EXTENDED SUMMARY

This article examines the effects of artificial intelligence on industrial relations with specific reference to trade unions, collective bargaining and strike dynamics. The central argument of the study is that artificial intelligence should not be considered merely as a technical innovation or a productivity-enhancing tool. Rather, it constitutes an institutional and political transformation that reshapes labour-capital relations, workplace power structures and the regulatory foundations of industrial relations systems.

The study is located within the broader industrial relations literature, which has long emphasized that technological change does not operate independently of institutional arrangements. From the Industrial Revolution to digitalization, technological transformations have altered the organization of work, the structure of labour markets and the balance of power between employers and workers. However, artificial intelligence differs from earlier technological changes because it does not only affect physical labour or routine production tasks. Generative AI, algorithmic management and data-driven decision systems increasingly influence cognitive labour, managerial coordination, performance evaluation, workplace surveillance and decision-making processes. This shift brings artificial intelligence to the centre of contemporary debates on labour process control, collective representation and workplace democracy.

The theoretical framework of the article draws primarily on labour process theory and institutional approaches in industrial relations. Labour process theory, particularly Braverman’s analysis of managerial control, provides a useful lens for understanding how technology may be used to reorganize work and intensify employer control over labour. In this context, algorithmic management represents a new form of digital control, through which workers’ performance, behaviour and productivity can be continuously monitored, evaluated and directed. At the same time, institutional industrial relations theory shows that the consequences of artificial intelligence are not technologically predetermined. They are shaped by trade union strength, collective bargaining structures, legal regulation, social dialogue mechanisms and the broader balance of power among labour, capital and the state.

The article adopts a qualitative, comparative and theoretical research design. It reviews international literature on artificial intelligence, digitalization, algorithmic management, platform work, collective bargaining and industrial relations systems. The analysis is based on descriptive and critical-interpretive methods. It compares different institutional models, including the Nordic and coordinated European systems, Anglo-Saxon liberal market systems and developing country contexts. This comparative perspective enables the study to show how the effects of artificial intelligence differ according to institutional capacity, union density, bargaining coverage and regulatory traditions.

The first major finding is that artificial intelligence transforms trade union organization. Platform work, remote work, individualized employment relations and algorithmic supervision weaken traditional workplace-based organizing models. Workers are increasingly dispersed across digital platforms and governed by opaque algorithmic systems rather than direct human supervision. This creates difficulties for union recruitment, representation and collective identity formation. However, artificial intelligence and digital technologies also create new opportunities for unions. Online communication networks, data analysis, digital campaigns and platform-based solidarity practices may enable unions to reach fragmented workers and develop new forms of organization. As a result, unions in the AI era are no longer limited to defending wages and working conditions; they must also address data rights, algorithmic transparency, digital surveillance, automated decision-making and lifelong learning.

The second major finding concerns collective bargaining. Artificial intelligence expands the agenda of collective bargaining beyond traditional issues such as wages, working time and social benefits. Algorithmic management, data governance, privacy, digital rights, human oversight and transparency have become new bargaining topics. Collective agreements increasingly need to regulate how workplace technologies are introduced, how employee data are collected and used, how automated decisions are made and how workers can challenge algorithmic outcomes. In this respect, collective bargaining becomes a mechanism of technological governance. It does not merely respond to the consequences of technological change after they occur; it can shape the conditions under which artificial intelligence is implemented in the workplace.

The third major finding relates to strike dynamics and collective action. In traditional industrial relations, strikes were largely based on the physical interruption of production. Digitalization and artificial intelligence alter this logic. In platform capitalism, work is organized through data flows, digital infrastructures and algorithmic coordination. This weakens some forms of workplace-based industrial action, especially where automation allows production or service delivery to continue with reduced labour input. Yet it also creates new vulnerabilities. Since digital production depends on platforms, data, visibility and network coordination, collective action may increasingly target these infrastructures. Digital boycotts, platform-based work stoppages, data-related resistance and online coordination may become important components of labour conflict in the AI era.

The comparative analysis demonstrates that artificial intelligence produces different consequences across industrial relations regimes. In Nordic and coordinated European systems, stronger unions, coordinated bargaining and social dialogue provide greater capacity to regulate AI collectively. Worker participation, consultation rights and co-determination mechanisms may limit unilateral employer control over algorithmic systems. In Anglo-Saxon systems, where bargaining is more decentralized and employer discretion is broader, AI is more likely to be implemented as a managerial tool for surveillance, performance optimization and cost reduction. In developing countries, limited institutional capacity, informal employment, weak unionization and digital inequality may intensify the risks of precariousness, exclusion and unregulated algorithmic control.

Overall, the article concludes that artificial intelligence does not eliminate industrial relations; it redefines them. Trade unions, collective bargaining and strikes remain central, but their content, strategies and institutional functions are changing. A fair and democratic digital labour regime depends not only on technological capacity but also on strong social dialogue, effective collective bargaining, transparent regulation and renewed forms of collective representation. Therefore, the future of work in the age of artificial intelligence will be determined less by technology itself than by the institutional framework and power relations through which it is governed.