 173 users having the paid license, we measured an average of 3.4 hours saved per week,” indicates Renaud Beaufils.<\/p>\n\n\n\n

The adoption rate now reaches 98.6%, demonstrating real tool appropriation. Adoption rate tracking also identifies teams requiring additional support, while satisfaction by tool guides training efforts on new features.<\/p>\n\n\n\n

These quantitative results were complemented by qualitative benefits:<\/p>\n\n\n\n