April 2, 2024
6 min

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

In the last few years, the influence of AI has steadily been expanding into various aspects of design. In early 2023, that expansion exploded. AI tools and features are now everywhere, and there are two ways designers commonly react to it:

  • With enthusiasm for how they can use it to make their jobs easier
  • With skepticism over how reliable it is, or even fear that it could replace their jobs

Google UX researcher Clara Kliman-Silver is at the forefront of researching and understanding the potential impact of AI on design into the future. This is a hot topic that’s on the radar of many designers as they grapple with what the new normal is, and how it will change things in the coming years.

Clara’s background 

Clara Kliman-Silver spends her time studying design teams and systems, UX tools and designer-developer collaboration. She’s a specialist in participatory design and uses generative methods to investigate workflows, understand designer-developer experiences, and imagine ways to create UIs. In this work, Clara looks at how technology can be leveraged to help people make things, and do it more efficiently than they currently are.

In today’s context, that puts generative AI and machine learning right in her line of sight. The way this technology has boomed in recent times has many people scrambling to catch up - to identify the biggest opportunities and to understand the risks that come with it. Clara is a leader in assessing the implications of AI. She analyzes both the technology itself and the way people feel about it to forecast what it will mean into the future.

Contact Details:

You can find Clara in LinkedIn or on Twitter @cklimansilver

What role should artificial intelligence play in UX design process? 🤔

Clara’s expertise in understanding the role of AI in design comes from significant research and analysis of how the technology is being used currently and how industry experts feel about it. AI is everywhere in today’s world, from home devices to tech platforms and specific tools for various industries. In many cases, AI automation is used for productivity, where it can speed up processes with subtle, easy to use applications.

As mentioned above, the transformational capabilities of AI are met with equal parts of enthusiasm and skepticism. The way people use AI, and how they feel about it is important, because users need to be comfortable implementing the technology in order for it to make a difference. The question of what value AI brings to the design process is ongoing. On one hand, AI can help increase efficiency for systems and processes. On the other hand, it can exacerbate problems if the user's intentions are misunderstood.

Access for all 🦾

There’s no doubt that AI tools enable novices to perform tasks that, in years gone by, required a high level of expertise. For example, film editing was previously a manual task, where people would literally cut rolls of film and splice them together on a reel. It was something only a trained editor could do. Now, anyone with a smartphone has access to iMovie or a similar app, and they can edit film in seconds.

For film experts, digital technology allows them to speed up tedious tasks and focus on more sophisticated aspects of their work. Clara hypothesizes that AI is particularly valuable when it automates mundane tasks. AI enables more individuals to leverage digital technologies without requiring specialist training. Thus, AI has shifted the landscape of what it means to be an “expert” in a field. Expertise is about more than being able to simply do something - it includes having the knowledge and experience to do it for an informed reason. 

Research and testing 🔬

Clara performs a lot of concept testing, which involves recognizing the perceived value of an approach or method. Concept testing helps in scenarios where a solution may not address a problem or where the real problem is difficult to identify. In a recent survey, Clara describes two predominant benefits designers experienced from AI:

  1. Efficiency. Not only does AI expedite the problem solving process, it can also help efficiently identify problems. 
  2. Innovation. Generative AI can innovate on its own, developing ideas that designers themselves may not have thought of.

The design partnership 🤝🏽

Overall, Clara says UX designers tend to see AI as a creative partner. However, most users don’t yet trust AI enough to give it complete agency over the work it’s used for. The level of trust designers have exists on a continuum, where it depends on the nature of the work and the context of what they’re aiming to accomplish. Other factors such as where the tech comes from, who curated it and who’s training the model also influences trust. For now, AI is largely seen as a valued tool, and there is cautious optimism and tentative acceptance for its application. 

Why it matters 💡

AI presents as potentially one of the biggest game-changers to how people work in our generation. Although AI has widespread applications across sectors and systems, there are still many questions about it. In the design world, systems like DALL-E allow people to create AI-generated imagery, and auto layout in various tools allows designers to iterate more quickly and efficiently.

Like many other industries, designers are wondering where AI might go in the future and what it might look like. The answer to these questions has very real implications for the future of design jobs and whether they will exist. In practice, Clara describes the current mood towards AI as existing on a continuum between adherence and innovation:

  • Adherence is about how AI helps designers follow best practice
  • Innovation is at the other end of the spectrum, and involves using AI to figure out what’s possible

The current environment is extremely subjective, and there’s no agreed best practice. This makes it difficult to recommend a certain approach to adopting AI and creating permanent systems around it. Both the technology and the sentiment around it will evolve through time, and it’s something designers, like all people, will need to maintain good awareness of.

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Efficient Research: Maximizing the ROI of Understanding Your Customers

Introduction

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.

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.

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

1. Time Allocation: Invest in What Matters Most

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.

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

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

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.

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

3. Collaboration: Make Research a Team Sport

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.

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

4. Prioritization: Focus on the Right Questions

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?

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

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

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.

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

6. Anticipation: Stay Ahead of Research Needs

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.

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

7. Justification of Methodology: Explain Why Your Approach Works

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.

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

8. Individual Engagement: Tailor Research Communication to Your Audience

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.

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

9. Business Actions: Ensure Research Leads to Real Change

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.

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

Final Thoughts: Research That Moves the Needle

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:


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

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

Watch the full webinar here

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1 min read

Qualitative insights: Reimagined and supercharged 🚀

We're thrilled to announce the re-launch of our Qualitative Insights tool, formerly known as Reframer. This powerful upgrade brings new features designed to revolutionize your qualitative data analysis process, making it faster, easier, and more insightful than ever before.

Introducing the new Qualitative Insights 🔍

Qualitative Insights has always been your go-to tool to help you plan and organize interviews, take notes, tag, and analyze rich, unstructured data. Now, we've taken it to the next level with two game-changing additions:

  • Insights feature: A dedicated space to capture, organize, and communicate your key takeaways.
  • AI capabilities: Optional AI-powered assistance to accelerate your analysis process.

Discover insights effortlessly 💡 

The new Insights feature transforms how you work with qualitative data:

  • Centralized hub: All your analytical discoveries in one place.
  • Structured insights: Each insight includes a title, detailed description, and associated observations.
  • Flexible viewing: Toggle between overview and deep-dive modes.
  • Efficient organization: Tag and categorize insights for easy retrieval.
  • Collaboration tools: Share and discuss findings with your team.

How it works 🛠️ 

Manual insight creation

  1. Filter your data using keywords, tags, affinity map groupings, tasks, segments, and sessions.
  2. Select relevant observations.
  3. Craft your insight with a custom title and description.

AI-Powered Insight Generation (Optional)

  1. Click "Generate" to activate our AI assistant.
  2. AI analyzes existing observations to produce new insights.
  3. Automatically generates insight titles, summaries, and attaches relevant observations.
  4. AI-generated insights are marked with an AI star symbol for easy identification.
  5. All AI insights remain fully editable.

AI: Your analysis assistant 🤖

Our AI capabilities are designed to enhance your abilities, not replace them. Use AI to:

  • Speed up insight discovery
  • Reveal hidden patterns in your data
  • Jumpstart the analysis process

Remember, your expertise is crucial. Always review and refine AI-generated insights to ensure accuracy and capture nuances that only human understanding can provide.

Your data, your choice 🔒 

We prioritize your privacy and data control:

  • Your data stays within your organization
  • We don't use it to train other AI models
  • You control when to use AI for insights
  • AI features can be turned on or off anytime

Get started today 🌟 

Ready to experience the power of the new Qualitative Insights? Learn more and dive in. Upgrade your qualitative analysis workflow and uncover deeper insights faster than ever before with Qualitative Insights!

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1 min read

Bear Liu: How visual thinking can improve communications in design workplaces

When Bear Liu was teaching himself design, he struggled remembering concepts since English wasn’t his first language. To help, he started doodling. By drawing pictures that related to what he was learning, he found he could not only remember them better, he could understand and communicate more effectively too. Ever since, he’s used the power of drawings and pictures to relay information in ways people can use.

Bear gives examples of how visual communication can help design workplaces to relay information in a more memorable and usable way. It may only seem like a minor change, but the difference can be significant.

Bear’s background 🎤

Bear Liu is a Product Designer at Xero, an online accounting platform that’s used all over the world. He’s also a Design Mentor at Springboard and CareerFoundry, and an Apple Award-Winning podcast host at BearTalk.

His background is in science education. As a self-taught designer, Bear has helped a raft of large and small businesses with digital products over the last 16 years. His clients come from diverse backgrounds and industries across the globe. Bear's professional passions also carry over into his hobbies. Outside of work he enjoys reading, drawing, and producing videos & podcasts on tech and design.

Contact Details:

You can find Bear on LinkedIn, or listen to his podcast, BearTalk.

Unleash your visual superpower as a communication pro 🦸🏻

When it comes to addressing business challenges it is important to keep these three aspects in mind: 

  1. Understanding - break down complex problems and solutions so everyone can understand. 
  2. Memory - retaining information in your mind is difficult even with note taking.
  3. Communication- People relate to words differently, and the meaning of something can easily get lost in translation. This issue is more prevalent with remote work.

Bear Liu strongly believes that visual communication helps people understand, remember and communicate information more effectively. Why?

  • It helps to focus. Pictures remove distractions and draw attention to where it’s desired.
  • It’s a token. A picture is universal - a house or a smiley face means the same thing to people that speak different languages. 
  • Most people are visual thinkers. Studies have found humans are hard-wired to process visual information faster. We are better at storing information in images, rather than numbers and letters.

But what if I can’t draw? This is a common issue Bear finds when talking to people about this. It’s not about the quality of the drawing itself, it’s about what it means. By delivering a message through a picture, it becomes understandable. Many of Bear’s drawings only ever remain in draft form. Even simple doodles can have meanings that make concepts clear.

In his design work at Xero, Bear has used drawing and sketches to great effect in a range of instances:

  • The accessibility tree was a complex, abstract system, but by drawing it (on a literal tree), and adding a few notes alongside it, the terminology became much more understandable.
  • Sketching how customers work made it easier to describe how Xero could help them. It was much more memorable than writing it out in paragraphs.
  • Wrapping the year in product design. A written summary of a year’s work is long-winded. Instead, Bear drew a tree and pinned key words, quotes and achievements to communicate the highlights.
  • UX terminology explanations can be difficult for those outside the industry to comprehend. Bear challenged himself to share 1 minute videos that accompanied simple drawings to help colleagues understand them, and had rave reviews.
  • Sketching notes is a great alternative to writing notes at conferences or meetings. Presenters can draw to help audiences follow along, and people in the audience themselves can also sketch their own notes.

Why it matters  🔥

Bear has adapted visual thinking to his own product design process and has seen a noticeable improvement in communication as a result.

People are busy - their brains are packed with all sorts of information, and they’re easily distracted by other things they have on their minds. By delivering information in a way that helps them to focus on it, remember and understand it, designers can achieve their ultimate goals.

As Bear also notes, drawing is fun. It’s much more rewarding than using words, as well as much more effective.

Bear used the example of his talk at UX New Zealand 2023 as a great place to use a drawing. Rather than follow along with his message by scribbling notes the whole way through, those in the audience could capture the biggest lessons easily in one simple drawing.

  • First, Bear drew one stick figure to represent himself as a speaker. He drew three speech bubbles, where audience members could write the most notable points he said.
  • Then he drew another stick figure, which represented the audience member listening to him. They had three thought bubbles, which people could populate with their biggest takeaways from the speech.

That one simple drawing is a template that can be used in any speech or meeting to remember the key points.

Seeing is believing

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