Based on a recent survey of our Customer Advisory Board (CAB) members, Redwood’s AI in Logistics Report reveals the real-world state of AI adoption among supply chain teams. One of the most surprising findings? Only 13% of logistics teams are realizing a quantifiable return on their investments in AI.
According to the IBM Institute for Business, the potential of AI in supply chain is real. Some companies are seeing significant value from logistics-centered AI deployments, especially from AI agents. These narrowly defined AI applications go beyond data ingestion and analysis to actually execute decisions.
The IBM Institute for Business found that organizations actively using AI agents expect to achieve a 36% improvement in procurement compliance, a 34% improvement in inventory turnover, and a 43% increase in real-time spend visibility by 2027. And those aren’t just “pie in the sky” numbers. They reflect actual AI capabilities already put into place, and scaling continuously, that drive autonomous execution in areas like procurement.
Looking for an AI transformation? Start with your operations model.
If you’re not achieving these kinds of results — or if you’re among the 40% of Redwood customers who haven’t piloted AI yet — don’t be discouraged. Be inspired. AI can deliver incredible financial, service, and efficiency benefits. It just requires the right foundation.
In our AI in Logistics Report, we identified four pillars for AI readiness, and this blog looks at the first: Organizational Structure and Operating Model Readiness.
Based on the findings of our CAB survey and our own hands-on work with customers, Redwood believes an AI transformation begins with assessing and updating your operations. The C-suite executives studied by the IBM Institute for Business agree. An overwhelming majority (78%) of them claim that achieving maximum benefits from agentic AI requires a new operating model.
Current supply chain organization structures are built around a premise that’s quickly becoming outdated: Human analysis is required to make all decisions. The truth is that AI agents can be trained to build loads, procure freight, and optimize inventory with far greater accuracy and speed than human planners. Human involvement is rarely needed to make and execute most supply chain decisions today. That doesn’t make your planners obsolete. It elevates them to roles where they intervene only in the most important cases.
But your operating model isn’t built for this scenario. It most likely relies heavily on human cognition, which is slow, error-prone, and unable to absorb and process huge volumes of real-time supply chain data. A LeanDNA study revealed that supply chain professionals currently spend about two days out of every week manually tracking data.
If you combine this human-first mindset with an outdated organizational structure, any AI application will simply become a standalone analytics tool that’s micro-managed by humans, instead of acting autonomously to drive greater speed, efficiency, and precision.
Your organization needs to change to fully leverage AI. The world of logistics simply moves too fast today for humans to keep up. Rates and costs fluctuate. Demand and supply shift. Routes are blocked. Weather events and other disruptions strike with little warning. AI can master these challenges in seconds. But you need to create an environment in which it can deliver its full power.
Imagine a future state where your supply chain is AI-ready.
What does the ideal organizational structure for AI look like? Instead of relying on humans to make and execute all decisions, AI agents become virtual team members — competently and accurately managing day-to-day activities like carrier selection and freight audits.
Humans monitor and supervise these agents, acting at the strategic level instead of the tactical level. This “human in the loop” approach exponentially amplifies the output and impact of planners, as they manage many more decisions, faster and more accurately.
Of course, this means having a carefully controlled operating model where authority and empowerment are balanced precisely between humans and AI agents. While AI excels at automating routine tasks — and can often resolve minor exceptions on its own — humans are still needed to make the big judgment calls.
Your organizational structure needs to reflect a distinction between day-to-day, automated execution and the occasions where a planner needs to step in to master unexpected disruptions or make strategic tradeoffs. These are two separate, but equally important, functions in the AI-enabled supply chain. Roles and skillsets will need to be redefined.
You’ll also need to shift your operating model from focusing on siloed tasks — like freight bidding or audits — to encompassing longer, end-to-end workflows like procurement. AI adds enormous value across these longer workflows by connecting, orchestrating, and informing discrete tasks.
For example, when an AI agent senses a disruption at one node of the procurement process, it needs to execute a correction at other nodes. AI can’t fully deliver if its view and its actions are constrained by functional silos that no longer make sense.
How will you get there? With Redwood.
If an organizational restructuring sounds time-consuming and resource-intensive, that’s true. But only if it’s led by your internal staff. If you undertake the operational groundwork on your own — including defining new roles and decision rights, creating cross-functional process ownership, implementing AI rules and guardrails, and establishing human-in-the-loop governance — that process can easily take 18 months.
Fortunately, you’re not on your own. You can significantly compress the restructuring process and accelerate AI results by partnering with Redwood. With decades of experience, hundreds of customer success stories, and unmatched technical leadership, we know how to get your supply chain AI-ready. As a modern 4PL, we uniquely combine operations and digital expertise, which positions our customers to maximize the value of AI in their supply chains.
Instead of building a new operating model from the ground up, you can benefit from our templates and best practices — quickly launching a new AI-ready structure that’s been tested and refined across logistics teams just like yours. That new structure will get individual AI agents launched quickly, then scale as your use of AI expands. Redwood works with your team at every step, from pilot to enterprise deployment, to ensure your operating model is maximizing your returns on AI.
Improve your AI readiness in weeks, not months. Starting now.
The words “organizational restructuring” can put fear into the heart of any logistics professional. But fear not. Redwood is not about to rip and replace every aspect of your daily operations. We respect your investments and the work your team is doing today. Instead, we’ll help you redefine the roles, processes, and decision parameters that pertain to AI — relying on proven practices.
AI is only growing in its ability to master your most urgent logistics challenges, both at the strategic and tactical levels. Don’t wait months or years to capitalize on advanced intelligence. Contact us today to start building your future.
This blog is the second in a five-part series from Redwood. Over our next three blogs, we’ll explore three additional pillars of AI readiness. Up next: Establish a solid data foundation and integration resources.