A Hybrid Framework for Retail and Paint Manufacturing
Keywords:
Agentic Artificial Intelligence, Supply Chain Resilience Management, Hybrid Agentic AI Framework, Resilience Engineering, Adaptive Decision-Making Systems, Autonomous Problem Solving, Collaborative AI Agents, Demand–Supply Network Optimization, Disruption Risk Mitigation, Inventory Cost Optimization, Stockout Reduction, Service Level Optimization, Semi-Structured Decision Support, AI Safety and Accountability, Human–Agent Collaboration, Resilience Strength Metrics, Intelligent Supply Chain Systems, Proactive Disruption Management, Multi-Agent Orchestration.Abstract
Disruptions in supply chains cause severe financial losses, necessitating exploration of Agentic AI solutions for Supply Chain Resilience Management. Agentic AI differs from traditional automation, offering innate problem-solving, adaptive-learning, and collaborative capabilities. Enabling Agentic capabilities in supply chain systems can enhance Resilience Strength by supporting accurate decision-making and expanding the range of explored solutions. Concerns regarding safety, accountability, and over-trust in Agentic systems need to be addressed. A Hybrid Agentic AI-Driven Resilience Engineering Framework comprises a central technology area for Resilience Strength and several application areas for demand and supply networks. Scenarios for Retail and Paint Manufacturing demonstrate expected contributions in terms of inventory cost, stockout level, and service level performance indicators.
Supply chain disruptions incur significant financial losses. Agentic Artificial Intelligence—AI with intrinsic problem-solving, adaptive-learning, and collaborative abilities—has been highlighted as a possible contributor to Supply Chain Resilience Strength. Concerns over Agentic features such as safety, accountability, and over-trust require exploration. Enabling Agentic capabilities in supply chain systems can improve Resilience Strength by facilitating precise decision-making while broadening the spectrum of potential solutions. Agentic AI departs from conventional automation by providing appropriate support for semi-structured decision environments. Supply Chain Resilience Management based on Agentic AI can leverage these features to preemptively mitigate novice-level disruption risk, fortifying the system’s ability to absorb, respond, and recover from a wider array of causes and types of disruption.
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