Exploring perspectives on AI adoption for smart energy: bridging lived practices and expert insights from Greek homes

Abstract

Artificial Intelligence (AI) is increasingly promoted as a solution for household energy management, yet adoption remains uneven due to infrastructural constraints, AI skepticism and privacy concerns. This paper explored the factors that shape AI adoption in Greek homes, situated within the Plegma Living Lab. The study engaged nine residents and six smart home experts in a two-phase participatory study to examine how lived practices and expert perspectives shape adoption. Our findings show that AI adoption is shaped by three key factors: awareness (driven by visibility and control over energy use), knowledge (enabled through personalised and explainable AI), and engagement (sustained by socially meaningful and motivating feedback). Experts highlighted tensions around predictability, affordability, ecosystem integration, and privacy. By bridging residents’ lived experiences with expert insights, we propose several design implications for supporting AI adoption in the home energy context.