Clara Kliman-Silver: AI & design: imagining the future of UX

As artificial intelligence (AI) continues to advance and permeate various industries, the field of user experience (UX) research is no exception. 

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At Optimal Workshop, our recent Value of UX report revealed that 68% of UX professionals believe AI will have the greatest impact on analysis and synthesis in the research project lifecycle. In this article, we'll explore the current and potential applications of AI in UXR, its limitations, and how the role of UX researchers may evolve alongside these technological advancements.

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How researchers are already using AI

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AI is already making inroads in UX research, primarily in tasks that involve processing large amounts of data, such as

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• Automated transcription: AI-powered tools can quickly transcribe user interviews and focus group sessions, saving researchers significant time.

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• Sentiment analysis: Machine learning algorithms can analyze text data from surveys or social media to gauge overall user sentiment towards a product or feature.

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• Pattern recognition: AI can help identify recurring themes or issues in large datasets, potentially surfacing insights that might be missed by human researchers.

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• Data visualization: AI-driven tools can create interactive visualizations of complex data sets, making it easier for researchers to communicate findings to stakeholders.

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As AI technology continues to evolve, its role in UX research is poised to expand, offering even more sophisticated tools and capabilities. While AI will undoubtedly enhance efficiency and uncover deeper insights, it's important to recognize that human expertise remains crucial in interpreting context, understanding nuanced user needs, and making strategic decisions. 

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The future of UX research lies in the synergy between AI's analytical power and human creativity and empathy, promising a new era of user-centered design that is both data-driven and deeply insightful.

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The potential for AI to accelerate UXR processes

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As AI capabilities advance, the potential to accelerate UX research processes grows exponentially. We anticipate AI revolutionizing UXR by enabling rapid synthesis of qualitative data, offering predictive analysis to guide research focus, automating initial reporting, and providing real-time insights during user testing sessions. 

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These advancements could dramatically enhance the efficiency and depth of UX research, allowing researchers to process larger datasets, uncover hidden patterns, and generate insights faster than ever before. As we continue to develop our platform, we're exploring ways to harness these AI capabilities, aiming to empower UX professionals with tools that amplify their expertise and drive more impactful, data-driven design decisions.

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AI’s good, but it’s not perfect

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While AI shows great promise in accelerating certain aspects of UX research, it's important to recognize its limitations, particularly when it comes to understanding the nuances of human experience. AI may struggle to grasp the full context of user responses, missing subtle cues or cultural nuances that human researchers would pick up on. Moreover, the ability to truly empathize with users and understand their emotional responses is a uniquely human trait that AI cannot fully replicate. These limitations underscore the continued importance of human expertise in UX research, especially when dealing with complex, emotionally-charged user experiences.

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Furthermore, the creative problem-solving aspect of UX research remains firmly in the human domain. While AI can identify patterns and trends with remarkable efficiency, the creative leap from insight to innovative solution still requires human ingenuity. UX research often deals with ambiguous or conflicting user feedback, and human researchers are better equipped to navigate these complexities and make nuanced judgment calls. As we move forward, the most effective UX research strategies will likely involve a symbiotic relationship between AI and human researchers, leveraging the strengths of both to create more comprehensive, nuanced, and actionable insights.

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Ethical considerations and data privacy concerns‍

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As AI becomes more integrated into UX research processes, several ethical considerations come to the forefront. Data security emerges as a paramount concern, with our report highlighting it as a significant factor when adopting new UX research tools. Ensuring the privacy and protection of user data becomes even more critical as AI systems process increasingly sensitive information. Additionally, we must remain vigilant about potential biases in AI algorithms that could skew research results or perpetuate existing inequalities, potentially leading to flawed design decisions that could negatively impact user experiences.

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Transparency and informed consent also take on new dimensions in the age of AI-driven UX research. It's crucial to maintain clarity about which insights are derived from AI analysis versus human interpretation, ensuring that stakeholders understand the origins and potential limitations of research findings. As AI capabilities expand, we may need to revisit and refine informed consent processes, ensuring that users fully comprehend how their data might be analyzed by AI systems. These ethical considerations underscore the need for ongoing dialogue and evolving best practices in the UX research community as we navigate the integration of AI into our workflows.

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The evolving role of researchers in the age of AI

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As AI technologies advance, the role of UX researchers is not being replaced but rather evolving and expanding in crucial ways. Our Value of UX report reveals that while 35% of organizations consider their UXR practice to be "strategic" or "leading," there's significant room for growth. This evolution presents an opportunity for researchers to focus on higher-level strategic thinking and problem-solving, as AI takes on more of the data processing and initial analysis tasks.

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The future of UX research lies in a symbiotic relationship between human expertise and AI capabilities. Researchers will need to develop skills in AI collaboration, guiding and interpreting AI-driven analyses to extract meaningful insights. Moreover, they will play a vital role in ensuring the ethical use of AI in research processes and critically evaluating AI-generated insights. As AI becomes more prevalent, UX researchers will be instrumental in bridging the gap between technological capabilities and genuine human needs and experiences.

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Democratizing UXR through AI

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The integration of AI into UX research processes holds immense potential for democratizing the field, making advanced research techniques more accessible to a broader range of organizations and professionals. Our report indicates that while 68% believe AI will impact analysis and synthesis, only 18% think it will affect co-presenting findings, highlighting the enduring value of human interpretation and communication of insights.

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At Optimal Workshop, we're excited about the possibilities AI brings to UX research. We envision a future where AI-powered tools can lower the barriers to entry for conducting comprehensive UX research, allowing smaller teams and organizations to gain deeper insights into their users' needs and behaviors. This democratization could lead to more user-centered products and services across various industries, ultimately benefiting end-users.

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However, as we embrace these technological advancements, it's crucial to remember that the core of UX research remains fundamentally human. The unique skills of empathy, contextual understanding, and creative problem-solving that human researchers bring to the table will continue to be invaluable. As we move forward, UX researchers must stay informed about AI advancements, critically evaluate their application in research processes, and continue to advocate for the human-centered approach that is at the heart of our field.

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By leveraging AI to handle time-consuming tasks and uncover patterns in large datasets, researchers can focus more on strategic interpretation, ethical considerations, and translating insights into impactful design decisions. This shift not only enhances the value of UX research within organizations but also opens up new possibilities for innovation and user-centric design.

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As we continue to develop our platform at Optimal Workshop, we're committed to exploring how AI can complement and amplify human expertise in UX research, always with the goal of creating better user experiences.

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The future of UX research is bright, with AI serving as a powerful tool to enhance our capabilities, democratize our practices, and ultimately create more intuitive, efficient, and delightful user experiences for people around the world.

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Natalie and Lulu have forged a unique team culture that focuses on positive outputs (and outcomes) for their app’s growing user base. In doing so, they turned the traditional design approach on its head and created a dynamic and supportive team. 

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Natalie, Director of Design at Hatch, and Lulu, UX Design Specialist, recently spoke at UX New Zealand, the leading UX and IA conference in New Zealand hosted by Optimal Workshop, on their concept of “radical collaboration”.

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In their talk, Nat and Lulu share their experience of growing a small app into a big player in the finance sector, and their unique approach to teamwork and culture which helped achieve it.

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Background on Natalie Ferguson and Lulu Pachuau

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Over the last two decades, Lulu and Nat have delivered exceptional customer experiences for too many organizations to count. After Nat co-founded Hatch, she begged Lulu to join her on their audacious mission: To supercharge wealth building in NZ. Together, they created a design and product culture that inspired 180,000 Kiwi investors to join in just 4 years.

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Contact Details:

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Email: natalie@sixfold.co.nz

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LinkedIn: https://www.linkedin.com/in/natalieferguson/ and https://www.linkedin.com/in/lulupach/

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Radical Collaboration - How teamwork makes the dream work 💪💪💪

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Nat and Lulu discuss how they nurtured a team culture of “radical collaboration” when growing the hugely popular app Hatch, based in New Zealand. Hatch allows everyday New Zealanders to quickly and easily trade in the U.S. share market. 

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The beginning of the COVID pandemic spelled huge growth for Hatch and caused significant design challenges for the product. This growth meant that the app had to grow from a baby startup to one that could operate at scale - virtually overnight. 

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In navigating this challenge, Nat and Lulu coined the term radical collaboration, which aims to “dismantle organizational walls and supercharge what teams achieve”. Radical collaboration has six key pillars, which they discuss alongside their experience at Hatch.

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Pillar #1: When you live and breathe your North star

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Listening to hundreds of their customers’ stories, combined with their own personal experiences with money, compelled Lulu and Nat to change how their users view money. And so, “Grow the wealth of New Zealanders” became a powerful mission statement, or North Star, for Hatch. The mission was to give people the confidence and the ability to live their own lives with financial freedom and control. Nat and Lulu express the importance of truly believing in the mission of your product, and how this can become a guiding light for any team. 

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Pillar #2: When you trust each other so much, you’re happy to give up control

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As Hatch grew rapidly, trusting each other became more and more important. Nat and Lulu state that sometimes you need to take a step back and stop fueling growth for growth’s sake. It was at this point that Nat asked Lulu to join the team, and Nat’s first request was for Lulu to be super critical about the product design to date - no feedback was out of bounds. Letting go, feeling uncomfortable, and trusting your team can be difficult, but sometimes it’s what you need in order to drag yourself out of status quo design. This resulted in a brief hiatus from frantic delivery to take stock and reprioritize what was important - something that can be difficult without heavy doses of trust!

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Pillar #3: When everyone wears all the hats

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During their journey, the team at Hatch heard lots of stories from their users. Many of these stories were heard during “Hatcheversery Calls”, where team members would call users on their sign-up anniversary to chat about their experience with the app. Some of these calls were inspiring, insightful, and heartwarming.

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Everyone at Hatch made these calls – designers, writers, customer support, engineers, and even the CEO. Speaking to strangers in this way was a challenge for some, especially since it was common to field technical questions about the business. Nevertheless, asking staff to wear many hats like this turned the entire team into researchers and analysts. By forcing ourselves and our team outside of our comfort zone, we forced each other to see the whole picture of the business, not just our own little piece.

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Pillar #4: When you do what’s right, not what’s glam

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In an increasingly competitive industry, designers and developers are often tempted to consistently deliver new and exciting features. In response to rapid growth, rather than adding more features to the app, Lulu and Nat made a conscious effort to really listen to their customers to understand what problems they needed solving. 

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As it turned out, filing overseas tax returns was a significant and common problem for their customers - it was difficult and expensive. So, the team at Hatch devised a tax solution. This solution was developed by the entire team, with almost no tax specialists involved until the very end! This process was far from glamorous and it often fell outside of standard job descriptions. However, the team eventually succeeded in simplifying a notoriously difficult process and saved their customers a massive headache.

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Pillar #5: When you own the outcome, not your output.

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Over time Hatch’s user base changed from being primarily confident, seasoned investors, to being first-time investors. This new user group was typically scared of investing and often felt that it was only a thing wealthy people did.

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At this point, Hatch felt it was necessary to take a step back from delivering updates to take stock of their new position. This meant deeply understanding their customers’ journey from signing up, to making their first trade. Once this was intimately understood, the team delivered a comprehensive onboarding process which increased the sign-up conversion rate by 10%!

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Pillar #6: When you’re relentlessly committed to making it work

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Nat and Lulu describe a moment when Allbirds wanted to work with Hatch to allow ordinary New Zealanders to be involved in their IPO launch on the New York stock exchange. Again, this task faced numerous tax and trade law challenges, and offering the service seemed like yet another insurmountable task. The team at Hatch nearly gave up several times during this project, but everyone was determined to get this feature across the line – and they did. As a result, New Zealanders were some of the few regular investors from outside the U.S that were able to take part in Albirds IPO. 

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Why it matters 💥

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Over four years, Hatch grew to 180,000 users who collectively invested over $1bn. Nat and Lulu’s success underscores the critical role of teamwork and collaboration in achieving exceptional user experiences. Product teams should remember that in the rapidly evolving tech industry, it's not just about delivering the latest features; it's about fostering a positive and supportive team culture that buys into the bigger picture.

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The Hatch team grew to be more than team members and technical experts. They grew in confidence and appreciated every moving part of the business. Product teams can draw inspiration from Hatch's journey, where designers, writers, engineers, and even the CEO actively engaged with users, challenged traditional design decisions, and prioritized solving actual user problems. This approach led to better, more user-centric outcomes and a deep understanding of the end-to-end user experience.

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Most importantly, through the good times and tough, the team grew to trust each other. The mission weaved its way through each member of the team, which ultimately manifested in positive outcomes for the user and the business.

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Nat and Lulu’s concept of radical collaboration led to several positive outcomes for Hatch:

• It changed the way they did business. Information was no longer held in the minds of a few individuals – instead, it was shared. People were able to step into other people's roles seamlessly. 
• Hatch achieved better results faster by focusing on the end-to-end experience of the app, rather than by adding successive features. 
• The team became more nimble – potential design/development issues were anticipated earlier because everyone knew what the downstream impacts of a decision would be.

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Over the next week, Lulu and Nat encourage designers and researchers to get outside of their comfort zone and:

• Visit customer support team
• Pick up the phone and call a customer
• Challenge status quo design decisions. Ask, does this thing solve an end-user problem?

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Introduction

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User research is invaluable, but in fast-paced environments, researchers often struggle with tight deadlines, limited resources, and the need to prove their impact. In our recent UX Insider webinar, Weidan Li, Senior UX Researcher at Seek, shared insights on Efficient Research—an approach that optimizes Speed, Quality, and Impact to maximize the return on investment (ROI) of understanding customers.

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At the heart of this approach is the Efficient Research Framework, which balances these three critical factors:

• Speed – Conducting research quickly without sacrificing key insights.
• Quality – Ensuring rigor and reliability in findings.
• Impact – Making sure research leads to meaningful business and product changes.

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Within this framework, Weidan outlined nine tactics that help UX researchers work more effectively. Let’s dive in.

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1. Time Allocation: Invest in What Matters Most

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Not all research requires the same level of depth. Efficient researchers prioritize their time by categorizing projects based on urgency and impact:

• High-stakes decisions (e.g., launching a new product) require deep research.
• Routine optimizations (e.g., tweaking UI elements) can rely on quick testing methods.
• Low-impact changes may not need research at all.

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By allocating time wisely, researchers can avoid spending weeks on minor issues while ensuring critical decisions are well-informed.

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2. Assistance of AI: Let Technology Handle the Heavy Lifting

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AI is transforming UX research, enabling faster and more scalable insights. Weidan suggests using AI to:

• Automate data analysis – AI can quickly analyze survey responses, transcripts, and usability test results.
• Generate research summaries – Tools like ChatGPT can help synthesize findings into digestible insights.
• Speed up recruitment – AI-powered platforms can help find and screen participants efficiently.

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While AI can’t replace human judgment, it can free up researchers to focus on higher-value tasks like interpreting results and influencing strategy.

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3. Collaboration: Make Research a Team Sport

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Research has a greater impact when it’s embedded into the product development process. Weidan emphasizes:

• Co-creating research plans with designers, PMs, and engineers to align on priorities.
• Involving stakeholders in synthesis sessions so insights don’t sit in a report.
• Encouraging non-researchers to run lightweight studies, such as A/B tests or quick usability checks.

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When research is shared and collaborative, it leads to faster adoption of insights and stronger decision-making.

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4. Prioritization: Focus on the Right Questions

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With limited resources, researchers must choose their battles wisely. Weidan recommends using a prioritization framework to assess:

• Business impact – Will this research influence a high-stakes decision?
• User impact – Does it address a major pain point?
• Feasibility – Can we conduct this research quickly and effectively?

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By filtering out low-priority projects, researchers can avoid research for research’s sake and focus on what truly drives change.

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5. Depth of Understanding: Go Beyond Surface-Level Insights

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Speed is important, but efficient research isn’t about cutting corners. Weidan stresses that even quick studies should provide a deep understanding of users by:

• Asking why, not just what – Observing behavior is useful, but uncovering motivations is key.
• Using triangulation – Combining methods (e.g., usability tests + surveys) to validate findings.
• Revisiting past research – Leveraging existing insights instead of starting from scratch.

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Balancing speed with depth ensures research is not just fast, but meaningful.

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6. Anticipation: Stay Ahead of Research Needs

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Proactive researchers don’t wait for stakeholders to request studies—they anticipate needs and set up research ahead of time. This means:

• Building a research roadmap that aligns with upcoming product decisions.
• Running continuous discovery research so teams have a backlog of insights to pull from.
• Creating self-serve research repositories where teams can find relevant past studies.

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By anticipating research needs, UX teams can reduce last-minute requests and deliver insights exactly when they’re needed.

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7. Justification of Methodology: Explain Why Your Approach Works

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Stakeholders may question research methods, especially when they seem time-consuming or expensive. Weidan highlights the importance of educating teams on why specific methods are used:

• Clearly explain why qualitative research is needed when stakeholders push for just numbers.
• Show real-world examples of how past research has led to business success.
• Provide a trade-off analysis (e.g., “This method is faster but provides less depth”) to help teams make informed choices.

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A well-justified approach ensures research is respected and acted upon.

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8. Individual Engagement: Tailor Research Communication to Your Audience

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Not all stakeholders consume research the same way. Weidan recommends adapting insights to fit different audiences:

• Executives – Focus on high-level impact and key takeaways.
• Product teams – Provide actionable recommendations tied to specific features.
• Designers & Engineers – Share usability findings with video clips or screenshots.

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By delivering insights in the right format, researchers increase the likelihood of stakeholder buy-in and action.

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9. Business Actions: Ensure Research Leads to Real Change

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The ultimate goal of research is not just understanding users—but driving business decisions. To ensure research leads to action:

• Follow up on implementation – Track whether teams apply the insights.
• Tie findings to key metrics – Show how research affects conversion rates, retention, or engagement.
• Advocate for iterative research – Encourage teams to re-test and refine based on new data.

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Research is most valuable when it translates into real business outcomes.

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Final Thoughts: Research That Moves the Needle

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Efficient research is not just about doing more, faster—it’s about balancing speed, quality, and impact to maximize its influence. Weidan’s nine tactics help UX researchers work smarter by:

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✔️  Prioritizing high-impact work
✔️  Leveraging AI and collaboration
✔️  Communicating research in a way that drives action

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By adopting these strategies, UX teams can ensure their research is not just insightful, but transformational.

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Watch the full webinar here

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