Auditing Smart and Sustainable Supply Chains: The Role of Assurance in AI-Driven Decision Systems

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:This paper contributes to audit theory by extending assurance concepts to AI-driven and sustainability-oriented supply chain contexts.

🏢実務担当者:Corporate sustainability and audit teams can use the framework to design assurance processes for AI-driven supplier evaluation and carbon estimation systems.

🏛政策担当者:Regulators can consider the assurance challenges identified for algorithmic decision systems in sustainability reporting standards.

Artificial intelligence, big data analytics, blockchain-enabled traceability, smart contracts, platform-based coordination, robotic process automation, and real-time digital systems are reshaping the governance architecture of contemporary supply chains. In smart and sustainable supply chain environments, managerial decisions concerning procurement, supplier evaluation, logistics optimization, corporate social responsibility reporting, sustainability reporting, carbon estimation, and risk monitoring are mediated by data-driven and algorithmic systems. This development creates new assurance challenges that extend beyond traditional financial statement auditing. This chapter develops and proposes a Data–Blockchain–Algorithm–Governance Assurance Framework to explain how assurance functions are expanding from transaction verification toward blockchain traceability, algorithmic decision systems, and governance accountability. The framework conceptualizes assurance as a layered structure connecting transaction evidence, blockchain-enabled traceability, AI-related risk assessment, and governance oversight within digitally connected supply chain ecosystems. Its central contribution is to translate traditional audit reasoning into AI-driven and sustainability-oriented environments while introducing concepts such as governance-control deviation, material decision error, and algorithmic assurance. Building on traditional auditing principles, the chapter further distinguishes between the complementary yet distinct assurance roles of blockchain and artificial intelligence. Blockchain technology strengthens traceability, transparency, auditability, and evidential integrity, whereas artificial intelligence raises assurance concerns regarding the reliability, explainability, fairness, and governance of automated decision systems. By integrating corporate social responsibility reporting, sustainability assurance, AI-driven supplier evaluation, and digitally mediated governance into a unified assurance perspective, the chapter positions auditing as an evolving bridge between conventional assurance disciplines and the emerging accountability demands of smart and sustainable supply chains.

• openalex https://doi.org/10.5772/intechopen.1016235first seen 2026-07-15 05:14:00