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UX Careers and Artificial Intelligence

UX Careers and Artificial Intelligence

If you have seen “careers” and “artificial intelligence” in the same sentence, it’s likely because there is yet another article wondering whether certain jobs will soon be done faster and more reliably by an intelligent algorithm.

Employers who hire UX professionals needn’t worry about their staff being replaced by programmed intelligence any time in the near future. UX jobs are anything but routine, and they involve a high level of creativity. Creativity plus the lack of routine is where UX job security lies. Even if UX jobs aren’t disappearing, however, AI will very likely have an impact on UX careers – in fact, employers should expect to soon be adding artificial intelligence (AI) and bot-related skills and experiences to job reqs.

As AI weaves its way further into products like Siri, Cortana, Google Now, Echo, and future products yet to be named or even conceived, having employees with AI experience will become more and more valuable.

For our purposes here, we’ll be focusing on how near-term future advancements in AI are likely to affect UX careers in design, content, and research.

Design and AI

Interaction design, one of several UX design careers in the digital screen-based consumer product space, is by definition focused on users and their interaction with a product. Users take an action and the system does something. The interaction may be with a “bot,” a virtual entity that listens (typically either by keyed text input or by voice) and responds. Through a back and forth communication, the response may then be further refined until completed, when the bot either performs an action or provides the needed information.

Every screen-based bot must have an interface in which it lives. The interface will need to:

  • Start up
  • Perform whatever precursors are necessary to get to the point where interaction with the AI takes place
  • Recognize initiation of the interaction with the AI
  • Allow for some back and forth discussion as a user goal is refined
  • Provide a way to acknowledge final output and perhaps continue on to other activities

In cases where users are not intending to interact with the AI, the other aspects of the interaction that are unrelated to bot-based conversation will need to “magically” make way for the AI to insert itself and provide useful information, without even being asked. (For example, your phone telling you the estimated time to drive home as you’re walking to your car.)

While many of the same skills that an interaction designer currently uses will likely be leveraged in the design of the AI interface, the new challenge for UX designers will be designing interfaces where the central aspects of the interaction are largely unscripted.

In addition, the interaction with the bot logic and functionality will itself be somewhat of a new aspect of interaction design careers. While limited algorithmic responses have been part of typical interaction design (for example a search followed by faceted refinement to get the right results), bot logic and functionality are more complex. Having employees with experience designing for these more sophisticated kinds of responses will be of exceptional value when creating new types of system interaction.

Content and AI

In addition, UX must also focus on the design of content. This impacts two types of UX content-related careers: content strategy and content writing.

A content strategist is focused on the structure of content across the organization, making sure that content is consistent in style and message, and metadata is appropriately and consistently used to frame all content. It’s already common to hear content strategy discussions around how best to chunk and tag content so that small pieces of content can be pulled in when needed. While developing a system for tagging and structuring chunks of content is part of a content strategist’s job, gaining experience with the even more refined level of chunking and tagging of information required of AI will become more critical as a job credential over time.

A content writer often writes chunks of content that get tagged in some way, but not to the granular level necessary for AI purposes. For a bot to effectively pull appropriate responses from the web as needed, content needs to be very finely chunked and written appropriately so that it works both on a webpage surrounded by related content and also potentially out of context from the rest of the page content. Additionally, if the content is written exclusively to live within an AI system, then the way that the bits of content are constructed would be somewhat different than ordinary web content. Clearly skills to develop content are valuable, but having experience with this deviation from standard content writing will be critical when hiring writers working on systems that involve artificial intelligence.

Research and AI

No matter what the designer and content writer produce, there is no question that user research will play a critical role in assuring that AI products are meeting users’ needs as expected. Understanding how power users currently use the rudimentary AI offerings of today (perhaps through ethnographic observations, in-depth interviews and focus group-based discussions) will help better inform what kind of AI should be created tomorrow. To do this sort of formative design research, a user researcher will need to have a good sense of the multitude of different kinds of AI products that are now emerging on the market in order to best frame research studies.

While usability testing of an interface that frames AI functionality may not be so different than usability testing of any kind of interface, the less predictable nature of AI responses within that interface will require a user researcher to provide flexible or perhaps more open-ended tasks without a predictable end point. Testing AI logic and response itself will require new kinds of research approaches to make sure that enough “representative responses” from a bot are appropriately presented to users and that the users are appreciative of the responses that they are getting.

While there are certainly voice-based types of research going on today, the pervasive nature of AI, and particularly AI centered around voice communication, will mean that more researchers will have to better understand what it means to recruit a representative sample of users based on certain speech criteria. So for researchers, having experience with this kind of research will be of great value to AI-based projects.

The Future Awaits

As a UXer, I’m looking forward to my first opportunities to work with the UX of truly intelligent agents, but I know that my first forays into this work will involve experimentation and adaptation. UX as a career is for people who like to experience constant newness and change – never knowing what cool design or project is around the corner. But while I know that I – and that all UXers – can adapt, employers should encourage their employees to find ways to gain a variety of AI experience now, both on and off the job to prepare for future UX needs.

About guest author Cory Lebson

Cory Lebson, Aquent UX Expert, has been a user experience consultant for nearly 20 years specializing in user research and evaluation, user experience strategy, UX training, and mentoring. Cory also greatly enjoys teaching topics related to user experience and technology. He regularly gives talks and workshops on topics related to UX career development, user experience, user research, information architecture, and accessibility. He has been featured on the radio and has published a number of articles in a variety of professional publications. He is also the author of The UX Careers Handbook (CRC Press; Taylor and Francis Group, 2016). Cory has an MBA in marketing and technology management, as well as an MA in sociology and a BS in psychology. He is a past president of the User Experience Professionals Association (UXPA) International and is also a past president of the UXPA DC Chapter. 


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