AI-Enabled Digital Product Passports in Emerging Economies: A Systematic Literature Review of Explanations, Evidence and Blind Spots

Digital product passports are becoming a legal requirement for goods sold in the European Union, and artificial intelligence is increasingly proposed as the means of turning these passports from static records into analytical tools. Because most of the data that a passport must carry is generated by suppliers, factories and smallholder producers in emerging economies, the way these actors adopt, or are excluded from, passport systems will decide whether the instrument supports circular production or simply shifts compliance costs upstream. This review asks how the current literature explains the adoption of digital product passports, with particular attention to passports enabled by artificial intelligence and to emerging-economy settings, and which behavioural and organisational questions remain unanswered. Two bibliographic databases were searched for studies published between 2015 and 2026, and 268 studies were included after title-and-abstract screening and coded for theoretical lens, level of analysis, research design, the role of artificial intelligence and country context. The literature explains adoption mainly from the outside in: as compliance with regulation, as a configuration of technological, organisational and environmental conditions, as a problem of inter-organisational data governance and orchestration, and, for consumers only, as individual technology acceptance. Studies that place artificial intelligence at the centre are conceptual or small feasibility tests, while emerging-economy studies are descriptive readiness assessments; no study combines the two. Five blind spots follow, concerning the intersection of artificial intelligence and emerging economies, supplier-side managerial cognition, power and value distribution in buyer–supplier relationships, non-adoption, and the workforce. The review derives two sets of suggestions from these gaps. Researchers should test institutional, resource-dependence and technology–organisation–environment explanations with supplier samples in emerging economies, examine managerial cognition as an antecedent of adoption and non-adoption as a strategic response, and evaluate AI-enabled data capture in field settings. Brands, industry associations, local universities and policymakers should support training for owner-managers and factory data staff, shared low-cost data infrastructure organised through clusters or cooperatives, and phased obligations with capacity support, so that passports advance Sustainable Development Goals 8, 9 and 12 without excluding the weakest actors in global value chains.