What every UX practitioner should know in 2026
Reflections on what shapes strong UX practice in the age of automation.
Our roles in product are going through an evolution. We’ve heard it time and time again that researchers can whip up prototypes, product managers can ship code, designers can run studies. We always hear “How are you using AI?”, “How should you use AI?”, but the question we’re exploring is what is happening to our human skills when the process is automated?
We put a question out to our community ahead of Research Week to define what the most essential skills for UX professionals are in 2026.
1. Sensemaking
“Humans are messy and ever-changing. Sense making — to inform why a thing should be, not just what things should be — will remain a most critically important and meaningful kind of design literacy.”
— Michael Palmyre, xuko
Some may call it a corporate buzzword, but it’s foundational. When AI can generate artifacts and surface patterns at speed, the job becomes less about production and more about meaning and value. This means navigating the nuances and constraints your systems are missing and working cross-functionally between business and product.
“AI is making it much faster to produce artifacts, flows, ideas, and variations. But the skill that matters most for UX professionals right now is still the ability to connect nuance, user needs, business goals, constraints, and signals from different places, then turn that into the right product decisions. To me, that sense-making ability is still deeply human, and it is where UX can create the most value.”
— Bear Liu, Bear Design
2. Judgement
“A consistent theme I’m seeing through coaching is the value of judgement. With more AI, data and tools than ever, knowing what to use, when, and owning the decision is what really matters.”
— Meera Pankhania, Propel Design
Access to more tools, more data, and more outputs doesn’t simplify decision making. In many ways it complicates it. It’s about using your judgement to make a considered call about what fits the situation given the risk, data, resources, and goals.
3. Orchestrating the invisible threads across people and systems
“In an AI world, UX shifts from execution to defining intent. Designers must guide AI systems, collaborate across disciplines, and use their unique design lens to ensure we solve the right problems.”
— Costanza Volpini, Logitech
If you think of the classic DVF framework, user experience holds closely to the desirability component. Our work has and always will be about creating desirable solutions and upholding users through sprints, roadmap planning, and the apparatuses of horizontal and vehicle innovation. Through translating and embedding design thinking into organizational structures, UX practitioners work across people, processes, and systems to orchestrate cross-functional collaboration across layers and protect intent as it moves through layers of automation.
“Translation is the UX superpower for the age of agentic AI. As agentic AI drives tech-led service design, UX must bridge human needs and AI solution design — protecting intent so speed doesn’t replace the experience.”
Value emerges from the way we connect intent, systems, and machine capabilities.
“Beyond the AI craze, our value lies in orchestrating the invisible threads of people, process, and systems. By designing the conditions for humans and machines to coexist, we turn automated chaos into meaningful value.”
— Michael Tam, Joyventure.io
4. Communication
“The ability to communicate an idea in its simplest form.”
— Tom Holloway, Clarus
It’s easy to underestimate this. The ability to take something complex and make it legible to the people who need to act on it is a real skill, and it shows up not just in words, but in visualizations and in how insights are packaged and shipped.
5. Humility
“Humility gives empathy its staying power, shifting our focus beyond short-term outcomes and inspiring us to create work that stands the test of time.”
— Sachi Taulelei, Humble
In a field that’s under pressure to move fast and demonstrate value quickly, this is a useful counterweight. Humility keeps a researcher honest about what they know and what they don’t. It keeps the focus on the people being designed for and the people who work with you along the way, rather than on the outputs being produced.
What this adds up to
None of these skills are new and that’s the point. What’s shifted is how clearly they stand out when more of the surrounding work gets automated. When AI handles more of the production, the pattern recognition, and the synthesis, what remains is the part that requires being human, sitting with complexity, orchestrating the invisible threads, making considered decisions, communicating clearly, and staying genuinely curious about the people at the center of it all. This mindset is what shaped how we approached Optimal 3.0.
What skills are you doubling down on in 2026?
