# **The AI Exchange: Routes That Learn From Every Delivery**

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### **Key Takeaways:**

- **Close the Gap Between Planning and Execution:** Create route plans that reflect real-world delivery conditions, not static assumptions.
- **Unlock Capacity Hidden in Existing Operations**: Improve route density, ETA reliability, and fleet utilization through more accurate planning.
- **Turn Delivery Data into Actionable Intelligence:** Transform execution data into insights that support better decisions, stronger customer communication, and continuous improvement.

In this episode of _The AI Exchange_ series, hosted by [SupplyChainBrain](https://www.supplychainbrain.com/), industry experts explore how AI in last mile delivery helps fleets move from [static planning](/content/resources/knowledge-center/what-is-route-planning-and-why-is-it-important#toc-4/index.html) to more adaptive, data-driven operations. The discussion looks at how [machine learning](/content/resources/knowledge-center/fleet-innovation-artificial-intelligence-and-machine-learning#toc-3/index.html) can use actual delivery execution to improve service time predictions, route planning accuracy, fleet utilization, and customer communication.

## **Why Static Routing Assumptions No Longer Work**

[AI-driven](/content/resources/knowledge-center/transforming-fleet-logistics-artificial-intelligence/index.html) planning takes a different approach. By continuously learning from historical [delivery data](/content/solutions/routing-mobile-and-telematics/route-execution-and-fleet-performance-management/fleet-analytics-and-ai/index.html), machine learning can account for variables such as customer type, geography, order size, product mix, site conditions, and equipment requirements to generate route plans that better reflect how routes are likely to perform in the real world. With more accurate planning, fleets can improve route adherence, deliver more reliable ETAs, increase route density, and spend less time reacting to unexpected disruptions throughout the day.

## **Watch the Full Webinar**

Watch the full discussion to learn how AI in last mile delivery enables routes to learn from actual delivery performance, helping fleets improve planning accuracy, optimize resources, and strengthen execution in the field.

### Meet the Experts

### **Cyndi Brandt,** VP, Fleet Solutions

Cyndi Brandt, VP of Fleet Solutions at Descartes, drives go-to-market strategy for fleet performance management solutions. With 23 years in transportation technology, she specializes in last-mile operations, dispatch, tracking, telematics, and data analytics, offering deep expertise in both last-mile and over-the-road logistics.

[connect with Cyndi about **Cyndi Brandt,** VP, Fleet Solutions](https://www.linkedin.com/in/cyndibrandt)

### **Sergio Torres,** Senior Vice President, Product Management

Sergio is Senior VP of Product Management for Descartes’ fleet performance management solutions, where he leads strategy and vision across the portfolio. Before joining Descartes, he was Director of Business Development and Consulting for CAPS Logistics in Europe.

[connect with Sergio about **Sergio Torres,** Senior Vice President, Product Management](https://www.linkedin.com/in/sergio-torres-45b14b/)

## **About SupplyChainBrain**

[SupplyChainBrain](https://www.supplychainbrain.com/) is one of the supply chain industry's most trusted sources for logistics, transportation, and supply chain management insights. Through expert analysis, educational content, webinars, and industry coverage, SupplyChainBrain helps professionals stay informed about emerging technologies, operational best practices, and the trends shaping the future of global supply chains.

## **Fleet Resource Center**

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