From Reporting to Transformation: A Review of AI Tools Enabling Sustainability Governance Across Multi-Tier Supply Chains

Authors

Petr Procházka
Prague University of Economics and Business, Faculty of International Relations
https://orcid.org/0000-0002-8886-6241
Emil Velinov
Newton University
https://orcid.org/0000-0001-6073-1196
Paul Lacourbe
Prague University of Economics and Business, Faculty of International Relations,
https://orcid.org/0009-0004-2481-468X

Synopsis

This paper deals with the topic of artificial intelligence tools that have the capacity to assist with sustainability governance in multi-tier supply chains. These tools in the sustainability sector in general are meant to cut costs and enable small and medium enterprises and lower-tier suppliers to get access to best practices, streamline their sustainability efforts, and create universally comparable outputs. The added value of our research is to categorize existing tools, to identify potential gaps, and to enable users to understand the tools with the highest impact. We collect available solutions by a combination of desk research and interviews of industry experts from various levels of supply chain. We evaluate them by their capability to overcome five main challenges – data beyond simple reporting and manual collection, reach beyond Tier 1 suppliers, usability by small enterprises, involvement of artificial intelligence, and tools having an accessible cost. Having such an overview will assist low-key users with less resources to easily tap on existing solutions without large barriers.

Author Biographies

Petr Procházka, Prague University of Economics and Business, Faculty of International Relations

Petr Procházka is a postdoc researcher in the area of sustainability transformation, sustainability governance within value chains and cost/risk optimization. His usual settings of data collection are enterprises in logistics or automotive sectors. He lectures at the Prague University of Economics and Business and has more than 10 years of professional experience at various supply chains levels of logistics in Czechia, Spain and Belgium. He was a visiting researcher at Rotterdam School of Management, worked at EFRAG and currently holds a position of ESG Specialist in a Belgian MNE.

Prague, Czechia. E-mail:petr.prochazka@vse.cz

Emil Velinov, Newton University

Emil Velinov is an Associate Professor in International Management. He lectures at the University of Chemistry and Technology in Prague, RISEBA, EM Normandie Business School in Ireland. His research area is international management, intercultural differences, leadership and board governance or sustainability. He also serves as the Academic Director of the Executive MBA Program at Newton University in Prague. 

Prague, Czechia. E-mail: velinov.emil@gmail.com 

Paul Lacourbe, Prague University of Economics and Business, Faculty of International Relations,

Paul Lacourbe is a researcher and lecturer from Prague University of Economics and Business specializing in sustainable business transformation, circular economy, and responsible innovation. His work focuses on how organizations integrate sustainability principles into strategy, governance, and operational models, particularly in industrial and supply chain contexts. Paul combines conceptual development with applied research, often working with companies and institutions to bridge theory and practice.

Prague, Czechia. E-mail: paul.lacourbe@vse.cz

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Published

July 3, 2026

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Procházka, P., Velinov, E., & Lacourbe, P. (2026). From Reporting to Transformation: A Review of AI Tools Enabling Sustainability Governance Across Multi-Tier Supply Chains. In J. Belak & S. Oberman Peterka (Eds.), Sustainable Governance in the Age of Artificial Intelligence: Interdisciplinary Perspectives on ESG, Digital Transformation and Corporate Responsibility (pp. 169-184). University of Maribor Press. https://doi.org/10.18690/um.epf.7.2026.10