There’s a growing chasm between AI ambition and adoption in the supply chain, according to research sponsored by Kinaxis, a cloud-based software company that provides supply chain management and orchestration solutions.

The findings underscore the need for companies to be strategic about how they use AI to prevent costly failures and deliver measurable value.

The research was done by IDC InfoBrief, which surveyed more than 2,000 supply chain leaders across nine markets. It found that while there is nearly universal AI adoption, over half of those surveyed say the lack of trust in AI-driven decisions is becoming a barrier. Just 12 percent of the respondents has AI planning governance fully embedded within the operations.

The findings also showed high expectations within these companies, with 41 percent expecting autonomous supply chains at scale to be their core operating model within one to two years, even though only one in eight organizations has been fully embedded with AI governance.

“AI adoption isn’t the question anymore. Whether AI delivers trusted decisions, measurable value, and governed autonomy—that’s the question, especially with 52 percent of leaders telling IDC that trust is what’s holding them back,” said Justin King, field chief technology officer at Kinaxis.

“We built Maestro to answer that question. Every AI-driven recommendation is explainable and auditable before it acts, so accountability happens at the decision, not just the policy,” King said, referring to its AI-infused supply chain orchestration platform that combines proprietary technologies and techniques that provide full transparency and agility across the entire supply chain.

Among other key findings, the research also found that only 12 percent of the respondents would consider themselves as AI leaders. The data suggested that the value of AI is yet to be proven for these leaders, 62 percent of whom say better data quality and integration would lead to more investment, while 51 percent want a clear return on investment.

With trust cited as the top barrier to adoption, the solution would require an explainable and auditable AI.

“The next phase of supply chain AI is not simply more adoption. It is accountability—ensuring AI delivers trusted decisions, measurable value, governed autonomy, and operational outcomes,” added Eric Thompson, IDC’s research director, global supply chain planning.