Generative Artificial Intelligence (GenAI) is reshaping Industry 5.0 manufacturing by enabling distributed automation and real-time decision support across socio-technical production systems. However, frequent model updates, stochastic behaviour, and upstream dependencies on foundation models create a persistent risk of misalignment between regulatory intent, organisational governance, and technical system behaviour. Existing governance approaches remain insufficiently equipped to address this dynamic instability. This paper develops a socio-technical systems (STS)-inspired governance framework based on a structured literature review. It conceptualises GenAI governance as a multi-dimensional alignment problem and distinguishes three interdependent logics: (i) cross-level alignment, capturing structural coherence between macro-level regulation, meso-level organisational governance, and micro-level system behaviour; (ii) cross-domain alignment, capturing relational coherence across normative principles, policy instruments, and ecosystem coordination mechanisms; and (iii) cross-lifecycle alignment, capturing temporal durability under continuous system evolution. The framework is then operationalised through characteristic Industry 5.0 mechanisms. In sum, the paper advances STS-based governance research by showing that effective GenAI governance depends not only on structural and relational fit, but also on temporal durability under continuous technological change, enabling trustworthy, accountable, and sustainable Industry 5.0 manufacturing ecosystems.
Absmayr et al. (Thu,) studied this question.