What if you had an assistant who continuously provided recommendations for optimizing your supply chain operations, then immediately implemented them upon your authorization? Would that assistant be even more valuable if they knew when they didn’t need to ask, but instead took immediate actions without your intervention?

Of course, no such person exists, but artificial intelligence-enabled digital twin (DT) technology has advanced to the point where this “super assistant” scenario no longer has to be just a dream. 

We sat down with RELEX experts Max Forsius, Product Director, and Rich Kurhajetz, Senior Strategist, to explore what agentic AI is, how it works in practice, and how businesses can successfully implement it. 

What is agentic AI? 

Max: AI agents are small autonomous entities that act, adapt, and collaborate with superhuman efficiency. Within a system, they can operate individually or as a network of decision-makers. You give them an objective, and they continually diagnose, optimize, and perform tasks to solve complex problems and achieve that objective. They can be triggered by data systems and, in the future, by other agents.  

This year’s report breaks down key trends and hard truths facing supply chain teams: Why visibility gaps are still slowing recovery, how supplier diversification improves resilience, the role tech stacks play in moving faster and what top-performing teams are doing differently.

See how your strategy compares—and where there’s room to improve.

Prior to the imposition of trade tariffs by the United States in April 2025, retailers already knew that they had a lot of work to do to enable an agile response to sudden changes in either supply or demand.  

Now, in the face of new pressures in the global supply chain, it is more important than ever for retailers to use modeling techniques to better anticipate disruptions and potential corrective actions, to monitor the flow of goods at a more granular level, and to respond quickly to exception conditions when they inevitably occur.

With today’s volatile trade landscape and unpredictable global supply chain disruptions, e-commerce retailers can’t risk alienating customers — or leaking profits — through stockouts. Yet overselling remains a serious problem, with 40 percent of sellers cancelling one in 10 orders and the cost of out-of-stocks estimated at $ 1.2 trillion in 2024.

Overselling occurs when demand exceeds available inventory, leaving consumers facing the dreaded “out of stock” notification after being charged for an item. As a result, overselling erodes consumer confidence, creating serious brand reputation and bottom-line issues for e-commerce retailers as consumers abandon their purchases, turn to competitors, and potentially share negative reviews. Notably, nearly 70 percent of shoppers claim their perception of a business is damaged when an item is out of stock after being told it was available online.

Detailed digital simulations could help to model supply chains and offset risks, easing supply chain challenges. But there are high barriers to widespread adoption.Supply chains are the central nervous system of the global economy, facilitating the movement of billions of dollars in trade every day. But as the past few years have shown, disruptions are hard to predict. 

As companies look for ways to offset these risks, attention has turned to so-called digital twins. These detailed simulations of real-world objects, systems or processes are built with real-time data and provide snapshots that can help firms to monitor threats, test different scenarios and improve decision-making. 

Bamboo Rose and The Interline are proud to present the second annual survey research report, The State of Retail Supply Chains & Sourcing Strategies in 2025. Building on last year’s insights, this in-depth report provides unparalleled analysis of the evolving landscape of global retail supply chains and sourcing strategies, offering a clear view of the priorities, challenges, and opportunities shaping the industry.

Effective lead time management is a critical factor in securing supply chain efficiency and cost control, since lead time represents the total time required for a product or material to move through the supply chain, as measured from the time of ordering to the time of delivery.

Lead time typically encompasses various supply chain stages, including order processing, manufacturing, transportation, and delivery. It can be scrutinised at a high level, by looking at overall supply chain lead time, or with more granularity by zooming in to elements such as supplier lead time and customer-order lead time.