While nearly all respondents to ORTEC’s study recognize Agentic AI’s potential to modernize planning and execution, 42% of organizations report they are not yet exploring Agentic AI at all and remain focused solely on traditional AI and machine learning (ML) approaches.
“Executives are entering 2026 with a clear mandate: make Agentic AI real, measurable, and safe for operations,” says Daphne de Poot, SVP, operations, Americas, for ORTEC. “Our research shows they believe Agentic AI can fundamentally improve cost, service, and resilience, but they need transparent decisioning, reliable data, and a phased approach that keeps planners in control while AI gradually takes on more of the repetitive and complex decision-making work. These survey findings provide a detailed view into how leaders are thinking about the next wave of AI, beyond predictive analytics and into autonomous, decision-making systems that can continuously optimize complex logistics networks."
Key takeaways:
· The survey found that only a small minority had active Agentic AI pilots or deployments at the end of 2025, even as 23% say they plan to pilot Agentic AI within the next 12 months, putting 2026 squarely in focus as a test-and-learn year for autonomous decision-making in logistics.
· Expectations for impact are high, as respondents cite drastic cost savings through fuel and mileage optimization (30%), increased operational resilience (22%), and improved data quality (20%) as their top anticipated benefits.
· Respondents point to high integration costs with existing systems as their No. 1 frustration (32%), followed by lack of model explainability (26%) and poor data quality (22%).
· For organizations that have yet to adopt AI/ML in core logistics processes, the biggest barriers are lack of in-house expertise (23%) and unclear ROI (21%).
· Leaders also highlight structural risks unique to Agentic AI, including the need to redesign business processes for autonomous decision-making (42%) and reliance on high-quality, real-time data feeds (22%).
· Despite these obstacles, executives have a clear view of where Agentic AI should be applied first as they plan roadmaps for 2026 and beyond. First- and final-mile route scheduling is seen as the top target for AI-driven reinvention (35%), followed by global supply chain network design (20%).
· When asked what would most accelerate adoption, respondents prioritized clear ROI measurement frameworks (30%), peer case studies from similar organizations (25%), and seamless integration with existing planning systems (24%).
