ChatGPT-5 Won’t Book Your Loads: Real Freight Automation Starts with Email

AI hype won’t clear your freight inbox. Learn how Levity turns messy emails into structured automation that improves response times, accuracy, and broker ROI.

ChatGPT-5 Won’t Book Your Loads: Real Freight Automation Starts with Email

Every time a new AI model drops, the hype machine spins up. With ChatGPT-5, self-proclaimed “AI gurus” rushed to post that they had “automated their entire business” overnight. Templates, shortcuts, and out-of-the-box promises flooded LinkedIn feeds.

As Levity Co-Founder and CEO Gero Keil put it:

“GPT-4 to GPT-5 only is an incremental improvement. LLMs are plateauing… It’s now fully up to the application layer to unearth the vast untapped potential of AI across industries.”

And this FreightCaviar poll backs that up. 

While 43% said AI hype outweighs real impact, the majority pointed to day-to-day pain: inbox and phone chaos (30%), messy system integrations (20%), and edge cases or compliance (6%). 

That tells us the real bottlenecks aren’t solved by bigger models, but instead by structured, application-level automation. Here’s how Levity’s approach does it.

1. Reveal Inbox Bottlenecks

The average office worker in logistics gets hundreds of emails a day, spending nearly 23% of work time just checking messages. 

C.H. Robinson has proven this point at scale. They now automate over 10,000 email transactions per day classifying quote requests, processing tenders, and handling order intake automatically. It shows the inbox is the real front line for automation.

“Instead of waiting up to four hours for a person to get to their shipment in an email queue, over 5,200 customers are getting their loads accepted in under 90 seconds.” – Mark Albrecht, VP for Artificial Intelligence, C.H. Robinson

But Robinson has thousands of employees and the budget to build AI in-house. Most brokerages don’t. That’s why Levity starts with the inbox, too. 

Levity’s Control Tower makes the same insight accessible: revealing what’s in your inbox and surfacing where automation should begin. 

“A lot of companies say, 'We don’t know where to start.' And the reason for that is they don’t know how many emails of each type they get.” – Thilo Huellmann, Levity Co-Founder

Control Tower turns this blind spot into a dashboard giving brokers a first-ever look at volume by request type, response times, and bottlenecks, all before automating a single step.

2. Deploy Structured Automation

Black-box AI might look good in a demo, until it misreads a flatbed request or confirms the wrong pickup. Logistics can’t afford “magic tricks.”

Experimenting with AI is easy. Building automation that can be relied on every day is the real challenge. “ From scalability, to maintainability and AI reliability, a long tail of challenges awaits those who try,” Keil explains. 

Looking to C.H. Robinson again, their AI agents have already processed over 3 million shipping tasks. The catch is that it took them years of proprietary data, engineering teams, and constant retraining to get there. 

Instead of custom R&D, Levity’s AI Flows let brokers drag-and-drop rules, fallback logic, and edge case handling into their workflows with the explainability that black-box demos lack

3. Integrate Seamlessly

Integration is where many automation projects stall. In PwC’s 2025 Digital Trends survey, 42% of supply chain leaders flagged integration with existing systems as their top challenge. FreightCaviar’s poll results echoed this, with 20% of logistics professionals citing system integrations as the biggest blocker.

On Levity’s U.S. road trip, brokers repeated the same frustration: legacy TMS systems and brittle APIs.

Levity integrates without brittle workarounds, syncing email flows straight into your TMS, CRM, or legacy stack.

Levity.ai Hits the Road: Exploring America’s Freight Brokerage Hotspots
Thilo Huellmann and his team traveled 2,500+ miles, visiting key freight markets like Grand Rapids, Cincinnati, and Houston to discuss AI and automation with freight brokers. Here’s what they learned.

4. Measure & Optimize Continuously

Automation isn’t “set and forget.” If you can’t track outcomes, you’re flying blind.

Most brokerages don’t actually know:

  • How many quote requests they get each week
  • How quickly their team responds
  • Which reps are the most productive
  • Where service level agreements are breaking

C.H. Robinson measures these things at scale, tracking how long quotes sit in queues and how automation is improving speed.

Levity's Control Tower gives every brokerage the same visibility. It breaks down emails by request type, shows the full quoting funnel, tracks win/loss ratios, and even captures customer sentiment. 

Performance data isn’t buried in a monthly report. KPIs are live, actionable, and designed for brokers who need to adjust pricing, quoting, and customer response times on the fly.

The Levity Difference

C.H. Robinson proves what’s possible when you invest millions in AI: inboxes cleared, quotes accelerated, orders automated. But that’s not reality for most brokerages.

Levity takes the lessons of giants and makes them practical for the rest of the industry.

  1. Reveal inbox bottlenecks
  2. Deploy structured automation
  3. Integrate without brittle IT projects
  4. Measure and improve continuously

In a market full of noise, this is what enterprise-grade looks like: structured, explainable, and built to scale.

If “automation” has burned you before, it’s time to try a method shaped for logistics reality, not LinkedIn hype.


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