The Potential of Artificial Intelligence in Enhancing Recycling Processes and Reducing Environmental Pollution: A Critical Review and Framework for an Emerging-Market Context

Vollständiger Abstract

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Jordan landfills or dumps more than ninety percent of its solid waste and recycles only around a tenth of it, placing recycling and pollution reduction at the center of its green-growth agenda, aligning with Sustainable Development Goal 12 on responsible consumption and production. Artificial intelligence (AI) is widely proposed to improve recycling through sorting, prediction, and process optimization, yet the evidence is fragmented: technical studies show what AI can do, while management studies examine AI capability and green outcomes elsewhere, and the two rarely meet around recycling in a resource-constrained setting. This paper offers a critical narrative review of these literatures and develops an integrative framework. Reading the evidence through the natural resource-based view and the dynamic capabilities perspective, we argue that an AI waste capability improves environmental performance mainly by enabling circular economy practices, and that environmental regulatory pressure conditions how strongly firms convert the capability into circular action. We synthesize the state of knowledge, identify gaps, and advance five propositions and a research agenda to test them in emerging markets such as Jordan. It connects the technical, capability, and circular-economy literatures and gives researchers and policymakers a structured basis for turning AI adoption into environmental gains.