In 2022, the global artificial intelligence (AI) market was valued at USD 136.55 billion, with a projection to expand at a compound annual growth rate (CAGR) of 37.3% from 2023 to 2030 (source). Continuous and speedy innovation is also driving deeper adoption across automotive, healthcare, retail, finance, and manufacturing sectors. Within the UX space too, there has been rapid and deeper integration of AI throughout the process. From more general actions like sorting data and modifying images to more specific actions like prototyping, data analysis and testing, AI has played a role in automation for some time now. However recent advances, and the indication of what is to come (Adobe Firefly, Open AI) makes it very clear that this is no mere trend but a significant technological advancement whose moment has come.
The purpose of integrating AI into the UX process, as with automation of any kind, is primarily for improved optimisation and efficiency. By letting technology perform functions requiring logic and reasoning, trial and error, sequencing and duplicating, to name a few, the need for human intelligence is reduced. This is at play in automated customer service chatbots, predictive systems that make product recommendations based on a user’s browsing history, audio processing speed-to-text tools, and data sorting and tabulation tools.
On the other hand, this has also brought about a lot of thought around the changing nature of how we work in the UX space, and how AI could aid the future of UX design jobs. While we rely on technology to quickly learn and efficiently execute repetitive jobs, we are essentially freeing the minds and schedules of designers to allow them to turn to more complex activities that need a human element. These functions will require empathy, judgment and compassion, which perhaps no machine or technology can fully emulate. The belief is that as long as we’re designing for humans, we’ll need empathic design, therefore, we’ll need human designers.
If AI is here to stay, it’s worth looking at how it is likely to impact the nature of our work, and how we can best use it to our advantage in creating more inclusive, thoughtful user experiences.
1. Analyzing user data: instead of tediously combing through pages and pages for hours on end, tools like User Evaluation and Research AI can help speed things up. Algorithm based actions make gathering and analyzing staggering amounts of data snappy. This AI can deftly do everything a UX designer would take hours to do, like predicting user behavior, tracking page visits, picking up patterns, and further processing it to generate significant insights. Designers can use that information towards making intelligent calls about user behavior and how that might impact their interactions with a product.
2. UX and product writing: traditionally, we’re used to using dummy text to indicate where pieces of content will appear on product screens. But now, with tools like Copy AI, Writer and Wordtune is smoothening workflow and enhancing wireframes and prototypes by providing real content pieces, without a dependence on a writer. Having quick access to relevant, meaningful copy now means the gap between designing something and seeing how it will eventually look and sound is now shortened.
3. Creating user personas: Using tools like Delve, Smartone, UserPersona.Dev along with the AI powered data gathering, designers can now create user personas that are data-driven, insight-backed in half the time it would probably take to do it manually. This can make for quicker, efficient, impactful design interventions.
4. Automated workflows: you guessed it, there are also tools for streamlining workflows now, such as FlowCharts, Brainpool, which can reduce the effort spent in inputting repetitive features and organizing design elements by recognising existing patterns, thereby freeing up a lot of mindspace for a UX designer.
5. User-testing and prototyping: Ultimately, products are only relevant if they’re useful to a user, and this is where user testing is invaluable. In order to iterate and tweak aspects of the design to make it relevant, tools like Visualeyes can help with understanding and recognising user patterns through algorithm-based simulations. Flexibility in creating a spectrum of input scenarios and testing them out efficiently, to gather data and feedback around how a user might experience a product is at the heart of effective design, at the end of the day. And this entire process can be much smoother and less time consuming.
I cannot overstate the fact that AI intervention, as it stands today, can be immensely beneficial for the UX design process if wielded intelligently in making our lives easier. However, our jobs should depend much more heavily on the deep and empathic understanding of what human beings need or what motivates them to use a product and interact with it.
Tools, algorithms and other technological wizardry can definitely help us do things faster, smarter and thereby more cost effectively, but creating useful, delightful products that make a difference to human beings and keep them coming back for more requires human interaction, understanding and empathy at the heart of it. Technology may not be able to entirely replicate this for a long time to come. The landscape of the UX process and how we work is changing, and how we can leverage AI and steer our career paths is a discussion worth having. But that’s a topic for another blog!