The Impact of Artificial Intelligence on Sustainable Regional Innovation Ecosystems and Participation

Abstract

This study explores the transformative role of Artificial Intelligence (AI) within the context of Regional Innovation Ecosystems (RIVs), Smart Specialisation Strategies (RIS3), and the European Union’s Mission on Adaptation to Climate Change. Building upon ten empirical cases from nine countries in the Baltic Sea region, the research examines AI’s potential to enhance sustainable development, climate resilience, and inter-regional cooperation. While the literature on regional innovation emphasizes governance models, stakeholder engagement, and impact assessment, the specific contributions and limitations of AI within these frameworks remain underexplored. This study aims to fill that gap by analyzing the integration of AI across various components of regional development strategies.AI offers substantial benefits in climate adaptation through enhanced data processing capabilities. It improves climate modeling and forecasting by analyzing vast datasets from satellites, sensors, and historical records, enabling more accurate predictions of extreme weather events and strengthening early warning systems. AI supports the optimization of critical resources such as water, energy, and land, and informs the development of adaptive infrastructure including smart energy grids. It also aids in ecosystem conservation and enhances carbon capture through predictive modeling. In the domain of regional collaboration, AI facilitates partner identification and strategic matchmaking by analyzing regional strengths, competencies, and innovation needs. It supports multilingual knowledge-sharing platforms and provides real-time translation, thus lowering communication barriers and improving cross-border collaboration. AI-driven tools also enhance the Entrepreneurial Discovery Process (EDP) by delivering market trend analysis, identifying niche areas for specialization, and simulating policy outcomes to guide strategic decisions. When embedded in participatory processes, AI augments human-centric approaches by analyzing qualitative data from stakeholder workshops, identifying dominant themes, and offering real-time facilitation support. Furthermore, AI can support the creation of targeted communication materials, helping tailor regional development messages to different audiences. The benefits of AI integration include increased speed and efficiency in innovation processes, greater accuracy in modeling and assessments, enhanced foresight through pattern recognition, optimized resource allocation, and scalable solutions that can address both local and global challenges. AI also helps navigate the complexity inherent in multi-stakeholder ecosystems and climate governance. However, several disadvantages merit attention. High initial costs for infrastructure and skilled personnel can impede adoption, especially in less developed regions. The reliability of AI depends heavily on data quality; biased or incomplete data can lead to flawed outputs. Ethical risks include algorithmic bias, lack of transparency, and the “black box” nature of many AI systems. These concerns call for robust oversight and inclusive governance mechanisms. Additionally, AI cannot replicate human intuition, creativity, or value-based judgment, which are essential in participatory and strategic processes. Risks such as job displacement, cybersecurity threats, and the environmental impact of energy-intensive AI systems also raise critical concerns. Finally, there is a risk of widening the digital divide between technologically advanced and under-resourced regions. In conclusion, AI holds significant potential to accelerate sustainable regional innovation, smart specialisation, and climate adaptation. However, realizing these benefits requires a careful balance between technological advancement and social responsibility. Human agency, ethical oversight, and inclusive governance must remain central to ensure that AI contributes to equitable and resilient regional futures.