The Role Of Artificial Intelligence In Promoting Sustainable Supply Chains Across The Food Industry:Evidence From Agriculture, Manufacturing And Fast-Food Retail In India

Authors

  • Purvi Sinha Research Scholar, School of Commerce and Management studies, Sandip University, Sijoul, Madhubani, Bihar Author
  • Dr Bhaskar Mishra Supervisor, School of Commerce and Management studies, Sandip University, Sijoul, Madhubani, Bihar Author

DOI:

https://doi.org/10.66635/kc477w68

Keywords:

Impact of Artificial Intelligence, Sustainable Supply Chain Management, Fast-Food Industry, Consumer Behaviour, Sustainability, India

Abstract

This paper examines how Artificial Intelligence (AI) is reshaping sustainable supply chain management (SSCM) across the food sector, with particular attention to consumer-facing implications for India's fast-food industry. As environmental and ethical concerns increasingly influence purchasing decisions, AI capabilities — demand forecasting, waste-reduction systems and intelligent logistics — are changing how food businesses source, produce and distribute their products. Synthesizing evidence from more than 120 academic and industry sources published between 2015 and 2022, the review traces AI's footprint across four connected stages of the food value chain: agricultural production, manufacturing, supply-chain logistics and consumer engagement. The evidence indicates that AI-enabled SSCM strengthens consumer trust, lifts operational efficiency and supports environmental accountability, positioning it as a meaningful lever for long-term sustainability in food retail, including fast-food operations.

 

 

References

1.Barocas, S., Hardt, M., & Narayanan, A. (2019). Fairness and Machine Learning. fairmlbook.org.

2.Brynjolfsson, E., & McAfee, A. (2017). Machine, Platform, Crowd: Harnessing Our Digital Future. W. W. Norton & Company.

3.Choi, T. M., Wallace, S. W., & Wang, Y. (2018). Big data analytics in operations management. Production and Operations Management, 27(10), 1868–1883.

4.Desai, D. R. (2020). The new empiricists: Regulating AI and machine learning. Georgia Tech Scheller College of Business Research Paper.

5.FAO. (2017). The Future of Food and Agriculture: Trends and Challenges. Food and Agriculture Organization of the United Nations.

6.Føre, M., Frank, K., Norton, T., Svendsen, E., Alfredsen, J. A., Dempster, T., et al. (2018). Precision fish farming: A new framework to improve production in aquaculture. Biosystems Engineering, 173, 176–193.

7.Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.

8.IBM. (2020). IBM Watson Supply Chain: AI-Powered Insights for a Resilient Supply Chain. IBM Institute for Business Value.

9.John Deere. (2020). See & Spray™ Ultimate: The Next Generation of Targeted Spraying. John Deere Press Release.

10.Klerkx, L., Jakku, E., & Labarthe, P. (2019). A review of social science on digital agriculture, smart farming and agriculture

11.4.0. NJAS – Wageningen Journal of Life Sciences, 90–91, 100315.

12.Kumar, A., Ghadge, A., & Tiwari, M. K. (2021). Reinforcement learning for real-time optimization of food processing operations. Journal of Food Engineering, 299, 110499.

13.Lezoche, M., Hernandez, J. E., Alemany Díaz, M. D. M., Panetto, H., & Kacprzyk, J. (2020). Agri-food 4.0: A survey of the supply chains and technologies for the future agriculture. Computers in Industry, 117, 103187.

14.Liakos, K. G., Busato, P., Moshou, D., Pearson, S., & Bochtis, D. (2018). Machine learning in agriculture: A review.

15.Sensors, 18(8), 2674.

16.McKinsey & Company. (2020). The Future of Food: Harnessing Digital Innovation to Transform the Food System.

17.Mohanty, S. P., Hughes, D. P., & Salathé, M. (2016). Using deep learning for image-based plant disease detection. Frontiers in Plant Science, 7, 1419.

18.Mønster, J., Abadi, M., & Saha, S. (2021). A systematic review of artificial intelligence in agri-food supply chains.

19.Computers and Electronics in Agriculture, 191, 106546.

20.Neethirajan, S. (2020). The role of sensors, big data and machine learning in modern animal farming. Sensing and BioSensing Research, 29, 100367.

21.Nestlé. (2021). Annual Report 2021: Driving Operational Efficiency Through Digitalization.

22.Rockström, J., Williams, J., Daily, G., Noble, A., Matthews, N., Gordon, L., et al. (2017). Sustainable intensification of agriculture for human prosperity and global sustainability. Ambio, 46(1), 4–17.

23.Russell, S., & Norvig, P. (2016). Artificial Intelligence: A Modern Approach (3rd ed.). Pearson.

24.Ryan, M. (2020). The social and ethical impacts of artificial intelligence in agriculture: Mapping the field. Agriculture and Human Values, 37(4), 1221–1236.

25.TOMRA. (2021). AI-Powered Food Sorting: The Next Leap in Quality and Sustainability. TOMRA White Paper.

26.Tzachor, A., Devare, M., Richards, C., & Avin, S. (2022). Artificial intelligence in agriculture: A systematic review.

27.Agronomy for Sustainable Development, 42(4), 57.

28.Wang, X., Li, D., & Menassa, C. C. (2018). Understanding the role of artificial intelligence in the food supply chain. International Journal of Production Research, 56(17), 5801–5814.

29.Zonta, T., da Costa, C. A., da Rosa Righi, R., de Lima, M. J., da Trindade, E. S., & Li, G. P. (2020). Predictive maintenance in the Industry 4.0: A systematic review. Computers & Industrial Engineering, 150, 106889.

Downloads

Published

2026-10-03

How to Cite

The Role Of Artificial Intelligence In Promoting Sustainable Supply Chains Across The Food Industry:Evidence From Agriculture, Manufacturing And Fast-Food Retail In India . (2026). Journal of Asia Entrepreneurship and Sustainability, 22(6s), 383-389. https://doi.org/10.66635/kc477w68