Supply Chain AI Outpaces Governance, IDC Study Finds

"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."

The 52% trust reading places the constraint on the demand side. The technology is installed at nearly every respondent; confidence in what it decides is another matter. IDC conducted the research independently; Kinaxis sponsored it.

Kinaxis (TSX:KXS), which sells supply chain planning and orchestration software, says the findings point to a clear need for explainable, auditable AI. Justin King, field chief technology officer, said the Maestro platform was built around the accountability question. Every AI-driven recommendation is "explainable and auditable before it acts," King said, so "accountability happens at the decision, not just the policy." Kinaxis describes Maestro as combining proprietary technologies for full visibility across the supply chain, covering multi-year strategic planning and last-mile delivery. In practice, recommendations carry a rationale that can be inspected, and the audit trail is set before the system acts.

The accountability question is not confined to supply chains. Who carries responsibility when an autonomous system makes a costly error remains unresolved. Financial services are working through the same issue; there, AI agents act without direct human oversight. AlphaScala's AI rogue agents analysis examines who bears liability when those systems cause a breach.

Kinaxis posted the full InfoBrief on its website. The webinar with Thompson and King follows; registration stays open until the session starts, and those who cannot join live receive the recording afterward.