Customers expect a Managed Transportation partner to run their freight reliably and cost efficiently. They should get more: experts who understand their network, bring ideas for making it better, and drive those changes. The scale and knowledge of their partner should work to their advantage.
At Uber Freight, we call this Transportation Orchestration and it’s the next step in delivering on this promise. It means continuously monitoring how customers’ networks perform, identifying opportunities to improve, and increasingly automating the decisions and execution that turn those insights into results. Our scale creates opportunities to improve each customer’s network in ways no individual company could achieve alone.
Advances in AI expand what is possible. Even the best experts can only review so much information at once. AI enables us to analyze far more network data in real time, identify better options, and increasingly automate action. As routine execution becomes more automated, our experts can focus more on advising customers and implementing strategic changes. Those changes—and their results—feed back into the system, improving future recommendations and helping us identify where similar improvements could benefit other customers.
As Chief Product Officer, my focus is on building that loop so our capabilities and expertise grow more powerful with every interaction.
A partner that sees what’s next
In my first few months at Uber Freight, customer conversations have sharpened my thinking about the opportunity ahead. Running today’s freight well is essential table stakes. Customers benefit the most when we bring ideas and drive the change tomorrow requires.
Customers value visibility and expect us to act on it: anticipate disruptions, protect service, and address recurring problems at the source. When demand, freight rates, or facility operations change, they need guidance on the implications for service and budgets—and help executing the right response.
As a partner working across shippers in a broad range of industries, we bring a broad perspective, helping customers understand what is possible and which changes are worth pursuing.
Making the next decision smarter
We see three connected steps toward increasingly autonomous network planning and freight execution: automate routine work, turn data into actionable intelligence, and increasingly automate execution.
First, automation makes planning, tracking, and information gathering faster and more consistent, with fewer errors. Second, intelligence helps identify patterns, diagnose problems, and recommend better options. Third, we connect that intelligence to tools that turn recommendations to action, with experts remaining in the loop to guide high judgment decisions. We capture and measure the results, feeding them back into the system to deepen the system’s transportation knowledge and improve future decisions.
For example, repeated late deliveries might reveal that a route consistently takes longer than planned. The system identifies the pattern, adjusts the plan within agreed parameters, and measures whether service improves. No digging through reports, analyzing data, or manual decision and action taking needed. If it works, that learning helps identify similar issues in other customers’ networks—so one improvement becomes the starting point for others.
Make the broader network work for each customer
Some improvements come from understanding one customer’s operations deeply. Others require looking across shippers.
For years, the industry has largely optimized within individual networks. A private fleet may be well planned around one shipper’s freight, while two shippers may each have a workable plan that leaves their trucks partially filled—even when their shipments could move together. Improvements happen incrementally at the edges where opportunities arise, often leaving carriers to connect the pieces across networks.
Looking across those networks creates a bigger opportunity: coordinating freight and capacity to lower costs in ways individual shippers cannot achieve alone. Finding those opportunities requires understanding each shipper’s constraints; delivering them requires coordinated execution.
Uber Freight brings together the network insight and capabilities to orchestrate that execution. Managing our customers’ logistics gives us operational expertise, our marketplace connects us to capacity, and Uber provides a technology foundation we are building upon. Our product priority is to make these opportunities easier to identify, evaluate, and execute consistently, so more customers benefit from our scale.
AI empowers experts to drive change
Our logistics experts understand the constraints and trade-offs that determine whether a recommendation will work in the real world. Their judgment remains essential as agents take on more routine execution.
With more data and analysis at their fingertips, our experts can bring customers better ideas, guide network decisions, and implement strategic changes. Customers should feel that shift in the partnership: technology handling more daily execution, with experts focused on what their network needs next.
The vision is ambitious. Progress has to be tangible.
Transportation Orchestration is the future we’re building toward. We are moving with urgency: improving the data that informs recommendations, connecting those recommendations to execution, and proving that agentic execution delivers tangible benefits and reliable results in customers’ operations. We are iterating on these capabilities, learning as we go, and expanding what works across all the freight we manage. This will take time to build, but every step will create value.
Customers will judge our progress through the outcomes that matter to their business: lower costs, reliable service, and faster adaptation as their businesses change. Our responsibility is to deliver networks that continuously get better—with systems that operate autonomously and experts guiding high-judgment decisions to drive strategic change.
Let’s build!
—Amir Pelleg, Chief Product Officer, Uber Freight
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