{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T16:32:53Z","timestamp":1785169973115,"version":"3.55.0"},"reference-count":125,"publisher":"Emerald","issue":"11","license":[{"start":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T00:00:00Z","timestamp":1750377600000},"content-version":"vor","delay-in-days":214,"URL":"https:\/\/creativecommons.org\/licences\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,12,16]]},"abstract":"<jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This paper aims to provide empirical evidence on adopting artificial intelligence (AI), including generative AI, in knowledge management (KM) processes and its impact on organisational decision-making. Specifically, the study addresses three key research questions: RQ1: How is (generative) AI adopted within KM processes in organisations? RQ2: What factors influence the adoption of AI in these processes, either facilitating or inhibiting it? RQ3: How does AI adoption in KM processes affect organisational decision-making?<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design\/methodology\/approach<\/jats:title>\n                    <jats:p>An explorative investigation has been conducted through semi-structured interviews with KM and AI experts from a worldwide sample of 52 mostly private, large and for-profit organisations. Interviews have been analysed through a mixed thematic analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>The study provides an original framework in which the three investigated concepts are interconnected according to a dual relationship: linear and retroactive and 20 factors affecting AI adoption within KM processes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Practical implications<\/jats:title>\n                    <jats:p>The provided model guides managers in improving their organisational decision-making through AI adoption in KM processes. Moreover, according to the rational decision-making model, the authors propose a six-step systematic procedure for managers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Originality\/value<\/jats:title>\n                    <jats:p>To the best of the authors\u2019 knowledge, this is the first study that simultaneously addresses AI, KM and decision-making and provides an integrated framework showing the relationships between them, allowing organisations to better and practically understand how to ameliorate their decision-making through AI adoption in KM processes.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1108\/jkm-03-2024-0262","type":"journal-article","created":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T04:15:04Z","timestamp":1731989704000},"page":"320-347","source":"Crossref","is-referenced-by-count":67,"title":["AI-empowered KM processes for decision-making: empirical evidence from worldwide organisations"],"prefix":"10.1108","volume":"28","author":[{"given":"Luna","family":"Leoni","sequence":"first","affiliation":[{"name":"Tor Vergata University of Rome Department of Management and Law, , Rome,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ginetta","family":"Gueli","sequence":"additional","affiliation":[{"name":"InfoCert Department of International and Strategic Programs Governance, , Rome,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marco","family":"Ardolino","sequence":"additional","affiliation":[{"name":"University of Brescia Department of Mechanical and Industrial Engineering, , Brescia,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mateus","family":"Panizzon","sequence":"additional","affiliation":[{"name":"University of Caxias do Sul Department of Business and Management, , Caxias do Sul,","place":["Brazil"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shivam","family":"Gupta","sequence":"additional","affiliation":[{"name":"NEOMA Business School Department of Information Systems, Supply Chain Management and Decision Support, , Reims,","place":["France"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"140","published-online":{"date-parts":[[2024,11,18]]},"reference":[{"key":"2025120417065485200_ref001","article-title":"How AI will change the way we make decisions","volume":"26","author":"Agrawal","year":"2017","journal-title":"Harvard Business Review"},{"issue":"3","key":"2025120417065485200_ref002","first-page":"23","article-title":"What to expect from artificial intelligence","volume":"58","author":"Agrawal","year":"2017","journal-title":"MIT Sloan Manag. 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