AI-driven sustainable alliances for regional innovation: Strategic governance and digital transition.

This paper presents a novel, behaviorally informed framework for enhancing the implementation of Regional Innovation Strategies for Smart Specialization (RIS3) by integrating artificial intelligence (AI) tools with sustainable alliance governance. Drawing on comparative case studies from the Northern Netherlands, Northern Sweden, and two German states (Lower Saxony and Bavaria), the study identifies persistent barriers to RIS3 delivery, including low SME engagement, fragmented interregional collaboration, and weak university-industry alignment. The original contribution of this research lies in its synthesis of behavioral theory (COM-B model) with AI-enabled policy tools—such as chatbots, predictive analytics, and digital maturity assessments—to propose a phased roadmap for more inclusive and adaptive RIS3 governance. Empirical insights are grounded in a triangulated methodology combining stakeholder interviews, policy document analysis, and four supervised bachelor theses. The study demonstrates how centralized coordination platforms, AI-driven support systems, and participatory monitoring mechanisms can collectively address structural and behavioral barriers to innovation policy implementation. By bridging institutional and technological perspectives, this research offers actionable strategies for policymakers and contributes a new theoretical lens for understanding digital and green transitions in regional innovation ecosystems