17 Dec 2025
|14 min
UX research trends 2026
Discover the top UX research trends for 2026 from 100 researchers.
We surveyed 100 UX researchers to find out which trends they think will have the most impact in 2026. From AI-assisted analysis to research democratization, here's what the data revealed about the future of UX research.
Understanding where UX research is heading helps you prepare for what's next. Whether you're looking to upskill, advocate for research in your organization, or simply stay current with industry shifts, knowing what your peers are focused on can guide your decisions.
We used the Lyssna research panel to survey 100 UX researchers. We asked them about the trends they see shaping the field, how they're currently using AI, their predictions for 2026, and the biggest challenges they're facing right now.
Key takeaways
AI dominates the trends: 88% of researchers identified AI-assisted analysis and synthesis as a top trend for 2026, making it the most anticipated development in the field by far.
Synthetic users are gaining attention: Nearly half (48%) see synthetic users and AI participants as impactful, though many express skepticism about whether they can replace real user research.
Research is democratizing: 36% identified research democratization as a key trend, with non-researchers increasingly conducting research – raising both opportunities and quality concerns.
ROI remains the top challenge: Despite new tools and methodologies, 25% say proving the value and ROI of research is still their biggest challenge.
Speed vs quality tension persists: 21% struggle with balancing the pressure to move quickly with maintaining research rigor, a challenge that AI may both help and complicate.
Human judgment stays essential: Researchers predict AI will handle data processing while humans focus on empathy, strategy, and interpretation – suggesting the profession is evolving, not disappearing.
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Top trends shaping UX research in 2026
We asked researchers to select their top three trends from a list of 10 options. Here's what they told us, ranked by how many researchers selected each trend.
Trend | Percentage |
|---|---|
AI-assisted analysis and synthesis | 88% |
Synthetic users and AI participants | 48% |
Research democratization (non-researchers doing research) | 36% |
Research repositories and insight management | 29% |
Strategic positioning of research in organizations | 27% |
Continuous discovery approaches | 26% |
ResearchOps and scaling research | 25% |
Accessibility-first research practices | 22% |
Multimodal research methods | 20% |
Longitudinal/always-on research methods | 14% |
AI-assisted analysis and synthesis
Nearly nine in 10 researchers (88%) identified AI-assisted analysis and synthesis as one of the top trends that will impact UX research in 2026. This was by far the most selected trend in our survey, showing just how central AI has become to research workflows. (This was also reflected in our report on how teams are synthesizing research.)
When we asked researchers how they currently use AI in their work, the responses showed widespread adoption across multiple tasks:
AI usage | Percentage |
|---|---|
Analysis and finding patterns | 23% |
Other | 23% |
Transcription and note-taking | 21% |
Writing research deliverables (reports, summaries) | 13% |
Synthesizing insights from multiple studies | 8% |
Creating research materials (guides, surveys) | 7% |
I don't use AI in my research work | 5% |
One researcher explained how they see AI fitting into the research process: "AI will handle the 'what' (data processing and pattern recognition), while human researchers will drive the 'why' and 'how' (empathy, strategy, and judgment) of the user experience."
Another predicted that "UX research in 2026 will increasingly rely on AI-assisted analysis, where researchers combine human insight with AI-generated patterns and summaries to speed up decision-making and handle larger volumes of data."
But not everyone is entirely optimistic about AI's growing role. Several researchers expressed concerns about overreliance, quality control, and the environmental impact of AI tools. As one researcher put it, "AI will be overused and the gaps will be found and documented."
Synthetic users and AI participants
Nearly half (48%) of researchers selected synthetic users and AI participants as a trend that will impact the field in 2026. This makes it the second-most anticipated trend after AI-assisted analysis.
Synthetic users offer the promise of faster testing cycles, broader reach, and reduced costs compared to recruiting real participants. However, researchers' predictions revealed significant skepticism alongside the enthusiasm.
One researcher bluntly predicted that "synthetic users will turn out to be a bust," while another warned about "AI used by non-researchers with results that are not checked/confirmed."
The concern seems to center on whether synthetic participants can truly replicate the nuance, context, and authentic reactions of real users. While synthetic users might work for certain types of testing, many researchers question whether they can replace the empathy and understanding that comes from observing real people.
Research democratization
More than a third (36%) of researchers identified research democratization – where non-researchers conduct research – as a trend that will impact the field in 2026.
One researcher predicted that "a specific specialization in research might not be needed as everyone will do it with AI." Another noted they expect to "see more research democratization and 'people who do research.'"
The democratization of research presents both opportunities and challenges. On one hand, it can help organizations move faster and embed user-centered thinking across teams. On the other hand, it raises concerns about research quality and methodology.
One researcher expressed worry about "AI used by non-researchers with results that are not checked/confirmed," highlighting the risk that comes when people without research training use powerful tools without understanding their limitations.
Research repositories and insight management
Nearly three in 10 researchers (29%) selected research repositories and insight management as an impactful trend. As organizations conduct more research and gather more data, the ability to organize, store, and surface past findings becomes increasingly important.
This trend connects closely to research democratization – as more people across organizations want to access research insights, having a centralized repository becomes essential. It also relates to proving the value of research, as repositories can help demonstrate the impact of research over time.
Strategic positioning of research in organizations
Just over a quarter (27%) of researchers identified the strategic positioning of research in organizations as a key trend. This suggests a shift from research being purely tactical to playing a more central role in business strategy.
One researcher predicted that "UX research will be known by a lot of people and they will understand the value of having UX research in the organisation." This optimistic view contrasts with the reality that proving research value remains the top challenge researchers face (which we'll explore below).
Continuous discovery approaches
Just over a quarter (26%) of researchers selected continuous discovery approaches as an impactful trend. This represents a shift from research being conducted as discrete projects to becoming an ongoing, integrated part of product development.
Continuous discovery aligns with agile methodologies and the need for teams to make faster decisions based on user feedback. Rather than waiting weeks or months for formal research studies, teams can gather and act on insights continuously.
Other notable trends
Several other trends received meaningful support from researchers:
ResearchOps and scaling research (25%)
Accessibility-first research practices (22%)
Multimodal research methods (20%)
Longitudinal and always-on research methods (14%)
The biggest challenges facing UX researchers
While researchers are optimistic about new tools and methodologies, they're also dealing with persistent challenges. Understanding these pain points helps contextualize how trends like AI adoption might serve as solutions – or potentially create new problems.
Challenge | Percentage |
|---|---|
Proving value/ROI of research | 25% |
Balancing speed with research quality | 21% |
Getting stakeholder buy-in | 20% |
Keeping up with AI and new tools | 12% |
Scaling research across the organization | 11% |
Managing and sharing insights effectively | 10% |
Proving value and ROI of research
A quarter (25%) of researchers identified proving value and ROI as their biggest challenge. Despite AI tools and new methodologies, demonstrating the business impact of research remains difficult.
This challenge connects directly to the trend around strategic positioning. Until research leaders can clearly articulate how research drives business outcomes, securing resources and executive support will continue to be an uphill battle.
Balancing speed with research quality
Just over one in five researchers (21%) said balancing speed with research quality is their biggest challenge. This tension has likely intensified as AI tools promise faster insights and organizations demand quicker turnarounds.
One researcher captured this concern, warning about the pressure to move quickly potentially compromising research rigor. The challenge is finding ways to work faster without cutting corners that undermine the validity of findings.
Getting stakeholder buy-in
One in five researchers (20%) identified getting stakeholder buy-in as their biggest challenge. This relates closely to proving ROI – if stakeholders don't understand or value research, they won't support it with time, resources, or attention.
Several researchers mentioned this challenge extends beyond just securing budget. It includes getting stakeholders to participate in research activities, act on findings, and integrate research into decision-making processes.
Keeping up with AI and new tools
Just over one in 10 researchers (12%) said keeping up with AI and new tools is their biggest challenge. The rapid pace of technological change means researchers need to constantly evaluate new tools, learn new skills, and determine which innovations are worth adopting.
As one researcher noted, there's a concern about "falling behind" as AI capabilities expand. This creates pressure to stay current even as researchers juggle their core responsibilities.
Other challenges
Additional challenges mentioned by researchers include:
Scaling research across the organization (11%)
Managing and sharing insights effectively (10%)
What researchers predict for 2026
We asked researchers for their predictions about UX research in 2026. Their open-ended responses revealed several themes about how they see the field evolving.
AI will be everywhere (but concerns remain)
The most common theme in predictions centered on AI's growing presence. Researchers expect to see "bigger use of AI," "vast use of AI," and "more automation in terms of transcription and insights distillation, perhaps reporting."
However, predictions weren't uniformly positive. Some researchers expressed concerns:
"That AI will be overused and the gaps will be found and documented"
"Many jobs are being eliminated and I believe the quality will go down"
The research profession will transform
Multiple researchers predicted significant changes to the UX research profession itself. Some expect "the junior career path will continue to shrink," while others anticipate that "everyone will do research with AI."
One researcher offered a nuanced view: "That some researchers will become extremely comfortable with AI and others will still lag behind," suggesting the field may split between those who embrace AI and those who resist it.
Another emphasized the changing nature of research work: human researchers will focus on "empathy, strategy, and judgment" while AI handles data processing and pattern recognition.
Quality concerns will drive corrections
Several researchers predicted that after a period of AI enthusiasm and over-reliance, organizations will recognize limitations. One noted, "I hope/predict that businesses will see they have lost opportunities or have gone down the wrong paths and will need to rehire user researchers."
This suggests a potential cycle where initial AI adoption may lead to quality issues, which in turn leads to a renewed appreciation for skilled researchers who can properly leverage AI while maintaining research rigor.
How to prepare for UX research in 2026
Based on the trends and challenges researchers identified, here are practical ways to prepare for the evolving landscape of UX research:
Preparation area | What to focus on |
|---|---|
Embrace AI as a tool, not a replacement | Learn AI tools for transcription, note-taking, and pattern identification while maintaining human judgment |
Strengthen your ability to demonstrate ROI | Connect research findings to business metrics and tell compelling stories about research impact |
Build systems for insight management | Advocate for research repositories and maintain them for easy access and knowledge sharing |
Position yourself strategically | Move beyond tactical execution to contribute to product strategy and business planning |
Maintain research quality while moving fast | Build efficient processes with templates and standards that don't sacrifice rigor for speed |
Embrace AI as a tool, not a replacement
With 88% of researchers identifying AI-assisted analysis as a top trend, resistance isn't the answer. Instead, focus on learning how AI can enhance your work while maintaining the human judgment that makes research valuable.
Experiment with AI tools for time-consuming tasks like transcription, note-taking, and initial pattern identification. But keep your critical thinking skills sharp – AI can process data, but it can't provide the empathy, context, and strategic thinking that turn findings into actionable insights.
Strengthen your ability to demonstrate ROI
Since proving research value remains the top challenge, invest in developing your business acumen. Learn to connect research findings to business metrics, frame insights in terms of business impact, and tell compelling stories about how research drives outcomes.
Build relationships with stakeholders who can amplify research's value and help you demonstrate impact across the organization.
Build systems for insight management
As research scales and democratizes, having systems to organize and share findings becomes crucial. If your organization doesn't have a research repository, advocate for one. If you do have one, make sure it's well-maintained and easy for others to use.
Good insight management helps you demonstrate research's cumulative value over time and makes it easier for non-researchers to learn from past work.
Position yourself strategically
Move beyond purely tactical research execution. Look for opportunities to get involved in product strategy discussions, contribute to business planning, and demonstrate how research can inform decisions at every stage.
The researchers who thrive will be those who can operate at both strategic and tactical levels.
Maintain research quality while moving fast
Don't sacrifice rigor for speed. Instead, build efficient research processes that maintain quality. This might mean creating templates, establishing clear research standards, or using tools that streamline workflows without cutting corners.
Be explicit with stakeholders about the tradeoffs between speed and quality. Help them understand what fast-but-rigorous research looks like versus rushed research that may lead to poor decisions.
Looking ahead
AI is transforming UX research, but human researchers aren't becoming obsolete. The field is evolving toward a model where researchers leverage AI for efficiency while focusing their own efforts on the strategic thinking, empathy, and judgment that machines can't replicate.
The challenges researchers face – proving ROI, getting stakeholder buy-in, maintaining quality – aren't new. But AI and other emerging trends create both opportunities to address these challenges and risks of new problems if tools are misused.
The researchers who will thrive in 2026 and beyond are those who can adapt to new tools while maintaining the core skills that make research valuable: asking the right questions, interpreting findings in context, and translating insights into action.
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FAQs about UX research trends in 2026
Methodology: We surveyed 100 UX researchers who work full-time, part-time, or are self-employed using the Lyssna research panel in December 2025. Participants were asked about trends they expect to impact UX research in 2026, how they currently use AI, their predictions for the field, and the biggest challenges they face.
Diane Leyman
Senior Content Marketing Manager
Diane Leyman is the Senior Content Marketing Manager at Lyssna. She brings extensive experience in content strategy and management within the SaaS industry, along with editorial and content roles in publishing and the not-for-profit sector
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