Digitally nourished: unveiling AI solutions for promoting sustainable food consumption – toward a conceptual framework

Purpose This study examines the use of artificial intelligence (AI) in consumer-facing food systems to support sustainable consumption. It aims to synthesize empirical insights, identify dominant types of AI interventions and propose a process-based theoretical model that captures how AI solutions facilitate sustainable consumer behavior. Design/methodology/approach A systematic literature review was conducted in accordance with the SPAR-4-SLR protocol. 66 peer-reviewed articles published between 2010 and 2025 were included. Results were thematically organized using Transformative Consumer Research (TCR) and Technology Affordances to explore how AI-enabled solutions facilitate value creation and foster behavior change in sustainable food consumption contexts. Findings Five key AI domains were identified: product discovery, sustainability signaling, dietary guidance, household food management and social engagement. While personalization and health nudging dominate current applications, the potential of AI to drive long-term sustainable behavior remains underexploited. Existing research is fragmented and often lacks an integrative theoretical foundation. Originality/value This paper introduces the AI-Enabled Behavioral Activation Model for Sustainable Consumption, a novel theoretical framework grounded in transformative consumer research (TCR), transformative value theory (TVT), technology affordances and the COM-B model of behavior change. The model conceptualizes how AI solutions catalyze sustainable behavior by enabling consumer capabilities, shaping motivational processes, and expanding action opportunities, all while generating experiential and ethical forms of value. This integrative, process-based approach advances theoretical understanding of AI’s transformative potential in food-related consumer behavior.