Does Your Company Have a Formal AI Strategy for Supply Chain?

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Artificial intelligence (AI) is a powerful tool with roots dating back to the 1950s (or much earlier than that, depending on whom you ask), but its widespread integration into mainstream business operations is still relatively new. This is particularly true for supply chains, where the technology holds true promise—yet most companies continue to approach AI adoption with individual projects rather than a unified strategy.

 This approach isn’t unusual in a rapidly-advancing technology landscape, where new innovations, tools, applications and programs are proliferating at a high rate of speed. Sitting down and coming up with a formal approach for every single one of them is simply not feasible.

However, a scattershot approach to significant technological shifts, like the rise of AI, can prevent companies from realizing the full, transformative potential of these tools. In absence of a cohesive plan, organizations may wind up with siloed systems, inefficient deployments and a missed opportunity to truly leverage the technology for strategic advantage. It can also limit the full impact of AI within an organization.

A new Gartner, Inc. survey highlights this issue at a time when supply chain leaders are using more and more AI in their operations. The survey found that just 23% of them have a formal AI strategy in place. For now, at least, the focus seems to be more on short-term gains versus long-term, transformative change enabled by artificial intelligence.

Under Pressure

Gartner surveyed 120 supply chain leaders who had deployed AI in their organizations between December 2024 and January 2025. An analysis of the survey data revealed multiple disconnects between AI expectations and reality within the supply chain function. Under pressure to demonstrate near-term return on investment (ROI), for example, chief supply chain officers (CSCOs) may be jeopardizing the full potential for long-term AI transformation within their functions.

“CSCOs feel pressure to achieve short-term ROI from their AI investments, but they must ensure these quick wins don’t create future constraints,” says Benjamin Jury, senior principal, research in Gartner’s Supply Chain Practice. Without a structured approach, organizations risk creating inefficient systems that struggle to scale and adapt to evolving business demands."

When companies take a “project-by-project” AI investment approach, it can lead to inefficient "frankensystems,” or complex, layered architectures that hinder scalability and extend the payback period for AI transformations. The same thing happens when organizations use myriad, disparate software systems—none of which “talk” to each other—to run different aspects of their operations.

“While the immediate gratification of short-term ROI may seem appealing,” Gartner says, “it frequently leads to marginal long-term gains and a fragile technical infrastructure.”

3 Ways to Think Beyond Bottom-Line Metrics

The survey also found that most supply chain leaders use bottom-line metrics (i.e., efficiency, decision-making speed and cost) to gauge the success of their AI investments, ranking these factors far ahead of measures such as increasing revenue and innovation. “This suggests that CSCOs currently see AI primarily as an efficiency and cost-savings tool,” Gartner says, “rather than a truly transformative technology that can drive innovation and new business models.”

To get more out of their AI investments, Gartner tells supply chain leaders to develop AI portfolios that balance immediate returns with long-term, transformative goals. Go beyond the project-by-project method, it adds, and use a strategic approach that includes these three principles:

1. Develop a formal supply chain AI strategy. Establish a defined and documented AI strategy that outlines both short- and long-term objectives, what success looks like, and what needs to be done (and by when) to achieve that success. 
   
   
2. Adopt the “run-grow-transform” framework. Build an AI investment portfolio that includes “run,” “grow” and “transform” projects to strategically allocate resources and deliver immediate operational efficiencies, as well as mid- to long-term benefits. 
   
   
3. Invest in AI-ready infrastructure. Ensure scalability and adaptability to meet evolving business demands, in collaboration with the CIO and other executive leaders.