Lack of formal AI strategy holds back supply chain gains
Only about one-fourth of supply chain executives have a formal AI strategy in place, according to new research from Gartner. That lack of planning is holding companies back.
Organizations are increasingly adopting AI in supply chain processes, but the lack of a formal AI strategy might be holding back long-term transformational benefits.
A recent report from Gartner indicates that only 23% of around 120 global supply chain leaders surveyed have a defined and documented strategy in place to govern their AI implementations. About 40% of respondents said they have an ad hoc strategy.
The lack of a formal AI strategy could create a dynamic where quick paybacks from AI are overemphasized at the expense of more strategic, long-term value, according to Benjamin Jury, an analyst at Gartner and one of the report authors.
"By doing that, they've placed this artificial ceiling on the value that they can realize from AI at scale, especially if they're narrowing that vision, instead of expanding that out to have both the top line and a bottom-line vision for what AI can do for the supply chain organization and the organization as a whole," Jury said.
Senior leadership is tasking chief supply chain officers (CSCOs) to show quick returns on AI investments, according to the report, with 51% of respondents indicating that they feel intense pressure to implement AI tools into existing supply chain workflows. Further, 59% reported that they are expected to achieve ROI on a supply chain investment within a year of committing resources to it.
Having a formal AI strategy and an understanding of what AI can do for your supply chain helps you have that seat at the table and devise the strategy that then lets you drive transformation at scale within your supply chain.
Benjamin JuryAnalyst, Gartner
"Clearly there's this big push to get that ROI quickly," Jury said.
Focusing primarily on short-term goals such as improving process efficiency or generating cost savings is worthwhile, he said, but AI can be used for strategic initiatives that increase revenue.
"For example, this could be investing in ways to inform new product development efforts by using insights driven from AI to look at customer preferences and trends for product personalization," Jury said.
CSCOs should also use AI as a tool to elevate supply chains as a more strategic part of the organization, he added.
"Having a formal AI strategy and an understanding of what AI can do for your supply chain helps you have that seat at the table and devise the strategy that then lets you drive transformation at scale within your supply chain," Jury said.
Beware of emerging tech hype
The lack of an AI strategy in supply chain is not unlike the path that other recently hyped emerging technologies like IoT or blockchain have traveled down, according to Gaurav Malhotra, a partner at consultancy EY.
The difference, however, is that AI carries much more potential than the others, he said.
"There's more relevance and reality to this technology, but we're in that phase where there is a lot of hype," Malhotra said. "But even with the hype, there's a lot of confidence in the broader market that the opportunity is large, whether that's in supply chains or more broadly."
The hype can hold back AI-focused supply chain transformation because there's a lack of understanding around the technology along with its evolution from machine learning to agentic AI, he added.
"[Supply chain leaders] are pushed by their boards and their C-levels to start something," Malhotra said. "So there are a lot of these smaller pilots and PoCs [proofs of concept] springing up without a coherent strategy or foundation being laid out, and in some cases without a good objective of what's the end in mind."
AI needs a strong foundation
One major component that's missing in AI initiatives now is the foundational work such as governance, security and architecture that can pave the way for AI to revamp how enterprise supply chains run, according to Malhotra.
"You will run around in circles until, and unless, you really have a coherent strategy and all of these foundational elements laid out from an enterprise perspective, which means ownership and drive from the top," he said.
IDC research has found that AI initiatives are being held back by issues beyond strategy and governance, including high implementation costs, integration complexity, shortage of AI talent, lack of trust in AI-generated decisions and resistance to AI adoption from traditional stakeholders, according to Simon Ellis, practice director at IDC.
Plus, vendors such as SAP and O9 Solutions are building governance tools into their AI offerings, he said.
"They won't have to worry so much, because [the AI] will be built into the ways tools work," Ellis said. "However, companies who are attempting to develop the newer flavors -- generative and agentic AI -- themselves do so at their own peril."
All supply chain software vendors have a mandate to include AI in their products, but the real proof of success will only come if customers use the tools, he said.
"Once the system's in place, the people on the factory floor, supply chain planners or warehouse operators don't care," Ellis said. "All they want to know is that this tool helps them do their job, makes them more effective and efficient -- or it doesn't. The system is either easy to use or it isn't."
Ellis agreed that the comparison between the hype cycle for AI in supply chain and former emerging technologies is apt.
"I was always unclear on the way that blockchain was going to transform the supply chain because I didn't see the use cases or killer apps, and it fizzled," he said. "I don't think that's the case for AI because it's much easier to see where these use cases are and where the value is."
Jim O'Donnell is a news director for Informa TechTarget who covers ERP and other enterprise applications.
