AI Offers More Intuitive Way for People to Interact With Complex Systems Without Wrestling With Menus and Manual Processes
For years, the trucking and logistics industry has been flooded with software companies claiming to offer “AI.” The term appears everywhere — on websites, in sales pitches and in product announcements.
But look closer and it becomes clear that much of what is marketed as artificial intelligence is simply traditional automation with a new label. These systems follow preprogrammed steps and rigid workflows. They are useful and essential components of modern transportation software, but they are not intelligent, and they are not transformative.
And to be clear, AI isn’t perfect — no technology is. It’s not about replacing people or eliminating every challenge inside a transportation management system. When applied correctly, however, AI offers a more intuitive way for people to interact with complex systems without wrestling with layers of menus and manual processes.
The real operational bottleneck in transportation technology has never been the lack of automation; it’s the time, cost and frustration associated with training people to use a TMS. Dispatchers, customer service representatives, planners and safety teams all rely on a TMS, yet training new employees often takes weeks. Even experienced professionals struggle when switching platforms because new software can be difficult to navigate.
Ask any carrier what it costs to get a new dispatcher fully productive, and the answer is rarely salary alone. It’s the steep learning curve; interfaces are complex, workflows are unique and simple tasks often require navigating multiple screens. Companies respond by creating internal documentation, job aids and training videos — not because the work is complicated but because the software is.
This is where true AI — not marketing buzzwords — begins to matter. Generative AI models such as ChatGPT introduce a fundamentally different way to interact with software. Instead of memorizing steps, users can simply tell the system what they want, such as:
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- “Create a load from Boise to Salt Lake City for tomorrow.”
- “Show me which drivers or trucks are available today.”
- “Generate a rate confirmation for this load.”
The system understands intent and performs the task.
This is not a macro, script or workflow. It represents a shift away from forcing users to learn the system before they can use it. For an industry facing tight margins, labor shortages and persistent turnover, that shift matters.
Natural-language interfaces deliver three immediate benefits. First, training time drops dramatically. New hires can focus on learning the job rather than learning software navigation.
Second, workforce flexibility increases. Faster onboarding and easier cross-training make operations more resilient.
Third, data becomes more accessible. Information that once required reports or specialized knowledge can be retrieved by simply asking a question.
Of course, this transformation depends on deploying real AI rather than rebranded automation. When a system still requires rigid, step-by-step interaction, it is not intelligent. True AI interprets context, understands intent and adapts to new instructions. That distinction will increasingly separate vendors that deliver value from those that only market it.
AI will not replace people. But it will replace the time people spend fighting software. It will reduce repetitive training cycles and eliminate friction that slows operations. As more systems adopt natural-language interfaces, transportation companies will unlock productivity not by adding features but by making technology easier to use.
There will always be a place for automation, but automation alone is no longer enough. The industry deserves tools that adapt to how people think and work. The TMS providers that develop genuine AI will move ahead — not because they claim to have AI but because their systems demonstrate its value in real-world operations.
Julie Dodson is director of operations at TruckMaster Logistics Systems, where she focuses on improving TMS usability and operational efficiency for carriers and brokers.
