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June 21, 2026Global Smart Food Systems0 citationsOpen Access

Land to brand innovation in food processing using digital technologies

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DSD. Singh

Key Points

  • This review examines how digital technologies, particularly AI, impact the agri-food sector.
  • Synthesized advancements in AI applications in agriculture and food systems from academic literature and case studies.
  • Focused on technologies including machine learning, deep learning, computer vision, robotics, and IoT.
  • Critically evaluated barriers related to technology adoption and equity issues.
  • AI and digital tools enhance real-time monitoring, predictive analytics, and personalized consumer insights.
  • Identified challenges in data integration, digital literacy, and ethical concerns hindering widespread implementation.
  • Highlighted the transition towards Industry 4.0 and 5.0 with a focus on sustainable food systems.

Abstract

Purpose This review explores the evolving impact of Artificial Intelligence (AI) and digital technologies on the agri-food sector, examining their roles in enhancing productivity, safety, sustainability and consumer engagement across the food value chain. It also addresses existing barriers and provides a roadmap for inclusive and ethical AI implementation. Design/methodology/approach The paper synthesizes recent advancements in AI applications across agriculture and food systems, drawing from academic literature and case studies. It focuses on technologies such as machine learning, deep learning, computer vision, robotics and the Internet of Things (IoT), evaluating their integration into food production, processing, safety, packaging and personalized nutrition. Challenges related to adoption and equity are critically examined. Findings AI and digital tools are reforming the food system by enabling real-time monitoring, predictive analytics, automated processing, non-invasive quality assessments and personalized consumer insights. These innovations support the transition toward Industry 4.0 and the emerging Industry 5.0, with human-centric, sustainable and resilient food systems. However, widespread implementation is hindered by data integration challenges, digital literacy gaps, ethical concerns and infrastructure limitations, particularly in low- and middle-income countries. Originality/value This review provides a comprehensive and forward-looking perspective on the role of AI in the agri-food sector. It uniquely combines technological insight with socio-ethical analysis, offering strategic guidance for inclusive, sustainable and responsible AI adoption in global food systems.

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Cite This Study

D. Singh (2026) studied this question.

synapsesocial.com/papers/6a3781db24f042ddf4c5b7d1https://doi.org/10.1108/gsfs-08-2025-0022
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Artificial Intelligence in the Food Industry: Transforming Safety, Efficiency, and Sustainability From Farm to Fork2026 · 2 citations
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  3. 3Recent Trends in Artificial Intelligence and IoT in the Agro-Food Industry: Smarter Farming to Safer Plates2026
  4. 4The Digital Transformation of Food Systems: A Review of Artificial Intelligence in Food Technology2026 · 1 citations
  5. 5Transforming the Food Industry with Artificial Intelligence: Applications, Challenges and Future Prospects2025