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The industry's main goal right now is speed and momentum. Use AI to gain speed. Kick products out. Get to market faster. And I understand the appeal. I really do. But what most people underestimate is the complexity that lives in the details.
If you can use an AI tool to create a dashboard or build a product, you can get to 95% accuracy pretty quickly. That part is impressive. But it's that last 5% where the real time gets spent. The inconsistencies. The data variations. The edge cases that don't fit neatly into a pattern. Getting from 95% to 100% is often overlooked, and it's significantly harder than most teams realize.
Speed Without Visibility Is Just Noise
Here's where I see companies get tripped up. They roll out new automation or workflow tools and focus entirely on how quickly they can deploy them. But the most important thing with automation is that you have a full audit trace and full visibility into how the decision got made.
Who authorized this automation to run in the first place? What were the inputs? What were the outputs? Users need to see all of that. And rightly so. In an age of information, users want to be able to self-serve. They don't want to have to ask how a decision was made. They want to be able to go and see how the decision was made for themselves.
The key to any automation is full visibility into the trace. If your team can't explain how an automated decision happened, you don't really have automation. You have a black box. And nobody should be comfortable making business decisions based on a black box.
Where AI Actually Delivers in Supply Chain
I think the best use case for AI is actually pattern recognition. That's its primary strength. AI is very good at identifying patterns. Those patterns can lead to conclusions, which can lead to recommendations.
But what gets me excited isn't just the pattern or even the recommendation itself. It's about consolidating that data for our users and showing them how making a certain decision based on a recommendation will materially impact their business. It's not only giving the recommendation. It's saying: here are the three things you can do, and here's what the data is going to look like if you do each of those three things.
That's the difference between a tool that tells you something and a tool that helps you decide something. And for supply chain teams making decisions that affect millions of dollars in spend, that distinction matters.
Why Dashboards Alone Won't Get You There
A dashboard is great. You have to have them. They provide visibility, and they're useful for understanding where you are today and how that compares to where you were yesterday. That's great information to have.
But where dashboards break down is in the recommendation. What do I do with this information now that I have it? So now I know I'm not paying my invoices on time. How do I fix that?
Focusing on the workflow allows you to see each step of the process and come to the recommendations you need to make changes. That's really where the industry is going. Recommendations over data. Not just telling you what happened, but guiding you toward what to do next.
The Accuracy Gap Is a Strategy Problem, Not a Tech Problem
The push for speed isn't going away, and it shouldn't. But the conversation needs to shift. Getting to 95% accuracy with AI is a technological achievement. Getting from 95% to 100% is a strategic achievement. It requires understanding your data variations, edge cases, and business context in a way that no AI tool can do on its own without the right inputs and oversight.
The companies that will win are the ones that move fast and invest in the visibility, audit trails, and workflows that make speed actually meaningful. Speed without accuracy isn't efficiency. It's just risk moving faster.
Dimi Kurtti is Senior Director of Product Strategy at Trax. With nearly 20 years at Trax spanning roles from business analyst to SVP of professional services and implementations, Dimi brings deep expertise in freight audit operations and supply chain data strategy.
Want to learn how Trax is helping companies turn freight audit data into strategic advantage? Contact Trax to learn more, or connect with Dimi directly on LinkedIn.