Human-AI Collaboration in Supply Chain Industry 5.0 to Build a Human-Centered Autonomous Ecosystem

The emergence of Industry 5.0 has shifted supply chain management from full automation toward a human-Al collaborative ecosystem, where artificial intelligence (AI) enhances efficiency while retaining human decision-making and ethical considerations. This study explores the incorporation of AI-powered decision-making, autonomous systems, and sustainability strategies in modern supply chains, emphasizing their impact on efficiency, resilience, and transparency. The research highlights how Al-powered predictive analytics, real-time inventory management, and automated logistics optimize supply chain performance, reducing operational costs and minimizing waste. Case studies from Amazon, JD Logistics, and Siemens demonstrate how AI-powered solutions improve predictive demand analysis, optimize routing, and circular economy practices, leading to more sustainable and agile supply chains. Furthermore, autonomous systems, such as self-driving freight vehicles and robotic fulfillment centers, significantly improve speed and accuracy in global supply networks. Despite its advantages, Al adoption in supply chains presents challenges, including substantial implementation costs, cybersecurity threats, and workforce adaptation challenges, and ethical concerns related to automation. The study underscores the necessity of a human-centric approach, ensuring that AI enhances human expertise rather than substituting it. Organizations must prioritize Al transparency, ethical governance, and digital upskilling programs to maximize AI's potential in next-generation Industry 5.0 supply networks. This research concludes the successful integration of AI in managing supply chains will drive the next generation of self-optimizing, sustainable, and resilient supply networks. Future research should examine AI's long-term socioeconomic effects, its integration with blockchain and IoT, and the development of AI ethics in decision-making.