Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)

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Artificial Intelligence Augmented Supply Chain Management Platforms for Transparent Logistics Predictive Analytics and Sustainable Trade Ecosystems

Authors
Srinivasarao Paleti1, Enagandula Sunil2, *, P. Bhuvaneswari3, Vikrant Sharma4, 5, Kothuri Parashu Ramulu6, F. Anitha Florence Vinola7
1Assistant Consultant, TCS, Edison, NJ, USA
2Assistant Professor, Department of CSE (AI & ML), St. Martin’s Engineering College (UGC Autonomous) Dhulapally, Secunderabad, Telangana, India
3Assistant Professor, Department of CSE, Sona College of Technology, Salem, Tamil Nadu, India
4Assistant Professor, Computer Science and Engineering, Graphic Era Hill University, Dehradun, India
5Adjunct Professor, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India
6Associate Professor, Department of Computer Science and Engineering, Indur Institute of Engineering and Technology, Ponnal, Telangana, India
7Associate Professor, Department of Mathematics, New Prince Shri Bhavani College of Engineering and Technology, Chennai, Tamil Nadu, India
*Corresponding author. Email: esunilcsm@smec.ac.in
Corresponding Author
Enagandula Sunil
Available Online 23 May 2025.
DOI
10.2991/978-94-6463-718-2_15How to use a DOI?
Keywords
Artificial Intelligence; Supply Chain Management; Predictive Analytics; Blockchain; Big Data; Transparency; Automation; Logistics
Abstract

AI-based supply chain management (SCM) is a game changer enabling logistics optimization, transparency improvement and sustainable trade. Specifically, the research notes that AI guided platforms have the possibility of achieving advanced proactive analytics, assist decisions, and lower the risks throughout the supply chains. We derive four core values (theoretical development and empirical assessment, blockchain, and AI as human collaborators) from synthesizing recent (2020–2024) work on these topics. It showcases how AI can be leveraged for increased resilience and sustainability and efficiency across supply chain. The study also emphasizes the new needs for SCM such as big data analytics, robotic process automation, and smart forecasting. Moving away from typical high-level models that can only offer a general view, these insights will be of value for industry practitioners as well as government policymakers and researchers who also wish for successful implementation of AI for supply chains. We also provide a prospect of future research avenues that would aid in overcoming obstacles both for adoption and in realizing the ultimate potential logistical benefit to the globe from AI.

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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Volume Title
Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
Series
Advances in Computer Science Research
Publication Date
23 May 2025
ISBN
978-94-6463-718-2
ISSN
2352-538X
DOI
10.2991/978-94-6463-718-2_15How to use a DOI?
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.

Cite this article

risenwbib
TY  - CONF
AU  - Srinivasarao Paleti
AU  - Enagandula Sunil
AU  - P. Bhuvaneswari
AU  - Vikrant Sharma
AU  - Kothuri Parashu Ramulu
AU  - F. Anitha Florence Vinola
PY  - 2025
DA  - 2025/05/23
TI  - Artificial Intelligence Augmented Supply Chain Management Platforms for Transparent Logistics Predictive Analytics and Sustainable Trade Ecosystems
BT  - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
PB  - Atlantis Press
SP  - 158
EP  - 169
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-718-2_15
DO  - 10.2991/978-94-6463-718-2_15
ID  - Paleti2025
ER  -