When we think about the future of UX, we often think about the latest technology. We see what apps have been developed and can do today, but there's an even more exciting development happening in AI—it's already being used by UX designers to improve their work. Let's explore how AI is helping UX designers find solutions for their clients' businesses and users.
How are AI and UX intertwined?
AI is a tool that can help improve UX.
It's easy to think of AI as a monolithic thing—a bit of magic pixie dust that can read your mind, download all the data it needs about you and make decisions for you. We're not there yet, but AI will be useful for UX in the future. It's possible that by 2023 we'll have a more nuanced understanding of how people use products and services and what their needs are. This can then be used by designers to create better experiences for them—and ultimately, everyone else.
Is it possible for AI to replace UX designers?
Yes, it is possible for AI to replace UX designers. In fact, it's happening now.
AI can be used to automate some tasks that are currently done by humans. For example, an AI system could tell you what features your users will find most useful and how you should use them in your design process. Another way this technology can help improve an existing product is by creating thousands of new ideas based on data from previous versions of the same product (or similar ones). This allows companies to innovate faster than ever before because they don't have time-consuming trial-and-error cycles like humans do when testing new ideas or redesigning existing products from scratch. Finally, AI algorithms may even help make UX processes more efficient—for example by predicting user behavior before they even click on something so there aren't any wasted steps required during testing stages at all.
AI can also help with repetitive tasks.
For example, if you're writing an article about the best way to cook a lasagna and you want to use data from previous recipes for inspiration, AI could help with that by applying its pattern recognition capabilities to your own recipe. It would take into account factors such as how long it took other cooks to cook their lasagnas (and what temperature they were cooking them at), what kind of meat they used, etc., then provide recommendations based on those observations. It could also easily create a vegetarian version of your favourite meat-based meal.
AI can also be helpful in analyzing large amounts of data from multiple sources at once—like customer feedback surveys or user behavior analytics—so that you know exactly where improvements are needed before launching new products or services into production. And since many companies today already have some level of analytics technology running behind the scenes anyway, this kind of analysis wouldn't require much additional investment beyond hiring someone who knows how best utilize the available toolsets available through those platforms.
AI will become an essential tool in the UX Designer's toolkit
So far, AI has primarily been used for tasks like image recognition and natural language processing—though there are some companies using it to improve usability testing methods as well. However, as more designers begin using machine learning algorithms on their own projects, they'll start realizing how powerful this technology can be when applied correctly (and also discover some interesting problems).
Conclusion
So, here's the thing: AI may not replace UX designers anytime soon, but over the next few years it will help you make better decisions when designing applications and websites.
More and more tools we use as designers (e.g., Figma) will start adding generative and testing features that utilise AI
We will be able to utilise data in meaningful ways that go far beyond the type of dashboards we're using today. Essentially, AI will be a type of new design material that we have to use in our products
From a process perspective, there will be many areas of improvement that today can cause quite a bit of friction. Usability testing, user recruitment, task analysis, analysing call centre data for insights, etc. are all areas where today's manual labor will be aided.
More code will be written by AI systems which means if we go further upstream that more design systems will eventually be AI driven as well. Humans will continue to focus on the creative parts of branding and solving problems, but generating design tokens and UI components are all something that will be handed off to the next generation of UX tools infused with AI.
