{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T17:38:46Z","timestamp":1792172326864,"version":"4.4.0"},"reference-count":142,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T00:00:00Z","timestamp":1784678400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Sociol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>The rapid integration of artificial intelligence (AI) into the music industries is fundamentally reshaping occupational roles, skill requirements, and career pathways, posing critical challenges for workforce development. This transformation compels a shift from conventional, craftbased music-making toward digitally enabled, interdisciplinary practices.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Employing a phenomenological qualitative research design, this study conducted in-depth, semistructured interviews with 20 stakeholders across four key groups-government officials, higher education faculty, enterprise managers, and frontline musicians- within the Beijing music industry. Data were analyzed using a six-step thematic analysis process facilitated by NVivo 14.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The findings reveal that AI is systematically permeating music creation, production, distribution, and copyright management, driving a shift toward more digital, collaborative, and data-informed roles. However, significant cognitive gaps and divergent adaptive capacities among stakeholder groups have created structural imbalances within the talent development ecosystem.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>To address these challenges, this paper proposes an empirically grounded, four-pillar workforce development framework comprising institutional support, educational reform, enterprise engagement, and community development, emphasizing systemic coordination to build a resilient digital music talent ecosystem. This study advances theoretical understanding of labor market transformation in creative industries and provides practical pathways for regions seeking to foster a sustainable and inclusive music workforce in the age of AI.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fsoc.2026.1852712","type":"journal-article","created":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T04:46:15Z","timestamp":1784695575000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["From traditional musicians to digital musicians: a study on talent transformation in the music industries driven by AI technology"],"prefix":"10.3389","volume":"11","author":[{"given":"Wei","family":"Wang","sequence":"first","affiliation":[{"name":"School of Music, Hanshan Normal University","place":["Chaozhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,22]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"2188","DOI":"10.1086\/705716","article-title":"Robots and jobs: evidence from U.S. labor markets","volume":"128","author":"Acemoglu","year":"2020","journal-title":"J. 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