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Artificial Intelligence in Supply Chain Finance: Insights from Industry 5.0 through a Systematic Review

Introduction

The transformation from Industry 4.0 to Industry 5.0 marks a critical shift in the global industrial paradigm, emphasizing not just technological innovation but also human-centric values, sustainability, and resilience. While Industry 4.0 focused on automation, cyber-physical systems, and digital connectivity, Industry 5.0 brings humans back into the loop, promoting collaborative intelligence between humans and machines. Within this context, artificial intelligence (AI) emerges as a central enabler, capable of optimizing processes, enabling mass personalization, and improving sustainability. One of the emerging areas where AI is expected to make a significant impact is Supply Chain Finance (SCF)—a strategic function that manages financial flows in supply chains to enhance liquidity, reduce risk, and strengthen supplier relationships. However, the integration of AI into SCF, particularly under the principles of Industry 5.0, remains a relatively underexplored but promising research frontier.


The Evolution of Supply Chain Finance in the Digital Era

Supply Chain Finance traditionally involves various practices such as reverse factoring, dynamic discounting, and invoice financing, all designed to optimize working capital and improve financial health across the supply chain. With digital transformation accelerating, SCF has evolved from being a transactional function to a more integrated and strategic operation. Digital tools now enable real-time visibility into cash flows and transactions, enhancing transparency and decision-making. However, the application of AI in SCF extends these capabilities even further by enabling predictive analytics, intelligent risk assessment, and real-time financial optimization.

Artificial Intelligence as a Catalyst in SCF

Artificial intelligence introduces a set of advanced capabilities that are particularly well-suited to the complex, data-intensive environment of supply chain finance. Machine learning algorithms can process historical and real-time data to predict payment behaviors, assess credit risk, and forecast liquidity needs. Natural language processing (NLP) allows for the automation of document processing and compliance monitoring, reducing administrative burdens and minimizing errors. Furthermore, AI-driven chatbots and decision-support systems can assist finance professionals in making informed decisions based on dynamic market conditions. These capabilities are especially relevant under Industry 5.0, which emphasizes responsive, personalized, and resilient financial operations.

Synergy Between AI and Human Decision-Making in Industry 5.0

A hallmark of Industry 5.0 is the emphasis on human-AI collaboration. In SCF, this means that AI systems do not replace human finance managers but augment their decision-making abilities. For instance, AI can generate risk profiles and suggest optimal financing structures, but the final judgment remains with human experts who can weigh contextual and ethical considerations. This synergy allows for more adaptive, empathetic, and strategically sound financial decisions—qualities that are increasingly necessary in today’s volatile global markets.

Sustainability and Resilience through AI-Enabled SCF

Another major focus of Industry 5.0 is sustainability. AI can significantly contribute to sustainable supply chain finance (SSCF) by helping firms evaluate the environmental and social risks associated with their suppliers and financing decisions. For example, machine learning models can analyze ESG (Environmental, Social, and Governance) data to inform lending policies and prioritize financing for suppliers that meet specific sustainability criteria. Additionally, AI can improve supply chain resilience by forecasting disruptions, identifying vulnerable partners, and dynamically reallocating financial resources to ensure continuity.

Challenges and Gaps in Current Research

Despite its potential, the integration of AI into SCF under the Industry 5.0 framework faces several challenges. These include data privacy concerns, limited access to high-quality financial and supply chain data, regulatory hurdles, and the need for cross-functional collaboration between finance, IT, and operations. The academic literature remains fragmented, with only a limited number of studies addressing the intersection of AI, SCF, and Industry 5.0. There is a need for more empirical research, cross-sectoral case studies, and frameworks that explore how AI can be effectively deployed to optimize SCF processes in real-world settings.

Conclusion and Future Directions

The convergence of artificial intelligence, supply chain finance, and Industry 5.0 presents a transformative opportunity for businesses seeking to enhance operational efficiency, financial agility, and sustainability. As industries shift toward more human-centric and intelligent systems, AI-enabled SCF has the potential to become a cornerstone of future-ready supply chain strategies. However, this potential can only be realized through further research, investment in digital infrastructure, and the cultivation of interdisciplinary expertise. Future studies should explore how AI tools can be designed to align with human values, ethical standards, and the broader goals of sustainable industrial development.

#Industry5_0 #ArtificialIntelligence #SupplyChainFinance #SCF #AIinSCF #SustainableFinance #SmartManufacturing #DigitalTransformation #IndustryEvolution #SystematicReview #PRISMA #SupplyChainInnovation #AIinIndustry #FutureOfIndustry #AIIntegration

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