Artificial intelligence and blockchain implementation in supply chains: a pathway to sustainability and data monetisation?

TLDR

Digitalisation is expected to transform end‑to‑end supply‑chain operations through advanced technologies, yet the combined impact of these digital tools remains under‑explored due to limited real‑world evidence. This study investigates how jointly deploying Artificial Intelligence and Blockchain Technology can extend supply‑chain performance, promote sustainability, and enable data monetisation, using the Thai tuna fish supply chain as a case. The authors mapped business processes and system interactions to identify material and data flows, then proposed a unified framework outlining key data elements for AI and BCT‑enabled food supply chains to deliver value. Mapping revealed that AI and BCT play central roles in digital supply‑chain management, with sustainability and data‑monetisation outcomes contingent on stakeholder‑defined parameters, and the modelling approach is expected to aid decision‑making for sustainable digital interventions.

Abstract

Abstract Digitalisation is expected to transform end-to-end supply chain operations by leveraging the technical capabilities of advanced technology applications. Notwithstanding the operations-wise merits associated with the implementation of digital technologies, individually, their combined effect has been overlooked owing to limited real-world evidence. In this regard, this research explores the joint implementation of Artificial Intelligence (AI) and Blockchain Technology (BCT) in supply chains for extending operations performance boundaries and fostering sustainable development and data monetisation. Specifically, this study empirically studied the tuna fish supply chain in Thailand to identify respective end-to-end operations, observe material and data-handling processes, and envision the implementation of AI and BCT. Therefore, we first mapped the business processes and the system-level interactions to understand the governing material, data, and information flows that could be facilitated through the combined implementation of AI and BCT in the respective supply chain. The mapping results illustrate the central role of AI and BCT in digital supply chains’ management, while the associated sustainability and data monetisation impact depends on the parameters and objectives set by the involved system stakeholders. Afterwards, we proposed a unified framework that captures the key data elements that need to be digitally handled in AI and BCT enabled food supply chains for driving value delivery. Overall, the empirically-driven modelling approach is anticipated to support academics and practitioners’ decision-making in studying and introducing digital interventions toward sustainability and data monetisation.