AI-driven Transformation in Coffee Agribusiness: a Systematic Review of Innovation, Efficiency, and Sustainability Interactions and Future Research Potential

DOI

10.2991/978-94-6463-908-7_8How to use a DOI?

Keywords

AI and coffee; Digital transformation; Efficiency; Innovation; Sustainability; Systematic literature review

Abstract

This study aims to map the impact of digital transformation driven by AI technology in the coffee industry, focusing on three key aspects: efficiency, innovation, and sustainability, as well as their interactions. Through a systematic review of hundreds of existing studies, this research identifies patterns in AI technology adoption and uncovers future research opportunities to expand its applications, including its effects on SMEs and smallholder farmers. This article employs a Systematic Literature Review (SLR) to examine the latest developments in AI technology adoption within the coffee industry. The primary focus is to map the benefits of AI in enhancing operational efficiency, driving product and process innovation, and strengthening sustainability. Additionally, this study explores the interconnections among these three aspects in shaping a more inclusive and sustainable digital ecosystem for industry stakeholders. The review indicates that while AI adoption in the coffee industry continues to expand, studies examining the interactions between efficiency, innovation, and sustainability remain scarce. Among the articles reviewed, 33 key benefits of AI technology implementation in the coffee sector were identified. The mapping reveals that efficiency is the most dominant aspect, followed by innovation and then sustainability. Additionally, many of these benefits overlap, creating opportunities for further research to optimize AI applications in the industry.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Antasalam Ajo
AU  - La Rianda Baka
AU  - Ansharullah Ansharullah
AU  - Tamrin Tamrin
PY  - 2025
DA  - 2025/12/07
TI  - AI-driven Transformation in Coffee Agribusiness: a Systematic Review of Innovation, Efficiency, and Sustainability Interactions and Future Research Potential
BT  - Proceedings of the International Conference on Innovation in Food Science, Culinary Art, and Fashion Technology (INNOFATEC 2025)
PB  - Atlantis Press
SP  - 88
EP  - 111
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-94-6463-908-7_8
DO  - 10.2991/978-94-6463-908-7_8
ID  - Ajo2025
ER  -