AI is accelerating the way that user experience designs are validated. Below I take a look at how AI is improving the speed and confidence of design work prior to implementation.
Acceleration > Rapid Prototyping
Prototyping with AI accelerates delivery and can reduce product insight costs.
In the world of software a prototype is something that allows a person to simulate the use of a system without needing the full investment to build it. Prototypes are typically used to validate whether a user experience will serve a user’s purposes before committing to engineering a full solution.
With the rise of unmoderated testing platforms that connect users with the prototype you need validated, it can be very quick and easy to collect user feedback on early designs.
Prototypes can also be treated as a living document that delivery teams use to support their understanding as they build robust software.
How is AI changing things?
AI is having some dramatic impacts on the practice of prototyping by lowering the cost of creating a prototype from hours and months to minutes. Using AI-powered prototyping tools, you can now easily:
- Provide realistic content in the interface, rather than placeholder text
- Develop prototypes with complex logic, rather than relying on verbal explanations of how something will function
- Create high-quality, on brand user interface designs, to help establish familiarity
The combined decrease in the cost of prototyping and validation is allowing product leaders to spend more time experimenting and ensuring they’re building the right thing, rather than working with their teams to figure out how to build it.
In addition to building the prototype, AI agents are also validating user interface designs, identifying issues, creating iterations and continuously checking compliance with accessibility standards and visual guidelines.
What can you do about it?
The same traps exist for AI-created prototypes that have always existed:
- Reluctance to criticize. When users are presented with paper prototypes made from sticky notes and markers, they intuitively understand the cost of a change is low. When they are presented with a perfect, beautiful computer-based design they are less likely to criticize [26], which can reduce the value of feedback sessions.
- Executive misunderstanding. When a leader sees how quickly a prototype can be created, they can be misled into thinking the software is complete. Special attention should be given to ensuring leaders understand the difference between a prototype that’s optimized for appearance and a fully tested, quality software product.
- Feasibility. It’s easy to dream up user interactions, but can be quite costly to implement interactions that aren’t supported by existing frameworks and data structures.
In Summary: AI speeds prototype creation, but does little to relieve the traditional issues with prototypes.
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