{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"The Freight Show","title":"Jonathan Drouin (WWEX) on Build-vs-Buy for AI in Freight","html":"","width":"100%","height":180,"duration":3385,"description":"Most freight brokerages are drowning in AI pilots that never make it to production. The gap between a working demo and a system processing thousands of loads per week is not technical — it is organizational.It comes down to setting clear KPIs up front, running biweekly AI steering committees with full leadership visibility, and being ruthlessly honest about what is working and what is not.Jonathan Drouin has lived both sides of this equation. He started as a software developer at 19, moved his first freight load in 2012 at Bear Transportation under Michael Kaney, built and sold his own TMS company and brokerage, then joined WWEX (formerly Worldwide Express) in 2019 to lead truckload technology.Over seven years, he has helped scale the company from $2B to $5B through the GlobalTranz merger and 35+ acquisitions — migrating systems, integrating business units, and now spearheading AI deployment across the entire quote-to-cash workflow.Today, he oversees product strategy and AI initiatives for a company where freight mix is roughly 40% LTL, with the rest split between parcel and truckload, serving primarily SMB and mid-market shippers as the largest UPS reseller in North America.In this conversation, Jonathan breaks down the exact framework WWEX uses to deploy AI: how they mapped every workflow from quoting to cash, prioritized initiatives against three hard metrics — customer retention, margin growth, and cost reduction — launched a dozen AI projects in year one to stress-test the boundaries, and now run every initiative through a rigorous steering committee with predefined KPIs and public accountability.He explains why email AI and repetitive tasks deliver the fastest ROI, why they shifted from build-first to partner-first as model complexity increased, the change-management discipline that separates successful deployments from expensive experiments, and why he believes AI will chip away at exception handling far beyond today’s repetitive-task automation.What...","thumbnail_url":"https://img.transistorcdn.com/f0lw4441guZC8PqbG1LeEKiz-6dFl98YZjNUQNRMTjU/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS80M2Vl/NThjZmRkZTYyNWU2/YzkyNGYyZmNiZjU2/ZWIyOC5wbmc.webp","thumbnail_width":300,"thumbnail_height":300}