Towards Trustworthy AI in Demand Planning: Defining Explainability for Supply Chain Management

Ruiqi Zhu, Cecilie Christensen, Bahram Zarrin, Per Bækgaard, Tommy Sonne Alstrøm

2025

Abstract

Artificial intelligence is increasingly essential in supply chain management, where machine learning models improve demand forecasting accuracy. However, as AI usage expands, so does the complexity and opacity of predictive models. Given the significant impact on operations, it is crucial for demand planners to trust these forecasts and the decisions derived from them, highlighting the need for explainability. This paper reviews prominent definitions of explainability in AI and proposes a tailored definition of explainability for supply chain management. By using a user-centric approach, we address the practical needs of definitions of explainability for non-technical users. This domain-specific definition aims to support the future development of interpretable AI models that enhance user trust and usability in demand planning tools.

Paper Citation

in Harvard Style

Zhu R., Christensen C., Zarrin B., Bækgaard P. and Alstrøm T. (2025). Towards Trustworthy AI in Demand Planning: Defining Explainability for Supply Chain Management. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 1245-1253. DOI: 10.5220/0013315900003890

in Bibtex Style

@conference{icaart25,
author={Ruiqi Zhu and Cecilie Christensen and Bahram Zarrin and Per Bækgaard and Tommy Alstrøm},
title={Towards Trustworthy AI in Demand Planning: Defining Explainability for Supply Chain Management},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2025},
pages={1245-1253},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013315900003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Towards Trustworthy AI in Demand Planning: Defining Explainability for Supply Chain Management
SN - 978-989-758-737-5
AU - Zhu R.
AU - Christensen C.
AU - Zarrin B.
AU - Bækgaard P.
AU - Alstrøm T.
PY - 2025
SP - 1245
EP - 1253
DO - 10.5220/0013315900003890
PB - SciTePress