How AI can help with testing products before accessing real users
In design, AI has shifted from being a buzzword to an essential tool in daily workflows. Agentic AI, a newer development, goes beyond simple automation. It’s a system that works independently, handling tasks that designers once had to oversee themselves. This is especially useful during early-stage product testing, where catching issues early can save a lot of time and effort down the line.
When applied to design, agentic AI can review prototypes, identify potential problems in a flow, or flag areas where the user experience might break.
It acts as an extra layer of validation before human testers even get involved.
The practical shift from human-driven to AI-assisted testing
In the past, product testing meant relying on human testers. It was a necessary but slow and expensive process that often stretched out product timelines. Designers would build, wait for feedback, and then go back to tweaking and reworking the designs, creating delays.
With agentic AI, this cycle looks different.
Instead of waiting for human input at every stage, AI tools built into design platforms can step in early. They catch things like layout misalignments, buttons that don’t work, or accessibility issues, acting as a first line of defense.
They can now spot inconsistencies in design systems or check if a design sticks to brand guidelines without anyone having to manually go over it.
How agentic AI handles objective validation
Let’s look at how it works in real-world tools.
Take Maze, for example. It allows designers to simulate user journeys and spot friction points before human testers are involved.
Designers can run tests on their prototypes and get immediate feedback on potential issues. The tool can flag usability problems, such as unclear navigation or broken interactions, making it easier to refine the user flow early on.
This means that before any human testing happens, designers already have a clear picture of how well their product holds up.
It’s like having an automated second set of eyes.
How agentic AI handles subjective validation & current limitations
AI excels at objective validation but still has limitations with subjective elements like visual aesthetics and user experience.
AI tools can suggest functional improvements,