Summary: UX professionals who are good at all steps of the UX lifecycle, including both research and design, are called “UX unicorns” because they are rare. But AI narrows skill gaps and may create many more UX unicorns.
I always used to be very skeptical of the idea of the “UX unicorns” — individuals who can do all the various parts of the user-centered design lifecycle, from qual & quant user research to all the different kinds of design (visual, interaction, IA, writing and content strategy, etc.). My anti-unicorn spiel went as follows:
The actual unicorn (shown below) is a mythical beast, and so is the UX unicorn. People who are good at everything don’t exist.
Realistically, a generalist will, at best, deliver a mediocre product, compared with a product developed by a set of specialists because each specialist will be superior at his or her special skill relative to the mid-level skill possessed by a good unicorn. At worst, you get somebody who claims to be a unicorn but is lousy at several (or all) of the claimed skills, and then you don’t even get a mediocre product but a bad one.
Unicorn by Midjourney. This animal doesn’t exist.
Unicorn UX professional: somebody who can do all steps of the UX design lifecycle, with great skill at all our many methodologies. Hard to say how many people like this exist outside of Dall-E’s cartoon world.
However, I am rethinking my unicorn position based on a recent post by Ronnie Battista reflecting on his job search experience. Battista points out that AI is uplifting specialized craft skillsets, leading to more demand for UX staff with a comprehensive skill set. He recommends, “for both new and seasoned practitioners, actively delving into tools and methodologies beyond their core competencies is crucial to amplify their value.”
It is indeed one of the 4 core facts about AI that AI use narrows skills gaps. This has been found again and again in virtually all the empirical studies comparing the performance of knowledge workers with and without AI. All business professionals benefit from using AI, and the top performers get even better with AI assistance. But their performance doesn’t improve nearly as much as that of the low performers. In other words, whereas the difference between good and bad professionals is vast without AI, it becomes more narrow when all workers benefit from AI assistance.
The skill gap between high and low performers isn’t eliminated by AI, so it still behooves you to hire the best staff you can get. But hiring a top performer isn’t as critical as it used to be.
(Since I mentioned 4 core facts that have been proven by countless empirical studies of AI, let me list the remaining 3 AI facts: AI immensely increases productivity, it improves the quality of the work product, and it enhances job satisfaction for those employees who use AI.)
The narrowed skill gap leads to better unicorn performance, exactly because of my previous point: that a unicorn will never be the best at any one skill compared with a specialist who has spent his or her entire career honing that single skill. With AI, the gap between these two workers isn’t that big. The unicorn benefits from superior communication and coordination since all steps of the design process are contained within a single brain. Knowing things from having done them yourself beats sitting in any number of team meetings or reading even the best journey map or persona descriptions.
Having complete information about all the design process steps kept within a single human brain eliminates communication overhead and misunderstandings and is a key reason to employ a unicorn UX professional. (Dall-E)
Remember that the skill gap is only narrowed, not eliminated entirely. This means that for the most demanding and critical design projects, it still pays off to hire specialists. But most projects are not actually that critical, nor are they groundbreaking and need the keenest of insights. Most design projects are rather pedestrian: make one more website or one more payroll system. Unicorns may rule this world of the 80% of design projects that will be perfectly fine with decent design.
The big change is as follows:
Without AI: UX unicorns = mediocre design
With AI: UX unicorns = decent design
This means that the projects that can (and maybe should?) be done by UX unicorns increase from the least challenging 20% of the world’s design projects to 80% of the world’s design projects.
The 20% most challenging or important design projects still need specialists, though.
AI narrows the gap in performance between high-skilled knowledge workers and their low-skilled colleagues. (I think what Dall-E is aiming for in this visualization is that the child-like person on the left is supposed to be the low-skilled worker.)
Rethinking the Future of Work
In my article on the big productivity increases for office workers using AI, I mentioned that the biggest gains are yet to come because they will result from reorganizing the way work is done and restructuring corporations accordingly.
A great analogy is the impact of electricity on factories.
Before Electricity:
Central Power Source: Factories typically relied on a central steam engine. This large, stationary power source drove all the machinery in the factory through an elaborate system of shafts, belts, and pulleys.
Layout Constraints: Because all machines had to be physically connected to the central power source, the layout of the factory floor was heavily constrained. Machinery was often arranged in long rows to align with the shafts and belts emanating from the steam engine.
Transmission of Power: The mechanical power was transmitted from the central steam engine to the machines via overhead shafts and belts. This system was not only space-consuming but also posed safety hazards and limited the placement and mobility of machinery.
Limited Flexibility: The layout was less flexible, and reconfiguring the production line was a significant undertaking. This setup favored mass production of a limited range of products rather than adaptable, diverse manufacturing.
Energy Inefficiency: There was a considerable loss of energy in the transmission of power from the central engine to the individual machines, leading to lower overall efficiency.
After Electricity:
Individual Electric Motors: With the introduction of electricity, factories began to use individual electric motors at each workstation. This decentralized the source of power and allowed for greater flexibility in factory layouts.
Flexible Layouts: The need for physical connection to a central power source was eliminated. Machinery could be arranged according to the most efficient workflow, rather than being constrained by the location of the power source.
Increased Safety and Efficiency: Electric motors were safer and more efficient. They eliminated the hazardous belts and pulleys of the steam era and reduced energy loss in power transmission.
Adaptability to Different Products: The new layout allowed factories to easily reconfigure production lines to accommodate different products, supporting more diverse and adaptable manufacturing processes.
Enhanced Control: Electric motors offered better control over the speed and power output for individual machines, leading to improvements in both productivity and product quality.
Centralized steam power vs. decentralized electric motors led to different ways of organizing the factory floor and the manufacturing process. (Dall-E)
In summary, the shift from a centralized steam engine to distributed electric motors revolutionized factory floor organization, enhancing safety, efficiency, and flexibility, and paving the way for modern manufacturing practices.
None of these benefits would have resulted if factories had simply replaced their steam engine with a single gigantic electric motor in the same location and kept the system of shafts, belts, and pulleys in place to distribute its power. The factory would have saved some money on coal and have realized some productivity gains from needing fewer workers to clean and maintain the new motor, but that’s all. Rethinking the way work was done also allowed rethinking the function of corporations, for example by introducing broader product lines due to improved manufacturing flexibility.
It's only an analogy, but I believe the introduction of AI in business will have similar effects to that of introducing electricity in factories. The biggest gains will come from restructuring work and companies, not from improving existing work practices, much as they will definitely will be better with AI.
The possible reemergence of the UX unicorn is one example. Yes, each individual step in the UX process will be 40%–100% more efficient when UX professionals are aided by AI. But the reduction in communication overhead by keeping everything within a single brain might easily add several hundred percent in additional productivity gains.
Having the info reside in one brain causes huge efficiency gains, eliminates misunderstandings, and removes the eternal curse for UX of needing to establish credibility for our work. If this guy ran the usability study himself, he’ll believe the findings when it comes to creating the design. (Dall-E.)
That’s changing the way UX work is done: from many specialists who have to communicate and exchange endless documents, to individual generalists who keep all the information in their brain.
Then we get to changing the way businesses operate. Increased UX efficiency, particularly at smaller scale might lead to embedding these UX unicorns much more tightly in many more places, so that everything the company does is infused with UX goodness. AI might finally realize the “user-centered corporation” which I envisioned as the highest level of my original UX maturity model decades ago, but which we never used to see in real life.
AI may finally realize my vision of the user-centered corporation with UX infused everywhere as organizations restructure according to new and more efficient workflows, also for UX work. Much happiness to ensue! And higher business profits, because UX works. (Dall-E)
About the Author
Jakob Nielsen, Ph.D., is a usability pioneer with 40 years experience in UX and the Founder of UX Tigers. He founded the discount usability movement for fast and cheap iterative design, including heuristic evaluation and the 10 usability heuristics. He formulated the eponymous Jakob’s Law of the Internet User Experience. Named “the king of usability” by Internet Magazine, “the guru of Web page usability” by The New York Times, and “the next best thing to a true time machine” by USA Today. Previously, Dr. Nielsen was a Sun Microsystems Distinguished Engineer and a Member of Research Staff at Bell Communications Research, the branch of Bell Labs owned by the Regional Bell Operating Companies. He is the author of 8 books, including the best-selling Designing Web Usability: The Practice of Simplicity (published in 22 languages), Usability Engineering (26,471 citations in Google Scholar), and the pioneering Hypertext and Hypermedia (published two years before the Web launched). Dr. Nielsen holds 79 United States patents, mainly on making the Internet easier to use. He received the Lifetime Achievement Award for Human–Computer Interaction Practice from ACM SIGCHI.
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