Kompetencer, tempo og fordeling

Generativ AI og den kompetencebaserede forhandlingslogik i den danske model

Abstract

Competences, tempo and redistribution: Generative AI and the competence-based negotiation logics in the Danish model
This article analyzes the encounter between generative artificial intelligence (GenAI) and the Danish labor market model. Drawing on international research, the article identifies three structural challenges to the current competence-based bargaining logic: a leveling effect, whereby GenAI may reduce productivity differentials between experienced and inexperienced knowledge workers, undermining the basis for competence-based wage negotiation; a tempo narrative, in which accelerationist rhetoric delegitimizes the deliberative processes through which competences are priced; and a distribution problem, as potential productivity gains require sectoral coordination or political intervention that exceeds the model’s workplace-level mechanisms. These challenges converge on the segments of the labor market where competence-based bargaining is strongest and where GenAI is projected to have the greatest impact: knowledge workers under individually negotiated agreements. Through an illustrative analysis of the two most comprehensive AI policy statements by the Danish social partners, the Danish Trade Union Confederation’s AI Panel report and the Confederation of Danish Industry’s position paper AI for All, the article demonstrates how both parties translate GenAI into familiar institutional frameworks while leaving key structural tensions unaddressed. Neither side articulates the possibility that GenAI may not merely be an object of negotiation but could alter the structural preconditions on which their bargaining power rests. The article argues for a position between technological determinism and institutional optimism, showing that while labor market institutions actively shape how AI is integrated, the technology may simultaneously transform the foundations those institutions depend upon.