Kinaxis has highlighted a widening gap between supply chain companies’ enthusiasm for artificial intelligence and their ability to govern it safely, after new independent research found that only a small minority have embedded the controls needed to support autonomous decision-making at scale.
The IDC infobrief, titled “Making Supply Chain AI Accountable” and sponsored by Kinaxis, surveyed more than 2,000 supply chain leaders across nine global markets. It found t...
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hat AI is now close to ubiquitous in the sector, with only 2% of respondents saying they have no AI-enabled capabilities at all. Yet just 12% described themselves as AI leaders, while more than half said trust in AI-driven decisions remains a major obstacle to faster adoption.
The study suggests that the pressure to automate is rising quickly. Only 6% of respondents said their supply chains are autonomous at scale today, but 41% expect that to become their core operating model within one to two years. That ambition appears to be running ahead of internal readiness, with just 12% saying AI planning governance is fully embedded in their operations.
The findings echo earlier Kinaxis-commissioned research with Economist Impact, which showed that 71% of global businesses had accelerated AI adoption in response to tariffs, inflation and geopolitical uncertainty. That study also found that while 97% of companies were experimenting with AI, only 20% could make real-time decisions and just 22% had a defined AI strategy.
Taken together, the reports point to a sector under intense pressure to move faster, but still struggling with the basics of execution. Kinaxis has been positioning its own supply chain orchestration platform, Maestro, around the promise of greater transparency and agility, and the latest research reinforces the company’s broader argument that AI investment needs to be matched by governance, accountability and clear business outcomes.
The issue is not only technical but organisational. Academic work on algorithmic supply chains has also stressed that responsibility is often spread across multiple actors, making it harder to assign accountability when automated systems fail or produce poor decisions. In practice, that means companies may be adopting AI tools more quickly than they can define who is responsible for the data, the decisions and the consequences.
For supply chain leaders, the message from the new IDC research is blunt: enthusiasm for autonomous systems is rising, but trust, governance and operational discipline are still lagging well behind.
Source: Noah Wire Services
