Blockchain-Enabled Trust Formation in AI-Driven Inter-Firm Capacity Sharing Ecosystems

Abstract

Inter-firm capacity sharing has emerged as a strategic instrument for coping with demand volatility, asset underutilization, and supply chain disruptions, yet its widespread adoption remains constrained by deficits in trust, information asymmetry, and coordination complexity. This paper investigates the architectural convergence of artificial intelligence and blockchain technologies as a mechanism to engineer trust in decentralized capacity sharing ecosystems. By analyzing system-level interactions, we demonstrate that AI-driven predictive and prescriptive models can significantly enhance the efficiency of capacity allocation, while blockchain-based distributed ledger technology provides an immutable, transparent substrate for recording commitments, executing smart contracts, and maintaining verifiable reputation trails without central intermediaries. The discussion is framed around structural trade-offs that arise when integrating these two computational paradigms: the tension between algorithmic opacity and ledger transparency, the scalability limits of consensus protocols in high-frequency capacity markets, and the governance challenges of embedding algorithmic decision rights into autonomous smart contracts. We further interrogate fairness considerations, including how access to AI-derived optimization and blockchain-anchored identity can asymmetrically benefit incumbent firms, and propose a layered architecture that decouples trust computation from capacity execution. Policy implications related to cross-border capacity pooling, data sovereignty, and the regulatory treatment of algorithmically managed capacity consortia are examined. The paper concludes that a carefully orchestrated fusion of AI and blockchain can transform inter-firm capacity sharing from a relationship-intensive, fragile practice into a resilient, semi-automated industrial infrastructure capable of underpinning sustainable supply networks.