More than half (55%) of chief supply chain officers cannot clearly measure the return on their AI investments, according to a survey by Gartner, Inc. That gap matters because 67% of supply chain digital investments now go to AI, putting the largest share of technology budgets into projects whose payoff is unclear.
Gartner surveyed 394 supply chain professionals at organizations with annual revenue of at least $250 million between November 2025 and February 2026 to determine how digital investments are allocated. A separate survey of 135 senior supply chain leaders, conducted from January through April 2026, documented AI use cases and their return on investment.
"Organizations are getting better at executing change for individual initiatives," said Lorraine Gavin, Senior Principal Analyst in Gartner's Supply Chain practice. "The bigger challenge today is deciding where to invest limited change management resources so that they support the business outcomes that matter most. AI is making that decision more important than ever."
The gap between AI budgets and measured returns
The survey numbers point to a widening gap between spending and measurement. Most supply chain digital budgets now flow to AI, yet a majority of chief supply chain officers say they lack a clear view of what that spending returns.
AI use cases are multiplying faster than organizations can develop effective change management approaches to support them, Gartner found, which makes it harder to connect individual AI projects to measurable results.
Change strategy vs. change methodology
Gartner distinguishes between change methodologies and change strategy. Methodologies provide the steps and activities used to execute change for individual initiatives. A change strategy, by contrast, establishes how finite change management resources are allocated across AI initiatives to achieve broader supply chain and enterprise objectives.
The distinction matters because change management resources are limited, and spreading them evenly across every initiative dilutes their effect. CSCOs should establish an AI change strategy that links change investments to business outcomes and protects AI investments from fragmented adoption, Gartner said.
Allocating limited change resources well requires people across the supply chain who understand what AI can and cannot do. Supply chain teams can build that understanding through the AI Learning Path for Supply Chain Managers.
Why this matters for Executives and Strategy
For executives, the Gartner findings turn AI from a technology decision into a capital allocation decision. When a majority of technology spending cannot be traced to a clear return, the risk is wasted investment and slower adoption among teams that doubt whether AI projects are worth the disruption.
Gartner's analysis points to a specific fix: not more change management activities, but a strategy for where to deploy change resources so they directly support the business outcomes the organization is trying to reach. Executives who frame AI adoption as a portfolio of investments with defined outcomes, rather than a collection of pilots, give supply chain leaders room to prioritize projects that support the strategy.
For ongoing coverage of how executives and strategy leaders are handling these questions, see AI for Executives & Strategy.
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