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        <datestamp>2026-10-05T13:21:58Z</datestamp>
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          <dc:title>Table 1_The role of artificial intelligence in food systems transformation: a review of opportunities, challenges, and future directions.docx</dc:title>
          <dc:creator>Neo Mokone (25313169)</dc:creator>
          <dc:creator>Emmanuel Ndhlovu (25313172)</dc:creator>
          <dc:subject>Food Packaging, Preservation and Safety</dc:subject>
          <dc:subject>artificial intelligence</dc:subject>
          <dc:subject>food security</dc:subject>
          <dc:subject>food systems</dc:subject>
          <dc:subject>food systems transformation</dc:subject>
          <dc:subject>sustainability</dc:subject>
          <dc:description>&lt;p&gt;Global food systems face increasing pressure from climate change, resource scarcity, and supply-chain disruptions, creating a need for more integrated and resilient responses. This study critically examines the role of artificial intelligence (AI) in food-systems transformation through a systematic literature review of publications from 2020 to 2026. Guided by the PRISMA 2020 guidelines, the review searched multiple academic databases and applied predefined and subsequently refined eligibility criteria to identify and synthesize evidence from 40 publications addressing AI applications, implementation challenges, governance, sustainability, socio-technical conditions, and adoption patterns across food-system domains. The findings indicate that AI can support improvements in productivity, quality control, supply-chain traceability, resilience, and decision-making. However, these benefits are not automatic and depend on socio-technical readiness, governance, digital infrastructure, data systems, and organizational capability. Building on these findings, the review develops an integrated dynamic socio-technical AI food systems transformation framework by integrating socio-technical systems theory and diffusion of innovation theory. The framework conceptualizes AI-enabled food-systems transformation as a dynamic and conditional process and provides a basis for future research, policy development, and responsible AI implementation.&lt;/p&gt;</dc:description>
          <dc:date>2026-10-05T13:21:58Z</dc:date>
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          <dc:identifier>10.3389/fsufs.2026.1892956</dc:identifier>
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