Table 4 AI mechanisms targeting food...

Table 4

AI mechanisms targeting food consumption opportunity

Opportunity element	Examples	AI mechanism	Value for consumer	Sustainability outcome	Reference
Personalized discovery of sustainable food options	AI recommenders with local/eco filters in e-commerce and shopping platforms	Recommender systems with environmental filters and location data	Sustainability insight, Personalization and relevance, Convenience and accessibility	More sustainable products purchased (e.g. local, eco-labeled)	Aman et al. (2025), Kamran et al. (2021), Starke et al. (2025), Chatterjee et al. (2025)
Instant eco-feedback while shopping or eating	Mobile apps with barcode scanning and carbon scoring at point of purchase	Carbon scores, eco-labels, mobile barcode feedback	Sustainability insight, Behavioral support, Trust and transparency	Fewer purchases of high-impact or overpackaged items	Braga et al. (2024), Linseisen et al. (2025), Tanwar et al. (2024), Zumthurm et al. (2025), Capecchi et al. (2025)
Social comparison and motivation via peer benchmarks	Community dashboards and gamified leaderboards showing sustainable progress	Community dashboards, gamification, leaderboards	Engagement and Participation, Behavioral Support, Self-identity Value	Higher motivation to maintain sustainable food habits	Aman et al. (2025), Wandhekar et al. (2024), Beery et al. (2024a)
Effortless switching to sustainable alternatives	Checkout nudges and cart swap systems in digital shopping	Cart filters, sustainable swap prompts, checkout nudges	Convenience and Accessibility, Behavioral Support, Ethical Empowerment	More frequent substitution of unsustainable products	Chiu et al. (2022), Kamran et al. (2021), Tanwar et al. (2024), Huang et al. (2025), Nunkoo et al. (2024)

Opportunity element	Examples	AI mechanism	Value for consumer	Sustainability outcome	Reference
Personalized discovery of sustainable food options	AI recommenders with local/eco filters in e-commerce and shopping platforms	Recommender systems with environmental filters and location data	Sustainability insight, Personalization and relevance, Convenience and accessibility	More sustainable products purchased (e.g. local, eco-labeled)	Aman et al. (2025), Kamran et al. (2021), Starke et al. (2025), Chatterjee et al. (2025)
Instant eco-feedback while shopping or eating	Mobile apps with barcode scanning and carbon scoring at point of purchase	Carbon scores, eco-labels, mobile barcode feedback	Sustainability insight, Behavioral support, Trust and transparency	Fewer purchases of high-impact or overpackaged items	Braga et al. (2024), Linseisen et al. (2025), Tanwar et al. (2024), Zumthurm et al. (2025), Capecchi et al. (2025)
Social comparison and motivation via peer benchmarks	Community dashboards and gamified leaderboards showing sustainable progress	Community dashboards, gamification, leaderboards	Engagement and Participation, Behavioral Support, Self-identity Value	Higher motivation to maintain sustainable food habits	Aman et al. (2025), Wandhekar et al. (2024), Beery et al. (2024a)
Effortless switching to sustainable alternatives	Checkout nudges and cart swap systems in digital shopping	Cart filters, sustainable swap prompts, checkout nudges	Convenience and Accessibility, Behavioral Support, Ethical Empowerment	More frequent substitution of unsustainable products	Chiu et al. (2022), Kamran et al. (2021), Tanwar et al. (2024), Huang et al. (2025), Nunkoo et al. (2024)

Note(s): The table outlines how AI tools reshape external conditions –through recommender systems, eco-feedback, social benchmarks, and checkout nudges – to lower barriers and create enabling environments for sustainable food choices

Source(s): Authors’ own

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