Kinaxis-Sponsored Study Identifies Supply Chain AI Accountability Gap Amidst Rapid Adoption Expectations

Trust, measurable outcomes, and governance lag, even as 41% expect autonomous-at-scale operations within two years

OTTAWA, Ontario--(BUSINESS WIRE)--Kinaxis^® (TSX:KXS), a global leader in supply chain orchestration, today announced the findings of new independent research from IDC. The IDC InfoBrief, sponsored by Kinaxis, “Making Supply Chain AI Accountable,” reveals a growing chasm between organizations’ aggressive ambitions for autonomous AI adoption and their readiness to hold these advanced systems - which we believe underscores the need for a disciplined approach to AI investment and deployment to prevent costly failures and deliver measurable business value.

What This Means for Supply Chain Leaders
The IDC InfoBrief, which surveyed more than 2,000 supply chain leaders across nine global markets, found that while AI adoption is nearly universal - only 2% of respondents report no AI-enabled capabilities, and just 12% consider themselves AI leaders. Over half (52%) cite trust in AI-driven decisions as a top barrier to faster adoption, and just 12% say AI planning governance is fully embedded within their operations.

The research also points to a sharp acceleration in expectations for autonomous decision-making: just 6% of respondents describe their supply chains as autonomous at scale today, but 41% expect that to become their core operating model within one to two years - even though only 1 in 8 organizations has governance fully embedded to support it. We believe this is the central challenge facing the industry.

Key Findings of the IDC InfoBrief: Making Supply Chain AI Accountable

• Adoption is broad, leadership is rare. Only 12% of respondents describe themselves as AI leaders, despite broad deployment of AI capabilities.
• Trust is the number one barrier. Fifty-two percent cite trust in AI-driven decisions as a top barrier to faster adoption.
• Value must be proven. 62% say better data quality and integration would accelerate investment; 51% want clear ROI and time to value.
• Ambition outpaces governance. Autonomous-at-scale jumps from 6% today to an expected 41% in 1–2 years, but only 12% have governance fully embedded.
• Accountability tops the agenda. 67% say accountability for AI-driven outcomes will require the most governance change.
• Roles will shift, not shrink. 79% see AI as an opportunity over threat, and partners with AI plus supply chain depth will win.

How Kinaxis Helps Bridge the Accountability Gap
With trust cited as the top barrier to adoption and only 12% of organizations reporting embedded governance, we believe the study points to a clear need for explainable, auditable AI. Kinaxis addresses this through its Maestro^® platform by:

• Enabling Trusted AI Decisions: Embedding explainable AI into Maestro^® so planning recommendations are auditable, addressing the 52% of leaders who cite trust as their top barrier.
• Providing Robust Governance Frameworks: Giving organizations the tools to set parameters, monitor performance, and maintain human-in-the-loop oversight for autonomous processes - closing the gap behind the 12% embedded-governance figure.
• Delivering Measurable Business Value: Connecting AI-driven insights directly to operational outcomes such as inventory optimization and forecast accuracy, in line with the 51% of leaders who want clear ROI and time to value.
• Facilitating Data Quality and Integration: Providing a single, harmonized view of data across the supply chain - the factor 62% of respondents ranked as the top accelerator of AI investment.

"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," said Justin King, Field CTO, Kinaxis.

“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,” said Eric Thompson, Research Director, Global Supply Chain Planning, IDC.

Webinar: The next phase of supply chain AI: From promise to accountable outcomes
Kinaxis will host a live webinar today, Tuesday, August 11 at 10:00 AM ET, featuring guest speaker Eric Thompson, IDC Research Director, and Justin King, Field CTO at Kinaxis, exploring how organizations can move beyond AI adoption to accountable outcomes. Registration is open through the start of the session; those unable to join live will receive access to the recording. The discussion will cover:

• What accountable AI means in a modern supply chain environment
• How organizations can build trust while improving governance and demonstrating ROI
• Why governance must evolve alongside expectations for autonomous decision-making
• How AI is reshaping supply chain roles and responsibilities
• What it takes to move from AI adoption to measurable business impact

Registration: https://www.kinaxis.com/en/events/next-phase-supply-chain-ai-webinar

The full IDC InfoBrief, “Making Supply Chain AI Accountable,” is available at: https://www.kinaxis.com/resources/content/idc-2026/making-sc-ai-accountable

About Kinaxis
Kinaxis is a leader in modern supply chain planning and orchestration, powering complex global supply chains, and supporting the people who manage them. Our powerful, AI-infused supply chain orchestration platform, Maestro, combines proprietary technologies and techniques that provide full transparency and agility across the entire supply chain - from multi-year strategic planning to last-mile delivery. We are trusted by renowned global brands to provide the agility and predictability needed to navigate today’s volatility and disruption. For more news and information, please visit kinaxis.com or follow us on LinkedIn.

Source: Kinaxis Inc.