Connectedness and risk transmission across artificial intelligence industries

Artificial Intelligence (AI) has emerged as a key innovation in the global economy, with AI-related equities becoming major drivers of the recent stock market upswing. Yet, the internal dynamics and heterogeneity within the AI sector remain largely unexplored. We address this gap by analyzing the connectedness and risk transmission among four AI industries: hardware manufacturers, cloud providers, application developers, and AI-intensive BigTech firms, using self-constructed stock market indices for 2023–2025. Adopting an industry-level perspective, we explicitly account for the heterogeneous structure of the AI sector. By capturing both static dependence and dynamic patterns, we assess how intrasectoral relationships evolve over time and under varying market conditions. Results indicate strong positive relationships among the four AI industries, which intensify during periods of market stress. Cross-industry spillovers account for more than half of return variation in the AI sector, though they remain modest under normal conditions. During sharp market swings, particularly downturns, shocks propagate widely across all industries. While AI hardware manufacturers and AI BigTech typically act as net shock transmitters and AI application developers and cloud providers as net receivers, their roles shift over time. Our results emphasize the need for dynamic hedging, as static diversification offers limited protection in stressed markets, and closer monitoring of cross-industry exposures. Given the growing dependence of many sectors on AI infrastructure, disruptions in key AI segments may have wider systemic effects and should be incorporated into macroprudential oversight.