A feature is not useful just because it is intelligent
An AI feature can produce impressive output and still fail to help someone complete a task. The interface might hide the feature, explain it poorly or introduce uncertainty at exactly the moment a customer needs confidence. Product design has to connect the capability with a recognisable purpose.
Nielsen Norman Group’s research on the discoverability of AI features illustrates this gap. People do not always notice or find a capability simply because the business has added it. That is a useful reminder to evaluate the whole experience, not just the quality of a model response.
Explain the job before asking for a prompt
A blank prompt box transfers a lot of work to the user. They have to understand what the system can do, decide what to ask and guess what detail is needed. A more useful starting point is a specific task, such as comparing products or organising a project brief.
Use familiar language and task-based examples. Show the kind of result a customer can expect without making promises the system cannot keep. The goal is not to teach everyone prompt engineering. It is to make a relevant next action understandable.
Confidence is not the same as correctness
Fluent wording can make a generated answer look more certain than it deserves. Design should not hide that distinction. When an answer depends on sources, show where it came from. When the result is a suggestion rather than a decision, label it accordingly.
Give people a practical way to check, edit or reject the result. A product recommendation should leave room to inspect the product. A generated project plan should remain editable. The interface needs to support judgement rather than asking customers to trust an opaque answer.
Recovery belongs in the first design pass
Think about what happens when the feature returns an irrelevant answer, cannot respond or needs more information. A retry button is only one part of recovery. Sometimes the better route is a normal search, a manual control or a conversation with a person.
Write error and empty states as part of the product, not as housekeeping at the end. Preserve useful input where appropriate, explain what happened safely and provide an alternative next step. A good experience remains usable when its AI capability is unavailable.
Measure the task, not the novelty
A feature can attract clicks because it is new. That does not establish that it saves time or improves a customer decision. Observe whether people find it, understand it and complete the task more successfully with it. Include the effort spent correcting the output.
For teams in Australia, New Zealand, the UK and USA, these questions translate across markets, but the answers will depend on the product and audience. Scott Design Studios approaches AI as part of a broader product journey. Start with the problem worth solving, then decide whether AI is the right interaction for it.