55% of Supply Chain Chiefs Cannot Quantify AI Returns, Gartner Finds
Executives at organizations with revenues over $250 million struggle to measure the economic value of AI spending.
Corporate leaders are aggressively integrating artificial intelligence into their logistics networks, but many cannot prove the technology is paying off. A new survey from Gartner Inc. reveals a significant gap between the financial commitments made to AI and the ability of executives to measure the resulting economic impact.
According to the Gartner data, 55% of chief supply chain officers (CSCOs) polled are unclear on the return on investment (ROI) of their AI expenditures. The survey specifically targeted supply chain professionals from large-scale organizations with annual revenues of at least $250 million, indicating that even the most resource-rich enterprises are struggling to track the value delivered by these tools.
The Speed of Adoption
The supply chain sector has moved rapidly to integrate various forms of AI, including generative and agentic systems, as a means to optimize logistics and manage global disruptions. This rush has seen many leaders planning to implement generative AI within the coming year. However, the pace of technical adoption has fundamentally outpaced the development of formal corporate strategies and the measurement frameworks required to track financial performance.
The Risk of an AI Bubble
This disconnect suggests that corporate spending may be driven more by a fear of missing out (FOMO) than by proven efficiency gains. When large-scale enterprises fail to demonstrate tangible ROI, it creates the risk of an "AI bubble." If the gap between spending and measurable value persists, the industry may face a sharp correction in AI investment. Such a shift would likely move the market away from general-purpose tools and toward more specialized, narrow AI applications that offer clearer, more immediate utility.
Future Outlook
As organizations move forward, the focus is expected to shift from mere implementation to rigorous validation. The industry must now determine whether the current lack of clarity is a temporary growing pain of a new technology or a sign that the promised efficiencies of AI in supply chain management are overhyped. For now, the ability to quantify value remains the primary hurdle for CSCOs attempting to justify continued high-level spending.