It’s official. The buzz has shifted from AI in general to AI agents in particular. What’s the difference? AI agents go beyond large-scale data ingestion and smarter decision-making, to autonomously execute those decisions, at speed and scale.
In the supply chain, agentic AI is well suited to address many pressing challenges. Trained AI agents, working within predefined guardrails, can conduct analysis and arrive at solutions much faster than humans. They can build optimal loads, plan routes, reimagine warehouse layouts, and balance inventory. They can proactively rebook shipments and adjust carrier assignments. They can identify cost leakage and protect margins, as well as meet sustainability targets.
Across the enterprise and across functions, dedicated AI agents translate insight into action, autonomously and in real time. Agentic AI replaces days or weeks of manual planning and execution with a response that takes just micro-seconds.
By 2028, Gartner predicts that AI agents will autonomously make at least 15% of day-to-day operations decisions. Gartner analysts also believe that agentic AI will be incorporated into 33% of enterprise software applications by 2028.
But elsewhere, Gartner highlights the challenges of getting there. In fact, Gartner estimates that more than 40% of agentic AI projects will be canceled by the end of 2027. One of the primary factors? Companies lack the needed technical and data readiness to deliver meaningful agentic AI outcomes. They’re missing the robust technical infrastructure, as well as systems integration, required to move AI agents from narrow task completion to true crossfunctional supply chain orchestration.
With the right foundation, agentic AI becomes a strategic game-changer.
These findings dovetail perfectly with the results of Redwood’s recent Customer Advisory Board (CAB) survey. The findings, summarized in our AI in Logistics Report, highlight the critical importance of building the right tech architecture to enable AI success — before embarking on pilot projects that are destined to underperform.
Lacking a robust, connected digital architecture, today most organizations are anchored in reactive AI, using out-of-the box “copilots” or “assistants” to summarize emails, scrape portals, and perform other administrative tasks. While these applications save time, they only scratch the surface of AI’s enormous strategic potential.
In today’s disrupted supply chain landscape, exception management is one of the most critical functions of AI. But the value of AI doesn’t end when a disruption is identified. The highest value of advanced AI agents is flagging an exception at one node, determining the impact for every other node, and orchestrating an immediate response across the supply chain.
That’s only made possible by aligning end-to-end systems and digitally connecting multifunctional workflows. With a seamless, robust architecture supporting it, AI is empowered to master complex, multi-step logistics workflows like autonomous freight procurement and inventory movements in response to changing conditions.
Redwood sees a future where agentic AI will deliver “zero touch” resolution for 80% of standard supply chain exceptions, including blocked routes, weather events, and supply shortages. This doesn’t eliminate human team members. It elevates their roles, allowing them to define and perfect AI guardrails, monitor AI outputs, and intervene only when complex, non-standard situations emerge.
When AI agents are embedded in end-to-end supply chain workflows, they also make continuous improvement automatic. Key indicators like cost-to-serve are analyzed and improved in real time, instead of at backward-looking, regularly scheduled intervals. With AI, the financial impact of every tender, new route, or spot freight buy is clear before any decisions are made. Agentic AI makes smart, profitable trade-offs every minute to keep cost-to-serve and other metrics on track. That’s a game-changer for every supply chain stakeholder.
Architect optimal AI outcomes with help from Redwood.
Despite the potential payoff, many agentic AI pilots fail simply because of tech infrastructure issues. Companies may lack the internal expertise and resources needed to connect AI agents to integrated solutions across the supply chain — including the TMS, WMS, and ERP — so an AI-enabled decision in one system can naturally roll out across other systems.
As a modern 4PL, Redwood has the expertise and resources you need to quickly achieve an optimized, integrated tech architecture for AI. Via our proprietary RedwoodConnect integration platform, standardized APIs, and proven best practices, Redwood provides a seamless orchestration layer that positions AI agents to deliver at their highest level. Agentic AI can easily make and execute decisions across your in-house solutions and workflows, as well as your carrier networks.
Redwood has invested in defining opportunities where agentic AI can add strategic value in supply chains — and we’ve also built agents for high-volume, human-intensive workflows, particularly in spot and brokered freight. We can deliver transformational cost and service improvements in procurement, as well as other functions.
We understand that you don’t need another visibility dashboard, point solution, or task automation tool. You need practical, hard-working AI that delivers enterprise-wide improvements in disruption management, cost control, inventory balancing, and other critical areas. Backed by hundreds of successful customer engagements spanning two decades, Redwood understands your challenges — and our deep agentic AI expertise helps you overcome them intelligently.
As supply chain risks grow, you need the power of AI agents.
As we move into the second half of 2026, it’s clear that logistics volatility is at an all-time high. In its annual assessment of supply chain risks, Everstream Analytics rates geopolitical fragmentation at a 97% threat level, while extreme weather risk is rated at 93%.
Agentic AI is the clear solution for navigating today’s disrupted landscape with agility, precision, and strategic intelligence. Modern AI can master complexity and deliver more certain outcomes, even amid uncertainty. But AI agents need the right architecture to orchestrate those outcomes across the supply chain, at speed and scale.
Reach out to Redwood to learn more about how we can help you architect AI success, quickly and cost-effectively. You don’t need to add internal resources or make aggressive new tech investments. You just need the right partner.
This blog is the fourth in a five-part series from Redwood on the four pillars of AI readiness. In our fifth and final installment, we’ll look at the importance of change management as you transition your supply chain and culture to an AI mindset.