What are the best practices for developing user-friendly AI applications?

AI is a piece of technology that has the potential to solve user problems. So the fundamentals of product building doesn’t change. Start with the user and problem hypothesis, and validate it by running experiments(even if through non-scalable means like manually solving it problem. Look up wizard of oz ) . Once you’ve done that, you’ll most likely have a problem-solution fit and a clear view of your user needs / jobs. Start automating at this stage. Otherwise you might end up with a solution looking for a problem than the other way around.

Developing user-friendly AI applications starts with defining user needs. Understand who your users are, what problems they face, and how AI can assist them. User research, surveys, and feedback are invaluable. Design your AI with the user's perspective in mind to create a more intuitive and helpful experience.

From my experience, I would say before we start developing AI based app for any company / organisation, we must study their legacy system and business process. After all we will implement AI that will not only automate their business process but also saves time and money. Developing bridge (Data Connectivity) between legacy system and newly developed app should also take into consideration as it will enhance the usability, accessibility as well as overall performance.

Your users are the only thing that matters. Identify their pain points and goals through direct conversations, not just data points. Opt for in-depth interviews over generic surveys. Real insights often come from nuanced discussions. Be attentive. Users may not explicitly state their needs, but their behavior and feedback will. Use this to refine your AI's functionality. Bottom line: Know your users intimately. This isn't a box-ticking exercise; it's the bedrock of your AI application. The better you define their needs, the more user-centric and effective your AI will be.

Start with wireframes and mockups, but don't stop there. Test these early designs with actual users. Their feedback is gold; mine it. Be transparent about your AI's capabilities. No one likes a show-off that can't deliver. Clearly indicate what the AI can and can't do, and provide real-time feedback to guide user actions. Let users feel in control. Offer customization options to adjust AI behavior. And when errors occur—because they will—handle them gracefully. A well-designed error message can turn a moment of frustration into an opportunity for engagement. In short, your UI should be a clear, intuitive roadmap, not a maze. Make it so, and you'll have a user-friendly AI application.

UX isn't just a buzzword; it's the lifeblood of your AI application. You've built it, but will they come—and more importantly, will they stay? Kick off with usability testing. Get real users to navigate your AI and watch them like a hawk. Are they stumbling or breezing through? Take notes. Metrics don't lie. Track user engagement, task completion rates, and bounce rates. If numbers are sagging, your UX probably is too. In a nutshell, evaluating UX isn't a one-off task. It's ongoing, like a fitness regimen for your AI. Keep it in shape, and it'll serve your users well.