Agentic AI emerges as a game-changer for resilient supply chains

Supply chain leaders have spent the past few years grappling with geopolitical shocks, sustainability rules and an ever-growing number of decisions needed to keep customers supplied and shareholders satisfied. Forrester says agentic AI may not yet be deployed at scale, but it is already emerging as a tool that could help firms make their networks more resilient, more efficient and easier to manage.

The central appeal is straightforward: supply chain teams are drowning in comple...

xity. Analysts are expected to monitor demand and supply by stock keeping unit and fulfilment point across multiple planning periods, while also juggling more product variants, more sales channels and more service models. As companies expand into direct-to-consumer, long-tail and product-as-a-service offerings, the number of SKU-location combinations can quickly outstrip human capacity. Forrester warns that firms that do not use agents to help scale analysis risk both stock shortages that disappoint customers and excess inventory that drags on returns.

The technology’s value is not limited to forecasting. Forrester also points to routine logistics work, where finding extra transport capacity or alternative routes can consume large amounts of time. Logistics Management’s DispatchTrack benchmark survey has found that a typical dispatcher in an enterprise transportation office may make between 120 and 200 calls in an eight-hour shift. Agentic tools, the consultancy argues, could take on parts of that workload by searching options, negotiating rates and helping logistics teams respond more quickly when disruption hits.

Documentation is another area where automation may have an immediate impact. Modern supply chains generate a stream of paperwork, including purchase orders, acknowledgements, advanced shipping notices and bills of lading. That burden is growing as customers demand more transparency over carbon footprints and as regulators push for deeper multi-tier supply chain visibility. Forrester notes that missing or mismatched data can delay customs clearance or invoice payment, making document validation and reconciliation a natural fit for AI agents.

The consultancy cites live examples from large industrial and logistics groups. Maersk is using AI agents to streamline documentation and supplier interactions, while Schneider Electric is applying them to document checks and sustainability tracking. Those cases suggest the technology is moving beyond theory, even if most deployments remain at an early stage.

Other industry voices are making similar arguments. A Forbes Council article published in April said the return on investment from agentic AI is already becoming visible in areas such as procurement compliance, inventory turnover and real-time spend visibility. IBM has also described a shift from reactive to proactive resilience, saying nearly 70% of COOs and chief supply chain officers consider agentic AI market-ready. Genpact, meanwhile, has argued that the next challenge is scaling beyond pilots so that firms can respond faster to disruption and manage increasingly complex product portfolios.

Forrester’s broader warning is that enthusiasm for automation can easily outpace governance. It argues that rules-based systems such as robotic process automation have already helped companies like Siemens improve supply chain performance, but they can also harden existing processes and make organisations less adaptable to new sales channels or service models. Agentic AI, by contrast, requires security, authorisation and oversight frameworks that assume software may act dynamically and pursue goals in ways that are not fully predictable.

That is why Forrester recommends a dedicated guardrails approach for agentic systems, along with tighter cost controls as agent usage grows. It also argues that companies need a semantic model spanning procurement, enterprise resource planning, payments and partner systems if agents are to make reliable decisions. High-quality metadata layers, including knowledge graphs, are becoming increasingly important for giving AI the business context it needs to act accurately.

In Forrester’s view, the opportunity is not simply to automate existing supply chain work, but to redesign how decisions are made across the network. If companies can build the right data foundations, security controls and operating rules, agentic AI could become a practical lever for managing volatility rather than just another layer of automation.

Source: Noah Wire Services