Seeing the Supply Chain More Clearly with Agentic AI
Visibility is one of the most persistent challenges in the supply chain. Even with modern transportation systems, teams often still rely on manual status checks, emails and follow-ups to understand where things stand. At scale, those small gaps add up quickly, slowing decisions and increasing operational friction.
As supply chains grow more complex, the ability to validate information quickly and consistently becomes just as important as the data itself. When updates lag or require repeated outreach, teams lose time they could otherwise spend addressing higher value work.
Reducing Manual Work at Scale
To help address these challenges, Penske Logistics has implemented an agentic AI platform from Augment, designed to improve visibility speed and efficiency across the supply chain. The platform is being applied in areas where manual processes have traditionally slowed follow-up and decision-making.
In the program’s initial phase, the platform is being used to validate the status of an estimated 600,000 loads. By automating routine checks and supporting more consistent follow-up with carrier dispatchers, the approach is expected to reduce time spent on repetitive tasks while improving the quality and timeliness of information available to operating teams.
“We’re well underway with executing our AI strategy, and our partnership with Augment is one of many AI-related and tech-enabled supply chain initiatives we are implementing to enhance the experience for our customers,” said Jeff Jackson, president of Penske Logistics. “AI at this scale is about giving customers more convenience, certainty and clarity in an increasingly complex and dynamic operating environment.”
Supporting Operations Across the Supply Chain
Rather than focusing on a single segment of the network, the platform supports efficiencies across inbound operations, middle-mile movements and final delivery. This end-to-end view helps teams see issues sooner, respond more quickly and coordinate actions more effectively across different stages of the supply chain.
As the system continues to scale, additional efficiencies are expected as workflows become more streamlined and insights more readily available. The goal is not automation for its own sake, but practical improvements that help teams focus on what matters most.
Applying AI where it delivers real value
AI has the potential to create meaningful operational improvements when it is applied thoughtfully and grounded in real-world workflows. By focusing on visibility, follow-up, and consistency at scale, the approach reflects a broader effort to use technology in ways that support people, processes and performance across the supply chain.