Report Highlights Emerging Collective Bargaining Practices for AI in European Service Sectors
A report released earlier this year, titled “Collective Bargaining Practices on AI and Algorithmic Management in European Services Sectors,” is providing an in-depth analysis of how artificial intelligence (AI) and algorithmic management are being integrated into workplaces and the subsequent collective bargaining practices that have emerged in response. This study, prepared by UNI Europa and the Friedrich Ebert Stiftung (FES) Competence Centre on the Future of Work, explores the increasing use of AI in various industries, particularly within the service sectors, and highlights the challenges and opportunities this technology presents for both employers and employees.
The report begins by detailing the current state of AI and algorithmic management systems (AAMS) in the workplace. AI systems, defined as machine-based systems capable of making predictions, recommendations, or decisions with limited human oversight, are becoming more prevalent. These systems are often marketed for their ability to enhance efficiency and objectivity by reducing human subjectivity. However, they can also perpetuate and amplify existing disparities and biases, leading to concerns about algorithmic bias, unjust handling of employee data, and encroachments on personal privacy.
The State of AI Bargaining Across Europe
The study combines desk research with a survey of 148 trade union representatives from 32 countries and an analysis of 31 existing collective agreements that include AI-related provisions. The findings show that bargaining over AI is still in its early stages but steadily expanding. About 42% of UNI Europa affiliates report active discussions on AI topics, while 20% of unions already have collective agreements addressing AI governance, worker data rights, or algorithmic oversight.
Examples across Europe illustrate these early agreements. In Italy, unions FILCAMS-CGIL and FISASCAT-CISL reached an agreement with Partesa, a Heineken subsidiary, regarding a smartphone application used to monitor drivers. In the UK, the GMB union negotiated with Hermes to modify the company’s automated payment system to ensure drivers receive at least the minimum wage and bonuses without needing to request them retroactively. Similarly, in Spain, Telefonica signed a national agreement on the right to disconnect with trade unions UGT and Comisiones Obreras, and the country enacted the “Riders’ Law,” requiring companies to inform workers’ representatives about the criteria and operation of algorithms affecting working conditions.
Key Bargaining Topics: Privacy, Data, and Work Hours
According to the survey, data protection and privacy dominate AI-related bargaining. Other common concerns include the use of AI to monitor employee activities, schedule shifts, or determine working hours. In contrast, hiring-related applications of AI remain less frequently negotiated.
Unions also advocate for workers’ rights to challenge automated decisions and to seek independent expert advice on algorithmic systems. These demands reflect growing recognition that AI tools influence not only productivity but also fairness and dignity at work.
Future Outlook: Building Worker Protections in the AI Era
The report concludes that collective bargaining on AI will become increasingly vital as digital systems spread through European workplaces. Unions are focusing on data protection, privacy, and job quality while pressing for transparency in how AI decisions are made.
By analyzing real-world agreements and survey data, UNI Europa and FES highlight best practices that can guide unions across Europe. These include securing access to algorithmic information, ensuring human oversight, and integrating AI clauses into broader labor frameworks. As AI technologies continue to evolve, collective bargaining provides a critical mechanism to balance innovation with fairness and worker protection.
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