Interaction of AI and consumer behavior - A systematic literature review and future research agenda.

The way consumers interact with websites and apps and make decisions about what to buy has been profoundly changed by artificial intelligence (AI). But a large portion of the material now in publication still uses conventional adoption models, frequently ignoring important psychological, ethical, and emotional aspects of AI-consumer interactions. This study analyses 197 peer-reviewed papers from 2011 to 2025 using the TCCM (Theory, Context, Characteristics, Methodology) framework and performs a Systematic Literature Review (SLR) following PRISMA and SPAR-4-SLR criteria. Despite their continued dominance, theories such as the Technology Acceptance Model (TAM) and UTAUT are unable to adequately explain behavioral elements including perceived danger, anthropomorphism, personalization, and trust. Post-adoption behavior, demographic diversity, and emotional ties to AI are important study needs. To overcome these limitations, the paper suggests a conceptual paradigm that combines Social Presence Theory with TAM. For companies and policymakers looking to improve AI trust, ethical alignment, and customized customer experiences in digital settings, the findings provide theoretical insights and real-world consequences.