A recent survey of North American transportation, logistics, and supply chain executives reveals a disconnect between what those leaders see as the promise of advanced artificial intelligence (AI) solutions, such as Agentic AI, and their readiness to implement them.Conducted by global technology firm Ortec, which provides optimization software and analytics solutions to a range of industries, the survey examined the effects of adopting AI and machine learning (ML) in logistics. While nearly all of the survey’s 400 respondents said they recognize the potential of Agentic AI to modernize planning and execution, 42% said they are not yet exploring the technology and instead remain focused solely on traditional AI and machine learning (ML) approaches.“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,” according to the report.There are key differences in traditional and advanced AI: Traditional AI solutions perform tasks based on predefined rules and algorithms—a common example is the virtual assistant Siri. Agentic AI solutions can make decisions without human intervention—examples include autonomous vehicles that can navigate traffic.Despite a lack of industry testing and deployment of Agentic AI, respondents said they have high expectations for its use in supply chain operations, citing drastic cost savings through fuel and mileage optimization (30%), increased operational resilience (22%), and improved data quality (20%) as…
