Artificial intelligence (AI) brings new opportunities to boost productivity and promote sustainability and responsible business conduct. Applications span all business functions and pervade all sectors, jobs and regions, with the potential to transform economies, labour markets and societies. AI is also reshaping public governance and the making of public policies, by enabling greater efficiency, responsiveness and accountability in public action.
Recent diffusion, however, has been more driven by frontrunners escaping the pack than laggards catching up. The release of generative AI has lowered barriers to adoption, by allowing the use of pre-trained models for automating administrative tasks or creating new value from new data. But not all places, people or firms have the same capacity to transform, uneven progress opening gaps in the transition.
The prime AI adopter regions are innovation leaders, standing out as global tech hubs, where businesses are integrated into specialised knowledge networks and global value chains. As their innovation performance decreases, regions appear using less AI and being slower on uptake. The skills of local workforces play a pivotal role in these divides both as enablers as well as barriers to adoption . This fragmentation, and the speed at which divides appeared, raise concerns about competitiveness and territorial cohesion, especially since technology lags are difficult to overcome.
For businesses, regional governments or cities, scaling implementation remains challenging. Integrating AI is complex and context specific, requiring local tailored solutions for sourcing strategic assets for AI, upgrading legacy systems, adapting labour markets, revising skills and employment policies, or financing the transition. Managing AI risks and mitigating its adverse impacts on economies, labour markets and the environment, land use, or natural resources further heighten the complexity and cost of transformation.
Regional, urban, rural and local development policies can drive broader AI diffusion by creating the conditions for system transformation. In turn, AI can help improve these policies, by better addressing their cross-sectoral, multi-level and multi-stakeholder nature, and by better tailoring design and implementation to places.
Ensuring that AI delivers its full promises requires robust evidence on places’ AI readiness, exposure and adoption, strong stakeholders’ engagement and renewed policy capacity to inform place-based strategies and align action and investments.
