mlsanityData to 14 Oct 2026

AI in the Enterprise: How People Use M365 Copilot Chat

arXiv 2605.23958 ↗First posted 11 May 2026cs.CY cs.AI econ.GNcited by 2

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Abstract (arXiv)

M365 Copilot is used every week by millions of people across more than a million companies around the world as part of their workflows. Uniquely positioned in the AI landscape given its near-exclusive use for work purposes, M365 Copilot can offer a clear picture of how people use AI for work and where that usage may expand next. This paper characterizes that usage through direct classification of user interactions with M365 Copilot Chat. Based on an anonymized and privacy-preserving analysis of a sample of approximately 5.5 million sessions, we combine a learned classification of user intent with a classification of O*NET work activities done with M365 Copilot Chat. We find that M365 Copilot is emerging as an everyday assistant for knowledge work: writing dominates, but users also rely on it for information retrieval, analysis, decision making and strategizing, and evaluating and diagnosing programs and systems, among others. Information seeking tasks remain common, but time trends suggest a relative shift away from ``chat as search'' and toward content and communication-related work. Comparisons across occupational groupings and to work done in the labor market further show that usage is broad but uneven, where the relative share of work done with M365 Copilot Chat cuts across jobs in some cases and is occupation-specific in others. Areas of relative underrepresentation in the labor market suggest the next frontier for enterprise AI adoption.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 7 of its 26 references that are in the map. First posted on arXiv 11 May 2026.

Builds on

7 of 26 references.

References · 7

  1. 2024WildChat: 1M ChatGPT Interaction Logs in the Wildcited by 629
  2. 2023The Impact of AI on Developer Productivity: Evidence from GitHub Copilotcited by 274
  3. 2025Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversationscited by 96
  4. 2024TnT-LLM: Text Mining at Scale with Large Language Modelscited by 26
  5. 2025Anthropic Economic Index report: Uneven geographic and enterprise AI adoptioncited by 26
  6. 2025Measuring AI Diffusion: A Population-Normalized Metric for Tracking Global AI Usagecited by 5
  7. 2025Early Impacts of M365 Copilotcited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.