Nancy University Hospital harnesses AI as a catalyst for talent attraction with Microsoft 365 Copilot
Nancy University Hospital (CHRU)· FranceMicrosoft 365 Copilot · Word · PowerPoint +1
Nancy University Hospital (CHRU) in France piloted Microsoft 365 Copilot with 50 finance, operations and administrative users to automate email drafting, document summarization and presentation creation, without accessing medical data. The pilot succeeded so well that the hospital expanded it to 300 users, with staff reporting one to three hours saved per week and reduced cognitive load, backed by a formal AI roadmap funded in part by the regional health agency.
Overview
Nancy University Hospital (CHRU) in France piloted Microsoft 365 Copilot with 50 finance, operations and administrative users to automate email drafting, document summarization and presentation creation, without accessing medical data. The pilot succeeded so well that the hospital expanded it to 300 users, with staff reporting one to three hours saved per week and reduced cognitive load, backed by a formal AI roadmap funded in part by the regional health agency.
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Inspect the highlighted sourceThe challenge
Nancy University Hospital faced growing complexity in administrative and financial management, with understaffed teams and increasing volumes of data, meetings, and reporting, and wanted to improve efficiency, free up time, and reduce cognitive load for staff.
The solution
CHRU Nancy piloted Microsoft 365 Copilot with an initial cohort of 50 users across executives, business/operations managers, IT engineers, and administrative teams, without accessing medical data, using personalized enablement and role-specific examples; the pilot was expanded to 300 users within the hospital's existing, secure Microsoft 365 environment.
Reported business value
With Microsoft 365 Copilot, teams save one to three hours per week, reduce cognitive load from repetitive tasks, and improve overall organization, freeing staff to focus on higher-value work such as managerial oversight and deeper file analysis.
Sources
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