Frontiers in sociology · 2026
From traditional musicians to digital musicians: a study on talent transformation in the music industries driven by AI technology.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Wang Wei
Аннотация
INTRODUCTION: 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.
METHODS: 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.
RESULTS: 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.
DISCUSSION: 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.
METHODS: 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.
RESULTS: 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.
DISCUSSION: 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.