Methods for investigating online food environments with artificial intelligence: a systematic review.

BACKGROUND: The online food environment has transformed how individuals access and engage with food by amplifying food availability and promotions. Artificial intelligence (AI) offers scalable solutions to investigate and monitor this space, yet its application across food environment dimensions has not been systematically reviewed. OBJECTIVE: This systematic review examined how AI methods have been applied to assess key online food environment dimensions, including food availability, marketing, price, and nutritional properties. METHODS: We conducted a systematic review, searching Scopus, Web of Science, PubMed, and ABI/INFORM in 2024. Eligible studies were English-language and applied AI to assess online food environment platforms. Titles and abstracts were screened using an AI-based tool (ASReview) and manual review, followed by full-text screening. We assessed food environment setting and dimension, AI method, subfield, algorithm and study quality. RESULTS: In total, 19 studies applied different AI methods, mainly supervised learning, natural language processing (NLP), and computer vision across multiple platforms. Food availability was most frequently assessed, followed by nutritional properties and marketing. Fewer studies addressed pricing or individual exposure. Applications included food and outlet classification, caloric estimation, and consumer engagement analysis. Rule-based NLP enabled large-scale data collection. CONCLUSIONS: AI is increasingly applied to analyze the online food environment, particularly food availability, marketing, and nutrition. Research remains fragmented across platforms and regions, with limited comparative evaluations and standardization. To improve scalability and impact, future efforts should prioritize FAIR-compliant (Findable, Accessible, Interoperable, and Reusable) infrastructure, semantic data integration, multimodal transfer learning, and better alignment with public policy goals.