From deployment to longevity: Can agentic AI sustain IoT systems?

IoT deployments often face premature obsolescence due to evolving protocols, fragmented software stacks, hardware heterogeneity, and aging machine-learning models, leading to costly replacements. This talk explores whether agentic AI - combining large language models with autonomous agents - can sustain IoT systems by enabling automated lifecycle management that adapts code, models, and configurations as requirements, environments, and hardware evolve. It highlights feasibility and usability aspects of running language models on edge devices while addressing open questions around collaborative edge–cloud intelligence, adaptive deployments, and model aging, with a view toward the longevity and sustainability of future IoT infrastructures.