February 4, 2026
According to a FreightWaves report, after several years of implementing AI, research findings reveal a striking pattern. Jecklin says that when companies implement AI into existing workflows that have been in place for 10 years, they see little productivity improvement. However, if organizations fundamentally rethink their workflows, task structures, and what they’re trying to accomplish, productivity can increase by as much as 70%.
Echo has developed a dual strategy that combines both top-down and bottom-up approaches to AI implementation. Top-down strategies target specific high-volume tasks that are performed thousands of times throughout the organization. Echo deployed an AI system that quotes emails directly from shippers, builds loads from email content, tracks updates, collects documents, and manages the billing process.
Although Jechlin initially believed a top-down approach would provide the most value, his perspective has changed dramatically. He is increasingly bullish on a bottom-up strategy focused on helping Echo’s 3,000 employees learn how to use AI tools to their advantage based on their specific roles and challenges.
The reasons behind this change reflect the fundamental nature of brokerage and logistics operations. The industry thrives on nuance, with different customers wanting different things and unique requirements emerging from shipper to shipper and carrier to carrier. The true scope of these sensitive tasks is often not recognized until the employees who handle them every day begin to identify opportunities for AI assistance.
To support this approach, Echo introduced the concept of AI Enthusiasts or AI Champions across the organization. Hundreds of these individuals are trained to understand AI tools, allowing them to think critically about their roles and daily tasks and identify opportunities for improvement. When an AI champion develops a promising idea, Echo may organize a hackathon to quickly build a prototype. Successful innovations bring financial rewards and recognition, and the solution can be scaled up to other teams facing similar challenges.
This bottom-up model is similar to a venture capital portfolio strategy, where multiple teams experiment simultaneously in hopes of developing breakthrough solutions. The democratization of AI tools has fundamentally changed who can drive innovation with Echo. Everyone can now function as a process engineer or automation engineer using the tools at their disposal.
Tasks that previously required weeks or months of development time to be added to the roadmap can now be completed very quickly. This speed, allowing engineers and employees to build functional solutions in a day, has led Echo to implement more hackathons than ever before. For developers, this means a significant evolution in their role. They increasingly serve as code reviewers working with prototypes that already incorporate real-time business inputs.
Developers receive clearly defined requirements and working prototypes from hackathons, allowing them to focus on refining and implementing their solutions rather than tackling vague early-stage development. Looking to the future, Jechlin sees a future where logistics systems become simpler, rather than more complex. The nuances of intermediary operations can now be handled by AI, eliminating the need to build these nuances directly into transportation management systems.
The next wave of AI adoption in logistics will come not from simply automating existing processes, but by rethinking the way work gets done and empowering every employee to be an innovator.
Source: IndexBox Market Intelligence Platform
