If you're running a small SaaS or managing a tight development budget, you know the frustration: you suspect your app has UX issues, but hiring a UX consultant is not always feasible, and your team is too close to the product to spot problems objectively.
Recent studies show that every dollar companies invest in UX results in a return of $100 and design-centered companies outperformed the S&P by 228% between 2004 and 2014 (Baymard Institute).
The good news? AI has gotten surprisingly good at spotting UX issues—if you know how to use it properly.
Why Nielsen's Heuristics Work So Well with AI
Back in 1994, Jakob Nielsen established 10 Usability Heuristics for User Interface Design that remain the gold standard for UX evaluation. These heuristics include things like "visibility of system status," "user control and freedom," and "consistency and standards."
What makes these principles perfect for AI evaluation is their objectivity. Unlike subjective design preferences, Nielsen's heuristics provide clear, measurable criteria. An AI can systematically check whether your interface provides clear feedback, follows consistent patterns, or prevents user errors—without getting distracted by personal taste or familiarity with your product.
Nielsen himself has shared his perspective on AI being used for heuristic evaluation (What AI Can and Cannot Do for UX):
I see no reason why AI won’t eventually get better than most (or all) human UX experts at heuristic evaluation
The Current Reality: Promise and Pitfalls
But here's the catch—while AI shows tremendous promise, current implementations often fall short. A comprehensive study by Baymard Institute found that direct GPT-based UX audits produced numerous false positives and missed critical issues that human evaluators caught easily.
That study is from October 2023, so besides getting better AI models since then, there are also some techniques we can apply to get more reliable and relevant results from ChatGPT. Still, you can't trust the results blindly, of course, but it can help you identify opportunities to improve the overall experience of your interface.
It's also crucial to understand what heuristic evaluation can and can't do. This approach helps you identify issues worth investigating before you invest in user testing, but it doesn't replace talking to actual users. It helps you apply general fundamental principles of usability, but won't solve every usability challenge you have in your specific interface.
Getting Better Results: Beyond Basic ChatGPT
If you've tried asking ChatGPT to review your website and gotten generic advice, you're not alone. To improve the relevant of the analysis, we need to steer it in the right direction.
The most effective AI-powered UX audits happen when you remove human bias from the process entirely. When you manually take screenshots, you unconsciously frame things in the best light—showing the app in its ideal state rather than how a confused first-time user might encounter it.
This is where automated approaches shine. Tools like ScoutUX automatically capture screenshots across desktop and mobile, navigate your interface with an agent that interacts with the browser, and apply Nielsen's heuristics systematically. The result is a shareable report that your entire team can use to prioritize improvements—without the weeks-long wait or consultant fees.
Not convinced? No problem, we have some tips you can apply to improve your results if you choose the manual approach.
The 3-Step Method for Better AI UX Audits
Here's how to get dramatically better results from AI-powered UX evaluation, whether you're using ChatGPT or any other AI tool.
Step 1: Set Clear Interaction Context
The biggest mistake people make is uploading a screenshot and asking "what's wrong with this page?", which opens up to a subjective and imaginative response from the AI that is not relevant.
Instead, always provide specific context about what the user is trying to accomplish. Think about the user's journey and mental state when they encounter this screen.
Good context examples:
- "A new user just signed up and is seeing the dashboard for the first time"
- "An existing customer clicked 'Add to Cart' on a green hoodie product page and now sees this checkout screen"
- "A user searched for 'project templates' and this is the results page they landed on"
This context helps AI understand not just what's on the screen, but the users expectations for the interface.
Step 2: Focus on One Screen at a Time
Resist the urge to upload multiple screenshots at once. AI performs significantly better when it can focus completely on a single interface without getting distracted by comparing different screens.
Evaluate each critical screen in your user flow separately, always providing the interaction context specific to that screenshot, as described on Step 1.
Bonus tip: uploading all screenshots of a user interaction has the upside of potentially finding consistency issues between different pages, so we recommended doing both for a complete analysis, i.e. upload the screenshots separately and then all together.
Step 3: Use Structured Prompts with Nielsen's Framework
Here's an example prompt that combines context with systematic evaluation:
"A returning customer has just clicked 'Add to Cart' on a product page and now sees this checkout screen. Evaluate this interface using Nielsen's 10 usability heuristics.
The user is a 30 years old man with high tech proficiency.
For each heuristic that has issues, explain:
1. Which specific element violates the principle 2. How this might confuse or frustrate the user 3. A concrete suggestion for improvement
Only point out visible usability problems, not potential issues that could arise depending on future interactions with the page.
Why This Method Works
This approach addresses the main weaknesses in typical AI UX evaluation:
- Objective analysis: We instruct the AI to base the report on Nielsen's heuristics, instead of making a subjective analysis
- Context prevents generic advice: AI understands who is the user and what they are trying to accomplish
- Single-screen focus improves accuracy: No cognitive overload from multiple interfaces
Putting It All Together
The difference between generic AI advice and actionable UX insights comes down to being systematic about how you frame the evaluation. By providing context, focusing narrowly, and using established frameworks, you can get remarkably useful feedback from AI tools.
Remember: this method does not replace real user research, but it allows you to stretch your UX budget and start the research on higher ground.
Ready to apply these techniques without the manual work? ScoutUX automatically implements this systematic approach, providing context-aware evaluation across desktop and mobile in shareable reports that your whole team can act on.