AI in German Media Companies and Digital Industries: Potential for Efficiency, Structural Change, and New Responsibilities

Artificial intelligence (AI) has emerged as a pivotal driver of structural transformation in media companies. This article argues that AI must be understood not merely as an efficiency-enhancing tool in German media companies and digital industries, but as an infrastructural force that restructures production, distribution, editorial authority, and public communication. Across media sectors, AI is legitimized through promises of automation, personalization, audience analytics, and cost reduction. In journalism, it is primarily deployed for routinized tasks such as transcription, summarization, data analysis, headline writing, and workflow support. AI does not simply optimize journalism; it shifts the conditions under which journalism remains visible, credible, and accountable. The decisive problem is therefore not technological capability as such, but the diffusion of responsibility within AI-mediated media environments. As search, aggregation, and answer systems increasingly mediate access to information, journalistic content risks becoming detached from recognizable authorship, institutional context, and editorial judgment. AI resilience is defined as the organizational and professional capacity to integrate AI without surrendering editorial accountability, source protection, public trust, or interpretive sovereignty. Its core requirements are clear responsibility chains, transparent labelling, robust verification, audience dialogue, competence building, and institutional governance beyond mere compliance. The broader conclusion is that AI’s value in media industries is conditional: it can enhance productivity and even support diversity, but only where organizations align technological deployment with normative commitments to credibility, traceability, and human judgment. Without such alignment, AI becomes less a productivity tool than a catalyst of invisibility, mistrust, and weakened democratic mediation. Received: 12th May, 2026; Revised: 13th July, 2026; Accepted: 17th September, 2026

Authors

Publication Details

Journal
VNU Journal of Social Sciences and Humanities
Published
2026-11-06
DOI
https://doi.org/10.33100/jossh.2026.2.2.1
Primary Topic
Journalism and Media Studies
Type
article
Field-Weighted Citation Impact
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article

AI in German Media Companies and Digital Industries: Potential for Efficiency, Structural Change, and New Responsibilities

Felix Leyendecker
3 links
VNU Journal of Social Sciences and Humanities
Journalism and Media Studies
article

AI in German Media Companies and Digital Industries: Potential for Efficiency, Structural Change, and New Responsibilities

Felix Leyendecker
article en

Abstract

Artificial intelligence (AI) has emerged as a pivotal driver of structural transformation in media companies. This article argues that AI must be understood not merely as an efficiency-enhancing tool in German media companies and digital industries, but as an infrastructural force that restructures production, distribution, editorial authority, and public communication. Across media sectors, AI is legitimized through promises of automation, personalization, audience analytics, and cost reduction. In journalism, it is primarily deployed for routinized tasks such as transcription, summarization, data analysis, headline writing, and workflow support. AI does not simply optimize journalism; it shifts the conditions under which journalism remains visible, credible, and accountable. The decisive problem is therefore not technological capability as such, but the diffusion of responsibility within AI-mediated media environments. As search, aggregation, and answer systems increasingly mediate access to information, journalistic content risks becoming detached from recognizable authorship, institutional context, and editorial judgment. AI resilience is defined as the organizational and professional capacity to integrate AI without surrendering editorial accountability, source protection, public trust, or interpretive sovereignty. Its core requirements are clear responsibility chains, transparent labelling, robust verification, audience dialogue, competence building, and institutional governance beyond mere compliance. The broader conclusion is that AI’s value in media industries is conditional: it can enhance productivity and even support diversity, but only where organizations align technological deployment with normative commitments to credibility, traceability, and human judgment. Without such alignment, AI becomes less a productivity tool than a catalyst of invisibility, mistrust, and weakened democratic mediation. Received: 12th May, 2026; Revised: 13th July, 2026; Accepted: 17th September, 2026

VNU Journal of Social Sciences and HumanitiesVol. 2(2)
Openalex Percentile: Top 9%
Journalism and Media Studies
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