This talk addresses the distinct challenges of designing AI-first products when the foundational technology is advancing at an unprecedented pace. We will discuss the practical implications of this rapid evolution on the design process and share our insights into creating effective user experiences in such a dynamic environment.
Day 1: Using AI in UX with Impact
With the constant influx of new AI models and tools, it can be hard to distinguish hype from true value. Learn from experienced design practitioners where AI has delivered on its promises, where it hasn’t, and the processes they’re using to leverage AI to its full potential.
With the constant influx of new AI models and tools, it can be hard to distinguish hype from true value. Learn from experienced design practitioners where AI has delivered on its promises, where it hasn’t, and the processes they’re using to leverage AI to its full potential.
Day 1 Introduction
AI is fast transforming the way companies operate and design products and services. New design practices like “vibe coding,” or “prompt engineering,” are accelerating product launches at speed and scale. But with the rush to market; how can teams maintain their commitment to human-centered design, minimize the risks to consumers and keep up with the increase in developer velocity? We showcase various tactics companies are using to manage the risk of implementing AI into their products while keeping their ever tightening GTM timelines.
Break
NASA faced increasing complexity in managing data, meeting customer needs, and streamlining processes across its diverse missions and operations. With fragmented data sources, manual workflows, and a lack of integrated AI tools, teams struggled to maintain efficiency, consistency, and innovation.
Through a cross-organizational AI-readiness initiative led by the OCIO, NASA engaged stakeholders across Service Lines, Centers, and Mission Support Offices to identify challenges, articulate use cases, and prioritize AI opportunities. Workshops, assessments, and stakeholder collaboration provided a roadmap for integrating AI solutions, enabling secure data usage, and automating repetitive tasks. Focused efforts on training, governance, and iterative implementation ensured alignment with organizational goals.
Long Break
Learn how Accenture’s GrowthOS accelerator partners with WEVO to simulate user responses at scale—cutting research time from weeks to minutes. In this session, Accenture will show how AI-powered testing of early concepts, Figma prototypes, and full journeys helps their clients identify friction, de-risk launches, and refine designs before development begins.
The Challenge
Users engaging with the AI shopping assistant often felt constrained by limited options, excessive follow-up questions, and a lack of personalization. These shortcomings led to user fatigue, misunderstandings, and a subpar shopping experience. Insights from user research (UXR) and transcripts revealed that users wanted more intuitive, human-like interactions that catered to their unique needs.
The Solution
A robust, adaptable framework was designed to transform AI conversations into sales-like consultations. By breaking user queries into three core components—use-case, constraints, and preferences—the framework enabled the bot to understand intent and deliver relevant, personalized results. Key enhancements included:
Allowing users to skip questions and navigate freely.
Providing contextual help for technical queries.
Transitioning to open-ended interactions after gathering essential details to prevent over-questioning.
Displaying diverse and curated results aligned with user preferences.
Break
Our team at Gazzetta, a media research lab, is tackling a fundamental challenge in journalism: the disconnect between media output and community needs, particularly in restricted or distorted information environments of autocracies. We have learnt over the past years that traditional audience research has led to quant-heavy, superficial understanding, ineffective content and, ultimately, irrelevance.
To address this problem, we have developed a three-stage process using AI knowledge bases to build empathy, map information needs, and analyze information flows. We have used this process to systematically review multiple information sources to build deep community understanding before product development.
This methodology has helped us preserve nuance, identify knowledge gaps, and assign confidence levels to findings. Rather than treating AI as a black box solution, a thoughtful process-oriented approach can help us better understand and serve information needs, and gradually rebuild relevance.
Long Break
Product Context Analyzer is an AI-first solution that automates the discovery and analysis of product usage context, instantly synthesizing insights into industry-standard requirements models. By transforming raw inputs like tasks, personas, user journeys, or interview transcripts into structured design inputs, this tool dramatically reduces reliance on time- and labor-intensive primary research. It empowers any team, at any time, to generate actionable user insights in minutes, enabling continuous learning about user needs and scaling research operations across an organization. In this session, we’ll demo how to go from raw input to clear, structured requirements and user stories and illustrate how AI is reshaping the way teams develop a more inclusive and deeper understanding of users to make the right strategic and tactical design decisions to deliver successful products.
We built a novel math tutoring app for 11-year-olds in the UK. Since this was our first AI project, we expected lots of technical issues. Those happened and on top of it, we ended up questioning the value of designers in AI-driven products.
Break
AI moves fast. In the time since we began programming DwAI25 in December, we’ve already seen important new developments like DeepSeek R1, Deep Research from OpenAI and Perplexity, and Mira Murati’s Thinking Machines Lab. By June, the terrain will have transformed even further. In this panel, we’ll learn about the latest developments in AI from representatives from major AI players, and what they mean for UX professionals.
Wrap up
Cozy Juicy Real
Join us the evening of Tuesday, June 10 to play Cozy Juicy Real—an engaging online board game where the purpose is anything but trivial: creating authentic and truly meaningful connections with your peers.
This is an interactive session and spaces are limited. RSVP is required!
RSVP now!
Whether you’re looking to expand your network, meet your next client or connect with collaborators, this is your opportunity to make it happen.
You’ll experience Cozy Juicy Real, a simple, effective board game that’s been played in 71 countries. It’s proven to create stronger team bonds at the world’s most successful organizations – including Google, Adobe and the UN.
“You will connect. Cozy Juicy Real is the best way to foster connection online.”
– Marcia Goddard, Chief Culture Officer, The Contentment Foundation
Discover how JourneySpark Consulting partnered with WEVO to unlock persona-driven optimization at scale. In this session, you’ll learn how they used WEVO Pulse to simulate audience reactions, tailor ad messaging, and A/B test concepts—resulting in a 50% increase in click-through rates. Then, see how they used WEVO Pro to validate and scale these insights across channels.
Day 2: Cutting Edge AI Opportunities
Potential opportunities for AI in UX go well beyond the chat window. Hear about how design professionals are using AI to introduce exciting new capabilities – from data visualization, to storytelling and code, to real-world interfaces.
Potential opportunities for AI in UX go well beyond the chat window. Hear about how design professionals are using AI to introduce exciting new capabilities – from data visualization, to storytelling and code, to real-world interfaces.
Day 2 Introduction
“Feels Like Paper!” is a series of prototypes about augmenting physical paper through AI. Various ML models, LLMs and a mixed reality headset are used to infuse physical paper and ink with properties of the digital world without compromising on their physical traits.
Break
As a data visualization designer and developer the challenge I often face is what to do with unstructured data. One case study I can show is exploring survey results where the multiple-choice questions are straightforward to analyze but interesting open-ended questions like “What do your colleagues not understand about data visualization?” are much harder to crack.
Latent Scope is an open-source tool I built that streamlines a process of embedding text, mapping it to 2D, clustering the data points on the map and summarizing those clusters with an LLM. Once the process is done on a dataset structure emerges from the unstructured text, allowing us to get a sense of patterns in the survey answers. Themes like “the time it takes” to develop data visualization pop out, as do “the importance of good design.” While people don’t use the same language to describe these themes, they show up as clusters in the tool thanks to the power of embedding models.
https://github.com/enjalot/latent-scope
Long Break
“All of us are experimenting with using AI in our daily work. It is difficult to write prompts, the first output is never right, AI outputs can feel quite shallow, and then there is inertia. We get it, we all yearn for familiarity in our tools and processes – but the reality is that AI is rapidly changing how design gets done.
In this interactive session, design and product leaders from Miro will share their real world boards and examples of how they have been using AI. We will cover all stages of the design process – from discovery and roadmapping to design and delivery. We will end with a collective reflection on the emerging principles for using AI for design work.”
Sentient Scenes is a little toy with big lessons—an intelligent interface that changes style, mood, and behavior on demand. The project explores what it means to treat AI as a design material, weaving open-ended intelligence into interfaces beyond chat. We’ll share lessons in both technique and perspective for how the designer’s role evolves—from crafting visuals to sketching prompts—and what it takes to craft systems where machine intelligence mediates the user experience.
Break
John shares how AI-powered code generation tools can transform the product design process, even for those with no coding experience. He explains how, in 2025, these tools changed the way he works by allowing him to move directly from low-fidelity wireframes to high-fidelity interface design in front-end code—the same environment used by his engineering peers. The session includes practical examples, such as building interactive dashboard mockups to explore color and layout options, and creating tools for ideation using real components and data within the application codebase.
After this talk you may learn that:
- Trying out new AI tools, even if it means moving away from traditional ones, can help you build new skills and expand your capabilities.
- AI tools can speed up the early stages of design by quickly generating ideas, color palettes, and layouts, often faster than traditional design software.
- Working closer to actual code, with help from AI, allows you to create custom tools that support design decisions within the real context of your product.
Long Break
William Gibson famously claimed “the future is already here — it’s just not very evenly distributed.” This is particularly true in the fast-moving world of AI, where practitioners in other disciplines are already wrangling with new issues that will soon impact design. This panel brings together an expert technologist, creator, and ethicist to discuss key AI developments and how these developments are impacting their work. From these three lenses, they’ll grapple with what this means for design over the next 12 months.
Break
We’re moving into a future of widespread deployment of AI. Skate where the puck is going: what new design paradigms will we need for our new products there? To explore this, Matt starts practically… with his own prototypes and experiments. He finds five possible worlds, and we’ll imagine each in turn, finally asking: what does it mean to dream?