At The Toro Company, a Minnesota-based lawn mower manufacturer, supply chain director Kevin Carpenter says he is operating at inventory levels close to those of 2019, a far cry from the overstocking seen after the pandemic. To achieve this, his team relies on generative AI tools that can sort through a massive stream of data, from steel prices to presidential announcements, and recommend when and from whom to buy components.
According to Gartner, global spending on software solutions integrating generative AI for supply chains could reach $55bn by 2029, up from $2.7bn today, driven by economic and geopolitical uncertainty. SAP, Oracle, Coupa, Microsoft, and Blue Yonder (a Panasonic subsidiary) are among the leading sector players.
Consulting firms such as McKinsey and GEP have found that price volatility is driving demand for these technologies. The most advanced systems, known as "AI agents," can continuously analyze customs scenarios, anticipate counterfeit renewals, and propose an action plan, although experts warn against excessive enthusiasm: AI is not a miracle solution.
For groups such as Konecranes, a Finnish manufacturer of port cranes, AI is already optimizing complex tasks such as logistics planning by cross-referencing weather forecasts and transport constraints.
By reducing inventory, companies limit their financing and storage costs while reducing the risk of obsolescence. McKinsey notes that in 2024, only 34% of supply chain executives relied on high inventory levels to protect themselves from disruptions, compared to 60% in 2022.
While AI can increase responsiveness, strategic decisions remain human for now. Kevin Carpenter jokes, "I hope it doesn't take my job before my kids finish college."
