Reshaping the core competitiveness of broadcasters in the context of AI: emotional expression, cultural control and human-machine collaboration

Under the impetus of artificial intelligence, the core competencies of traditional broadcasters are severely tested. This study constructs a three-dimensional model of the broadcasters’ core competencies in the context of artificial intelligence, namely emotional competency, cultural competency, and human-AI collaborative competency. On the basis of mixed methods, surveys on 300 broadcasters, 500 audiences, and 50 media organizations were implemented, supplemented by in-depth interviews and case studies. The findings show that under the impact of artificial intelligence, the three aspects of broadcasters’ core competency all indicated significant improvement: emotional competency increased from a mean score to a mean score, improving by 0.45 points; cultural competency increased from a mean score to a mean score, improving by 0.42 points; human-AI collaborative competency increased from a mean score to a mean score, improving by 0.43 points; core competency index increased from a mean score to a mean score, improving by 43%. The weights for the three dimensions are 42%, 35%, and 23% respectively, with emotional competency being most prominent. The research findings can be used to inform broadcaster education and media professional development.

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Publication Details

Journal
Perspectives of Communication&Media
Published
2025-08-31
DOI
https://doi.org/10.63808/pcm.v1i2.197
Primary Topic
AI in Service Interactions
Type
article
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article

Reshaping the core competitiveness of broadcasters in the context of AI: emotional expression, cultural control and human-machine collaboration

Meili Chen
Perspectives of Communication&Media
AI in Service Interactions
article

Reshaping the core competitiveness of broadcasters in the context of AI: emotional expression, cultural control and human-machine collaboration

Meili Chen
article en

Abstract

Under the impetus of artificial intelligence, the core competencies of traditional broadcasters are severely tested. This study constructs a three-dimensional model of the broadcasters’ core competencies in the context of artificial intelligence, namely emotional competency, cultural competency, and human-AI collaborative competency. On the basis of mixed methods, surveys on 300 broadcasters, 500 audiences, and 50 media organizations were implemented, supplemented by in-depth interviews and case studies. The findings show that under the impact of artificial intelligence, the three aspects of broadcasters’ core competency all indicated significant improvement: emotional competency increased from a mean score to a mean score, improving by 0.45 points; cultural competency increased from a mean score to a mean score, improving by 0.42 points; human-AI collaborative competency increased from a mean score to a mean score, improving by 0.43 points; core competency index increased from a mean score to a mean score, improving by 43%. The weights for the three dimensions are 42%, 35%, and 23% respectively, with emotional competency being most prominent. The research findings can be used to inform broadcaster education and media professional development.

Perspectives of Communication&MediaVol. 1(2)
Shijiazhuang Academy of Agriculture and Forestry Sciences (CN), Hebei Academy of Sciences (CN)
Openalex Percentile: Top 88%
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Reshaping the core competitiveness of broadcasters in the context of AI: emotional expression, cultural control and human-machine collaboration — Meili Chen · Perspectives of Communication&Media (2025) | TGRS Research Map | TGRS