{"id":1059921,"date":"2024-07-31T06:00:09","date_gmt":"2024-07-31T13:00:09","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=1059921"},"modified":"2024-08-05T17:06:35","modified_gmt":"2024-08-06T00:06:35","slug":"generative-ai-in-real-world-workplaces","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/generative-ai-in-real-world-workplaces\/","title":{"rendered":"Generative AI in Real-World Workplaces"},"content":{"rendered":"<p>This report presents the most recent findings of Microsoft\u2019s research initiative on AI and Productivity, which seeks to measure and understand the productivity gains associated with LLM-powered productivity tools like Microsoft Copilot. The report synthesizes research results from over a dozen recent studies conducted by researchers at Microsoft, with a focus on studies of generative AI in actual workplace environments. One of these is, to our knowledge, the largest, randomized controlled trial of the introduction of generative AI into organizations. Overall, the research suggests that generative AI is already aiding workers in becoming more productive in their day-to-day jobs in significant ways. However, the influence of generative AI is subject to variation by role, function, and organization and is contingent upon adoption and utilization. The report explores these variations and underscores the potential for AI to have even greater impact as individuals and organizations recalibrate their work practices to harness AI in the places where it provides the most value.<\/p>\n<p>Slides summarizing the main findings of the report are available <a href=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/07\/Generative-AI-in-Real-World-Workplaces-Deck.pdf\">Generative-AI-in-Real-World-Workplaces-Deck.pdf<\/a><\/p>\n<p>This report is a follow up to the first productivity report released in Dec 2023: <a href=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/early-llm-based-tools-for-enterprise-information-workers-likely-provide-meaningful-boosts-to-productivity\/\">Early LLM-based Tools for Enterprise Information Workers Likely Provide Meaningful Boosts to Productivity<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>This report presents the most recent findings of Microsoft\u2019s research initiative on AI and Productivity, which seeks to measure and understand the productivity gains associated with LLM-powered productivity tools like Microsoft Copilot. The report synthesizes research results from over a dozen recent studies conducted by researchers at Microsoft, with a focus on studies of generative [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13556,13548,13554,13555,13559],"msr-publication-type":[193718],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-1059921","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-research-area-economics","msr-research-area-human-computer-interaction","msr-research-area-search-information-retrieval","msr-research-area-social-sciences","msr-locale-en_us"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2024-7-25","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"MSR-TR-2024-29","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"Microsoft","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/07\/Generative-AI-in-Real-World-Workplaces.pdf","label_id":"243109","label":0}],"msr_related_uploader":[{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/07\/Generative-AI-in-Real-World-Workplaces.pdf","label_id":"243112","label":0}],"msr_attachments":[{"id":1065561,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/08\/Generative-AI-in-Real-World-Workplaces-Deck.pdf"},{"id":1065555,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2024\/08\/2nd-AI-and-Productivity-Report-External-deck.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"Sonia Jaffe","user_id":37664,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Sonia Jaffe"},{"type":"user_nicename","value":"Neha Shah","user_id":40180,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Neha Shah"},{"type":"user_nicename","value":"Jenna Butler","user_id":39979,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Jenna Butler"},{"type":"text","value":"Alex Farach","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Alexia Cambon","user_id":43305,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Alexia Cambon"},{"type":"user_nicename","value":"Brent Hecht","user_id":38997,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Brent Hecht"},{"type":"user_nicename","value":"Michael Schwarz","user_id":37803,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Michael Schwarz"},{"type":"user_nicename","value":"Jaime Teevan","user_id":33975,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Jaime Teevan"}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[643845,1001961],"msr_project":[717493],"publication":[],"video":[],"download":[],"msr_publication_type":"techreport","related_content":{"projects":[{"ID":717493,"post_title":"The New Future of Work","post_name":"the-new-future-of-work","post_type":"msr-project","post_date":"2021-01-25 07:40:51","post_modified":"2025-01-27 11:49:54","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/the-new-future-of-work\/","post_excerpt":"This cross-company initiative is dedicated to creating solutions for a future of work that is meaningful, productive, and equitable. 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