Artificial intelligence has been the biggest tech buzzword of the last few years. The idea of AI sometimes is daunting and reminiscent of science fiction, but it’s rapidly becoming integrated into different products and into the daily lives of many people. The more obvious examples of AI include Amazon’s Alexa, Apple’s Siri, Google Home and Nest, but email apps, ride-sharing apps and streaming services all have artificial intelligence components to their products and services.
AI also has the capability to make design smarter and more intuitive. And ultimately, combining the two will only lead to a more effective, human-centric user experience. As Justin Baker of Muzli says, “AI-driven UX leverages intelligent computing to simplify and augment human-centered experiences by catalyzing decision-making, efficiency, intelligence, and delight.” Companies are using AI to strengthen their UX in a variety of ways. Here are a few examples of such techniques that have been executed successfully:
With AI’s data processing capabilities, systems can collect much more detailed information about users — such as the products they like and how long they spend looking at a specific page or product — and use that to build personalized algorithms. Hyper-personalized algorithms are more likely to lead to conversions. In fact, 75% of Netflix’s views are solely from the personalized recommendations they offer on the streaming service.
Providing Real-Time Assistance
Artificial intelligence allows chatbots and other virtual assistants to have more natural, human-like conversations with users. AI also can help identify behaviors that would indicate a customer is about to exit a site page or drop a task, which would allow chatbots to pop-up and provide real-time help instead of waiting for the user to initiate the interaction. Better UX and customer satisfaction? This one is a win-win.
Since AI has an exponentially higher data processing capability than humans, it can be used to evaluate many UX metrics regarding user behavior during the product testing phase. Some such metrics include session time and length, bounce rates, user flow, location of users and device used. And since AI relies on hard data, applying it during processes like A/B testing also eliminates potential biases.
A lot of the design wireframing and prototyping process can be automated with the use of AI. Designers will still oversee conception, strategy and management, but AI can take care of more minor production tasks, such as cropping, contrast adjusting and even cleaning up sketches and models. There are even tools that directly turn sketches into working prototypes, making the behind-the-scenes work of a designer much more efficient.
Without a doubt, AI is going to change the future of UX design. Whether it’s by making behind-the-scenes design work more efficient, creating a more personalized consumer experience or decreasing bias during testing, AI will become a part of your company’s UX process, if it hasn’t already. How is your company or team combining UX and AI? Let us know in the comments below.