Industry experts highlight how Agentic AI is transforming supply chain management from passive analytics to active, real-time decision-making, boosting resilience and cost savings amid global disruptions.
Agentic AI is emerging as a transformative force in enhancing the agility and resilience of supply chains, according to industry experts Manik Sharma of Celonis and Pushpinder Singh of IBM Consulting. Speaking during a recent Webinar Wednesday, they underscored the urgent need for organisations to become more responsive amidst increasing global supply chain disruptions. Their insights reflect a broader industry shift towards intelligent, autonomous systems that not only generate insights but also automate actions to accelerate decision-making processes.
Pushpinder Singh observed a notable change in how companies leverage AI—from simple forecasting and insight generation to using AI agents actively managing supply chain elements such as rerouting shipments, adjusting inventory levels, and negotiating with suppliers. This shift is driven by the complexities and vulnerabilities of today’s interconnected supply chains, where disruptions at critical nodes, such as semiconductor production hubs in Taiwan or key maritime passages like the Red Sea, can trigger cascading effects globally.
The financial impact of these technologies is significant. Singh cited that over the past two years, AI deployment has saved organisations around £3 billion in costs. Manik Sharma pointed out that Agentic AI extends well beyond chatbots, serving as a crucial tool to manage modern supply chain complexity and respond swiftly to global turmoil.
One of the core capabilities enabled by Agentic AI is fostering supply chain resilience through enhanced end-to-end visibility and scenario simulation. According to Singh, resilience cannot be achieved merely by cutting costs—it requires a diversified supply chain strategy combined with the capacity to predict and simulate various disruption outcomes before decisions are executed. Sharma emphasised leveraging existing IT investments augmented by Agentic AI overlays, which can integrate disparate data sources and systems without requiring costly replacements.
The traditional monthly cadence of sales and operations planning (S&OP) is no longer sufficient given the rapid pace of change and frequent disruptions. Real-time or near-real-time decision-making is becoming imperative, with executives increasingly making strategic supply chain decisions outside the confines of formal meetings. Insights from research by Supply Chain Media reveal business strategy as the leading driver for transformation projects, reflecting a strategic rather than purely financial risk-oriented mindset. However, maintaining financial performance remains critical for the sustainability of such initiatives.
Despite the popularity of supply chain control towers, Sharma noted that many organisations treat these as advanced dashboards rather than action-driven tools. This gap can be bridged by Agentic AI, which, when combined with generative AI capabilities and comprehensive data integration, facilitates intelligent, self-healing, and potentially fully autonomous supply chains. Celonis has developed a platform that supports this approach by creating a contextual digital twin of the supply chain, incorporating both physical flow data and procedural aspects like customs and paperwork. This context-rich environment enables AI agents to assess disruption impacts accurately and propose or autonomously enact mitigation strategies.
The pace of AI adoption is accelerating beyond traditional forecasts like Gartner’s hype cycle, which predicted a decade before full productivity is realised. Singh insists that the rapid uptake of technologies such as ChatGPT foreshadows faster adoption of Agentic AI within supply chains.
Other industry players are also innovating in this space. Resilinc has introduced an Agentic AI platform built on Microsoft Azure, designed to predict disruptions, automate compliance, and facilitate real-time risk response. Their platform leverages AI agents tailored to specific industry needs, enabling multi-tier supply chain mapping and proactive scenario planning. This represents a significant advancement in transforming conventional risk management approaches into autonomous, self-healing systems.
Similarly, IBM’s detailed reports describe how Agentic AI enables supply chains to become autonomous, adaptive, and resilient. The model enhances forecasting accuracy, increases ecosystem-wide visibility, and integrates seamlessly with legacy analytics tools, boosting operational resilience both within organisations and across supply chain partners.
Consultancies like EY highlight how Agentic AI revolutionises supply chains by enabling autonomous decision-making and realtime adaptations, improving demand forecasting, predictive maintenance, and strategic risk management. Technology providers also focus on applications such as dynamic contract negotiation, risk-aware rebalancing, spend optimisation, and self-driving logistics—further illustrating the broad scope of Agentic AI’s disruptive potential.
In summary, Agentic AI is shaping the future of supply chain management by transforming passive analytics into proactive, real-time orchestration. This shift promises not only to enhance efficiency and cost savings but also to build supply chains that are resilient and responsive in a volatile global environment. As adoption accelerates, organisations embracing these technologies are likely to gain a competitive edge through smarter, more autonomous operations that can withstand and quickly recover from disruptions.
Source: Noah Wire Services
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