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The rise of generative AI in 2023 has been prominent, with significant progression in tools like OpenAI’s ChatGPT and Google’s Bard. And of course, there are obviously several resources online that boast about the capabilities of these tools. However, what does that mean for UX designers? How can we put these AI tools to use in our real-world work, keeping practicality and effectiveness at the center?

Here are the top 5 real-world applications of generative AI that I have explored in the past few months and found useful.

1. Research problem space

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The very first step that UX designers engage themselves in is understanding the problem space. In most cases, this can include browsing through existing documentation and resources, especially when we don’t have a lot of knowledge about the domain. It is fair enough to say that searching on Google can sometimes be tedious. Browsing through different search results, clicking on one blue link, being unsatisfied with the content, coming back and exploring other blue links is almost an endless cycle. And there is no doubt that we all have done that.

I have found that generative AI can be useful for this task. Carefully crafting the prompt to include the role, the goal, and the problem space can lead to a good result. Instead of browsing through several links and figuring out information, this method can help us get an understanding of the problem space in a shorter amount of time.

2. Research target audience

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User research, again, is a crucial component in the UX process. Sometimes, conducting exhaustive user research can be challenging due to multiple reasons such as lack of time, availability of participants, funding, etc. Even though the ideal and probably the best way to conduct user research is going through the route of contextual inquiry and all the other stuff, it is not possible all the time. UX designers often try to conduct user research using alternate methods.

Using generative AI to research about target audience, and even potentially simulating user research is a beneficial technique. To do this, it is important to write the prompt in as much detail as possible. It is advisable to mention as much known information possible in the prompt, along with the product or service information. Furthermore, specifying the format of the user research results and other relevant details can make the prompt more refined, leading to more specific and insightful output.

3. Generate personas

Source: NN Group

User personas, one of the many models in contextual inquiry process, help UX designers visualize their target audience and relevant information at a high level. The use of personas can be debatable, with different people having varied opinions about the efficacy. I won’t go into that discussion here. If you feel that personas are relevant for your work, then go ahead and create them.

I have observed that generative AI is really effective in creating user personas. This can be save a lot of time for UX designers. The key to generating a good and refined set of personas is to specify the details about the problem area, the product or service, the scenario (if possible), and the different fields to be included in the personas.

4. Brainstorm design ideas

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Brainstorming and generating several design ideas before concretely finalizing one of them is a common practice among UX designers. This task can be made more efficient if there is a group of cross disciplinary UX professionals together, as they bring in a varied set of ideas and perspectives to the table. And as we know in the UX process, the more number of ideas, the better.

It never hurts to ask generative AI for some ideas. After all, it’s take-it-or-leave-it kinda thing. The success of generating several unique and revolutionary ideas can vary, depending on the problem space. However, it never hurts to try. Making the prompt particular with problem domain, product details, scenario, and expected outcome will yield good results.

5. Naming stuff

Source: Knapsack

As much someone might like it or not like it, this is one of the tasks that UX designers have to do as a part of their work. Whether it is naming colors, type styles, features, apps, and what not — it all requires some sense of creativity that goes well with certain amount of logic. And we all know, there are times when we have other ‘important’ things to cater to, and naming, even though important, can hit the sidelines.

Generative AI is almost like an assistant to us. Why not ask for some suggestions? All we need to do is describe the situation, give context, and that’s it. These AI tools will instantly list a bunch of suggestions for naming almost anything and everything. As usual, specifying the format can help further.

And there you have it! Tried and tested uses of generative AI tools to make your life as a UX designer a little easy.

Generative AI for UX designers: 5 Real-world Applications I’ve Explored was originally published in UX Planet on Medium, where people are continuing the conversation by highlighting and responding to this story.