The study, “Making Supply Chain AI Accountable,” surveyed over 2,000 supply chain leaders across nine countries.
While only 2% of respondents said their supply chains currently lack any AI-enabled capabilities, just 12% classified themselves as AI leaders.
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The research highlights a marked gap between broad AI deployment and effective leadership in the field.
Respondents identified trust in AI-driven decisions as the main barrier to further adoption, with 52% ranking it as a top concern.
Despite the push towards greater autonomy, just 12% of organisations reported having fully embedded governance procedures for integrating AI systems.
According to the research, expectations for rapid advancement persist: only 6% of supply chain leaders report having achieved autonomous supply chains at scale, while 41% expect autonomy to become their core operating model within the next one to two years.
However, the lack of robust governance frameworks raises concerns about an industry increasingly reliant on AI without sufficient accountability, the research indicated.
Furthermore, the study reveals additional concerns among supply chain leaders, with 62% marking better data quality and integration as the factor most likely to accelerate further AI investments. The report found that 51% cited the need for a clear return on investment and measurable time to value.
Accountability for outcomes produced by AI systems is emerging as a primary concern, with 67% of participants indicating that meeting these demands will require the most substantial changes to governance.
Despite anxieties about new technology, most respondents viewed AI as an opportunity rather than a threat, with 79% expecting AI to reshape, rather than reduce, existing supply chain roles.
Kinaxis, whose Maestro platform is designed to address some of these challenges, pointed to explainable, auditable AI as a way to build trust and facilitate better oversight.
Kinaxis field chief technology officer Justin King said: “AI adoption isn’t the question anymore. Whether AI delivers trusted decisions, measurable value, and governed autonomy – that’s the question, especially with 52% of leaders telling IDC that trust is what’s holding them back. 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.”
