Early Impacts of M365 Copilot
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
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| _version_ | 1866915244149833728 |
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| author | Dillon, Eleanor Wiske Jaffe, Sonia Peng, Sida Cambon, Alexia |
| author_facet | Dillon, Eleanor Wiske Jaffe, Sonia Peng, Sida Cambon, Alexia |
| contents | Advances in generative AI have rapidly expanded the potential of computers to perform or assist in a wide array of tasks traditionally performed by humans. We analyze a large, real-world randomized experiment of over 6,000 workers at 56 firms to present some of the earliest evidence on how these technologies are changing the way knowledge workers do their jobs. We find substantial time savings on common core tasks across a wide range of industries and occupations: workers who make use of this technology spent half an hour less reading email each week and completed documents 12% faster. Despite the newness of the technology, nearly 40% of workers who were given access to the tool used it regularly in their work throughout the 6-month study. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_11443 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Early Impacts of M365 Copilot Dillon, Eleanor Wiske Jaffe, Sonia Peng, Sida Cambon, Alexia General Economics Economics Machine Learning Advances in generative AI have rapidly expanded the potential of computers to perform or assist in a wide array of tasks traditionally performed by humans. We analyze a large, real-world randomized experiment of over 6,000 workers at 56 firms to present some of the earliest evidence on how these technologies are changing the way knowledge workers do their jobs. We find substantial time savings on common core tasks across a wide range of industries and occupations: workers who make use of this technology spent half an hour less reading email each week and completed documents 12% faster. Despite the newness of the technology, nearly 40% of workers who were given access to the tool used it regularly in their work throughout the 6-month study. |
| title | Early Impacts of M365 Copilot |
| topic | General Economics Economics Machine Learning |
| url | https://arxiv.org/abs/2504.11443 |