Rute Cotrim
May 27th, 2026
UX has always been about understanding people. The best digital experiences succeed because, somewhere behind the interface, there is human empathy shaping the paths and decisions.
In 2026, many companies are quietly replacing understanding with automation. AI will create more products, faster and cheaper. But will it scale the way people expect it?
The promise of AI is efficiency. It can generate interfaces, write microcopy, personalize flows and even predict user behavior. For businesses, this feels like a natural evolution: why would we rely on expensive human processes when machines can iterate endlessly and quicker? But there's something important. UX has never been just about output, it is about interpretation. And that requires context, nuance and judgement.
The Illusion of Understanding
One of the biggest challenges emerging in AI-driven UX is the illusion of understanding. Just because AI can mirror tone and anticipate some needs, this doesn't necessarily mean there's comprehension. When systems rely too heavily on patterns (rather than meaning) they risk creating experiences that feel polished but disconnected.
A quieter shift will happen on the user side as well, with changes that can have serious implications on our future way of thinking. AI systems take over more cognitive effort and people are asked to do more while thinking less. And, don't get me wrong: this doesn't mean people will become less intelligent, but there will be a significant drop in terms of engagement. When every decision is assisted and every answer easily generated, critical thinking will slowly atrophy. This challenges some of the most fundamental UX principles. When systems anticipate and do too much by themselves, users working on building products with the help of AI rely more and more on default acceptance and validation turns into a boring task. But due to the numbers, this is something to be truly aware of.
Recent data from Figma shows that 34% of designers and developers shipped an AI-powered product in 2025, up from 22% the year before. This is a clear sign that AI is moving faster from experimentation to actual production. At the same time, 56% of teams report that AI is being integrated into already existing products and 43% are already building entirely new AI-native experiences.
Curious enough, only 40% of designers say AI actually improved work quality, despite its rapid adoption by companies.
Where do Fundamentals stand?
This year (2026), UX Designers are even more responsible not just for usability but for preserving user agency as AI-driven products become more and more common. Many products are now being designed by people outside the Design scope or/and who may not have a strong grounding in UX Fundamentals. When speed becomes the priority, it is easy to skip the discipline needed to make products trustworthy in the first place.
This is where organizations need to carefully think about Team Restructuring vs AI capabilities. When fewer people are responsible for interpreting user needs, replacing that by automated systems, the AI process doesn't just reduce costs. Heuristics and Accessibility will risk being treated even more as compliance steps, a checklist to pass and not a lens through which experiences definitely need to be built. UX success metrics are also unknown to people building products with no fundamental knowledge. In the end, who even knows who Jakob Nielsen is anymore?
Every Good Strategy is human: so…will it backfire?
Designers must reclaim their power as decision-makers. Responsible design is not just an optional topic. Either we like to hear it or not, UX is also intrinsically linked to the commercial success of every product as it shapes how users understand value, build trust and, ultimately, also how they convert and advocate for the product. As a big part of every strategic decision, companies need to think long-term about the possible side-effects of a weakened human-side in product creation. UX has always been, and will continue to be, a negotiation space between what's desirable for the user, viable for the business and feasible technologically. This balance is the key for true success and a high organization maturity at all levels will be so important from now on.
And the devil in the room, as almost everyone already understood, is not the tool. While we can make use of powerful AI systems to accelerate processes and iterate better, designing for everyone still requires context and it's on us humans to recognize exceptions, not only patterns. That's where companies can win: treating AI not as a replacement but as an opportunity of collaboration. But the recent new wave of layoffs has created a broader workforce disruption.
According to Forrester, 55% of employers report regretting workforce reductions made in anticipation of AI capabilities that have not yet fully materialised.
This reflects a growing pattern: companies making structural decisions based on projected AI performance rather than proven outcomes.
While some organisations are now reconsidering or partially reversing these decisions, the adoption of AI is also reshaping job distribution across the market. Entry-level roles are becoming increasingly scarce, particularly in “AI-exposed” fields, where automation is replacing tasks traditionally assigned to junior profiles. What many companies are overlooking is this: while AI can significantly accelerate execution, expertise remains essential. This ties directly to the need for experienced human knowledge, empathy and vision.
In a recent Forbes article, citing a Robert Half report, a clear pattern is emerging in how companies handle post-layoff recovery. According to the findings, organizations typically take between 6 and 12 months to fully assess the operational impact of large-scale layoffs.
29% of the companies have already rehired into the positions they had previously cut. The hidden cost of these risky decisions always shows up with delay.
MY MAIN TAKEAWAY
The strongest companies will be the ones that understand where AI enhances the process without totally replacing people. The weakest will be those that confuse efficiency with quality and output with thinking. Right now, they may move faster but, over time, clarity, trust and designing for everyone beyond the average user will get lost, possibly resulting in one of the most significant UX and operational challenges seen in the technology world.
From my experience, designing for the average user has never been enough to win. Extending that mindset to other fields, aiming for "average" but faster outputs, will inevitable weaken results with time and dilute competitive advantages.
What's my Design stack?
From research, to designing and testing: Adobe Suite, Figma, Zeplin, Framer, Storybook, Typeform, Balsamiq, Lookback, Sketch, Lighthouse, WAVE, Silktide.
What's my tech stack?
I know HTML, CSS and JavaScript. CSS is a big passion of mine and I already worked with both Sass and Less. I've developed my skils on TypeScript, having worked with Angular 2+ in several projects and on Blazor as well. I would prefer to focus on the UX/UI side and give a little help on the development side if needed. I love to bring my knowledge to bridge the gap between teams and do a seemless delivery.
Where am I based?
I am based in Lisbon, Portugal - even though I am currently collaborating with teams from other countries, from a nearshoring perspective.