A deep dive into Day 1 of Designing with AI 2026
April 13, 2026Designing with AI 2026 is the third iteration of Rosenfeld Media‘s annual Designing with AI conference, and it’s shaping up to be unforgettable!
Dr. Llewyn Paine and the rest of the Designing with AI curation team has been carefully crafting the 2026 program since we wrapped up Designing with AI 2025. The virtual conference, taking place June 9-10, asks the critical questions designers have in 2026, like Where does AI fit into my work? How can I ethically use artificial intelligence? Will AI help or replace me?
This year, we’ve built our conference program around two themes:
- Managing AI-augmented product design work
- The new AI-augmented design process
Let’s focus on day 1 of our two-day conference below.
How can product designers manage the implementation AI into their work?
“Deciding how to align people, process, and AI infrastructure requires both strategy and empathy.”
As AI shifts design work in unprecedented ways, UX leaders are tasked with creating clarity. Deciding how to align people, process, and AI infrastructure requires both strategy and empathy. These case studies demonstrate how leaders are balancing conflicting AI pressures and justifying their teams’ value, even amid constant change.
Here’s a sneak preview at some of what day 1 of #DwAI2026, June 9, has to offer:
New Work, New Words: A Glossary for AI
with Paul Ford, Co-Founder, Aboard
8:25-8:55am PT: Paul Ford proposes 30 totally new terms (plus a few he didn’t make up), ranging from the ridiculous to the terrifying, to help make sense our new AI inflection point. Because we can’t talk about things until we name them. View talk info »
Q: Why do new words matter in the age of AI?
A: New technology changes how we think, talk, and work, so language matters. If we don’t have the right words, it becomes harder to understand what AI is doing and how it is reshaping product design.
Reimagining the creative process: Orchestrating intelligent systems for business impact
with Shambhavi Gupta, Director AI Product Design, System Thinking, Service Design, Design Strategy and Innovation, Incedoinc
9:05-9:35am PT: Traditional product design takes months, limits creativity, and often misses what users really want. We proved AI can flip that script.
By analyzing 10,000+ customer reviews, AI uncovered hidden pain points. It then generated 200 design variations in minutes, cut prototyping cycles nearly in half, and shrank the redesign timeline from six months to just eight weeks.
The payoff? A smarter, more ergonomic product that boosted customer satisfaction by 30%. AI isn’t replacing designers — it’s their superpower, turning design into a faster, bolder, and more human‑centered process. View talk info »
Q: How can AI improve the creative process in product design?
A: AI can help teams analyze large amounts of customer feedback, uncover hidden pain points, and generate more design options faster. That creates more room for exploration and better decision-making.
Coordinating chaos: Preventing workflow fragmentation when everyone accelerates with AI
with Claire Dhoosche, Senior DesignOps Manager, Criteo
10:15-10:45am PT: When Product, Design, and Tech all adopt AI in parallel, we instinctively think about tools. I discovered through my experience at Criteo that the real challenge is profoundly human: aligning teams with different visions, different fears, and different territories to protect, into a shared workflow that actually makes sense.
This is the story of my transformation-building journey over the past year, within Product, for designers as a team.
In a world where almost everyone can do almost everything thanks to AI – in a company like Criteo, with 4,000 employees, 900 devs, 80 PMs, and 35 designers – how do you operate this AI transformation without it becoming a mess? View talk info »
Q: What challenge appears when teams adopt AI at the same time?
A: The biggest challenge is not the tools themselves, but workflow fragmentation. When Product, Design, and Tech all move fast with AI, teams can easily lose alignment if they do not share a clear process.
Leading through ambiguity: Supporting a design team relearning their craft
with Beth Chappell, Senior Manager, Product Design (AI & Creator Tools), Articulate
10:55-11:25am PT: Our team had been designing AI features for some time before we were forced to confront what that meant for our own craft. At Articulate, we build tools that help people create learning at scale. As we introduced AI-augmented creation workflows, we focused on helping learning designers move faster and generate ideas more easily. But those same forces began reshaping how our own design team worked under the pressure of sustained ambiguity.
What started as workflow optimization became real-time field research into how designers learn, resist, and adapt when the act of creation itself changes. Familiar practices began to break, observing where problem framing eroded, critique expanded instead of converging, and experience stopped guaranteeing great judgment.
This talk is an ongoing case study in leading teams through that shift. It also reflects on how our internal experience designing with AI became a critical lens for understanding the people we build for. View talk info »
Q: How does AI affect the design process internally?
A: AI can speed up idea generation and workflow optimization, but it can also change how teams frame problems, run critique, and evaluate quality. That means the design process itself has to evolve.
Deciding when to automate: Integrating AI in high-stakes systems
with Joy KendiMwiti, Senior Creative Lead, Dalberg Design
12:35-1:05pm PT: In high-stakes primary health systems, designing with AI isn’t just about adding new capabilities. It is about deciding where AI genuinely helps, where it doesn’t, and how to introduce it in contexts where human judgment or public trust are on the line. With many designers raising ethical concerns related to AI, this case study places those risks at the center of a practical design process and offers practical decision tools designers can incorporate into their work. View talk info »
Q: What should designers keep in mind when using AI in sensitive environments?
A: They should evaluate where AI helps, where it should not be used, and how to make those decisions transparently. Practical decision tools can help teams balance innovation with responsibility.
From prototype to production: Vibe coding design for real engineering systems
Speakers TBA
1:15-1:45pm PT: Vibe coding can feel empowering for designers, but production code plays by different rules–and designers can’t see the full picture. In this panel, [panel members] unpack the hidden constraints, tradeoffs, and expectations that shape real codebases. Learn what engineers wish designers understood about AI‑generated code, and how to collaborate more effectively as design and engineering roles continue to blur. View talk info »
Q: What is the biggest gap between AI prototypes and real code?
A: Prototypes can make AI feel simple and fast, but production systems have constraints, tradeoffs, and technical expectations that are much harder to see. That gap is where many collaboration problems begin.
How can I attend Designing with AI 2026?
Register for a conference ticket to join us live on June 9-10, 2026 and hear all the insights and lessons learned from our featured speakers.
