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July 2025
training a model. The grading is already figured out, built from countless data points across the industry, closer to plug and play than most of what gets called "AI" right now. The camera goes up, the system starts classifying pallets against a standard trained on millions of prior judgment calls, and within days every unit gets graded the same way, whether it's the first pallet of the shift or the last, whether the driver's fresh or exhausted. Precision and consistency, every time.
None of that makes the person optional, though. Human expertise plus AI will always beat human expertise alone. There's always more to solve. We're just getting started. I'd rather work with someone using AI than someone who isn't, and I think most of your customers agree, whether they'd say it in those words or not. The only person AI replaces is the one who refuses to use it.
Our industry has spent years arguing over whose grading standard is right, peer to peer, supplier to customer, every yard defending its own instincts. But what happens once enough of us run the same kind of AI vision system, feeding it real judgment calls day after day? Does the standardization fight we've been having for decades finally resolve itself, simply because the machines doing the grading all learned from comparable expertise?
Your next assignment before this quarter ends, book a demo with an AI vision company. Ask them directly how fast they can have a working system checking real loads, not months from now, but days. This isn't a build project. It's an install. If you don't know where to start, connect with me and I'll point you toward a few vendors worth a conversation.
Until next time, keep partnering with AI, keep envisioning what's next, and keep bridging the gap!
Human expertise plus AI
will always beat human
expertise alone.
Kat Vasquez
Follow Kat Vasquez on LinkedIn
September 2026