A new ORTEC survey shows that despite growing pressure to reduce fuel use, stabilize networks, and improve planning speed, a significant share of logistics organizations remain reluctant to move beyond traditional AI tools. The findings highlight how expectations for Agentic AI are rising faster than operational readiness, especially as disruptions, tariff swings, and volatile freight flows continue to expose the limits of rule-based planning.
Nearly half of respondents, 42%, say they are not exploring Agentic AI at all, according to ORTEC’s November 2025 survey of more than 2,000 transportation, logistics, and supply chain executives across North America. The gap underscores how adoption is still concentrated among early movers, even as the industry looks for technologies that can automate more decisions without compromising safety or service.
Growing Interest, but Slow Movement Toward Pilots
Only a limited number of companies had Agentic AI pilots or live deployments by the close of 2025, though 23% expect to begin pilots in the next year. Cost reduction remains the biggest draw: 30% of respondents expect lower mileage and fuel consumption, an increasingly urgent priority as transportation providers navigate tighter margins and emissions-linked reporting requirements. Others pointed to stronger network resilience (22%) and better data reliability (20%) as the areas where automated decisioning could prove most valuable.
But barriers remain substantial. High integration costs were cited by 32% of respondents, reflecting the difficulty of embedding Agentic AI into routing engines, telematics platforms, and TMS stacks that were not originally designed for autonomous decision loops. Concerns about model transparency, reported by 26%, continue to shape internal risk assessments, especially in environments where planners must justify decisions that affect service levels and contractual performance. And 22% flagged poor or inconsistent data as a persistent adoption drag, echoing a theme widely reported across logistics in late 2025 as companies modernized aging data infrastructure.
A Wide Range of Readiness Levels Inside Logistics Organizations
For companies still early in their analytics journey, the obstacles are more foundational. Twenty-three percent said they lack in-house expertise to manage or evaluate Agentic AI, while 21% said the business case remains unclear. Many respondents also anticipate changes to how work is structured: 42% believe organizations will need to redesign business processes to support autonomous decisions, and 22% emphasized the need for stable, real-time data pipelines.
Despite reservations, respondents identified two priority entry points. First- and final-mile route scheduling ranked highest at 35%, a logical starting place given rising demand variability and tightening delivery windows. Global supply chain network design followed at 20%, an area where Agentic AI could help companies continuously rebalance flows as tariffs, capacity constraints, and cross-border requirements shift.
When asked what would accelerate adoption, respondents pointed to clearer ROI frameworks, evidence from comparable organizations, and smoother integration with existing planning systems. These themes align with broader industry commentary in late 2025, as shippers and carriers sought technologies capable of supporting real-time orchestration without overwhelming operational teams.
A Shift Toward Verifiable Decisioning
Across North America and Europe, regulators and large shippers are placing greater weight on audit trails for routing, emissions calculations, and capacity allocation. That pressure is steering attention toward systems that can show how a decision was formed, not just the outcome it produced. As companies evaluate Agentic AI in 2026, its ability to surface traceable reasoning may carry growing operational value, particularly in environments where service commitments, contractual penalties, and emissions disclosures increasingly depend on defensible digital records.
