Companies have stepped up their support for designers adopting AI. 87% of all respondents report at least moderate organizational support for AI adoption, and 53% say that support is strong—via budget, active encouragement, and formal programs.

In 2025, early-stage startups were twice as likely to have adopted AI tools compared to growth-stage or publicly traded companies. That gap has narrowed. Today, 60% of respondents at both early- and growth-stage companies report receiving strong organizational support, with publicly traded companies close behind at 56%. AI tools are being adopted across the spectrum.

Companies with strong organizational support don't just provide tools and budget. They create space for exploration. Among designers at high-support organizations, 55% report having a broader culture of tinkering where everyone is expected to build and experiment, compared to 28% at companies with moderate or minimal support. Tinkering appears to be the mechanism through which organizational investment actually reaches designers. 

Designers at companies with strong AI adoption support are also much more likely to say AI is part of their core workflow, to feel confident in their toolstack, and to ship code. And as we explore in Craft, they also report higher job satisfaction and feelings of creative capability.

46% of designers say their companies have internal AI champions or communities of practice. That’s followed by structured tinkering time (25%), formal training programs (20%), and subscriptions to learning platforms (16%).

Similar to our 2025 findings, learning happens bottom-up. Other than self-directed learning—the #1 way designers are staying current—they’re teaching one another.

Compared to last year, the number of designers relying on peer learning more than doubled, from 24% to 70% of respondents. Those using social media, newsletter, and online communities jumped from 41% to 76%.

Our respondents indicated that they learn from leadership recommendations at half the rate they did in 2025, dropping from 32% to 16%. Leaders who want to enable AI adoption can support peer learning and bubble up the best practices. They’re also getting back into individual contributor work to experience tools firsthand.

“Leaders are looking to their teams for recommendations,” says Heather Phillips, an independent design leader and former design director at Slack. “At Slack, we had a channel where designers posted resources and inspiration, which surfaced ideas to management. For example, the Design Ops team rallied for budget and organized cohorts of designers to go through Elizabeth Lin’s Cursor training.”

There is still no standard playbook for supporting AI adoption within companies. Here are a few anecdotes from real design teams.

Maze 

After six months of open experimentation, designers at Maze have formed their own rituals, like dedicated design coding time and show-and-tell sessions.

Netali Jakubovitz, Maze’s VP of Product, says, “We started with a rigid AI adoption policy but quickly decided to switch to a culture of organic experimentation, going ‘bonanza,’ just giving people budget, permission, and time to explore freely. As a leader, I set up my own dev environment and created my own PRs, sitting with my designers to understand their day-to-day. It’s a brand new world, and as leaders we have to get to know it.”

Watershed

Watershed provides company-level AI enablement resources and office hours, and designers are encouraged to find an engineering buddy—a best friend on the team who can get the designer unstuck when their dev environment breaks or review a PR they want to ship.

“The number one thing our designers are asking for is dedicated time to learn,” says Hannah Hudson, Head of Design at Watershed. “They have all their environments set up—now they need time to really deeply build stuff. It can be intimidating to work with new tools, so they want office hours, hackathon time, whatever they need to make it more comfortable to jump in."

DoorDash

The DoorDash design team set a clear expectation for every designer to ship PRs to production. To make the process less intimidating, they ran a two-week setup period, followed by a two-day hackathon where the team shipped 200 PRs. Designers share their work and learnings in a dedicated Slack channel, supported by internal resources and trainings on setting up coding environments.

Shali Nguyen, Head of Consumer Experience Design at DoorDash, says, “Our VP of Design created a company BHAG—a big, hairy, audacious goal—for all designers to ship a high number of PRs to production each month. 

“It’s intentionally a big number, which has inspired a ton of conversations about what gets in the way, working with our engineering counterparts to improve the product development process and identifying how we help the teams with more training. We want to create those conversations to change how the company works.”

Stripe

Stripe creates the conditions for designers to experiment through broad tool access, brown bag sessions, external speaker talks, “AI vacations,” and more.

“We set the table to enable the party,” says Katie Dill, Stripe’s Head of Design. “We try to make as many tools as possible available to teams, and the teams take it from there. Folks have built incredible things internally and externally this way. No top down mandate, just people and their ideas. We also give folks an “AI-ication” once a quarter where they can take time away from their day jobs to play with new tools and build whatever they’re interested in. We celebrate this great work at the weekly company meeting with Stripe’s founders, inspiring others to try.

“We are comfortable with progress over perfection. When rolling out a new internal AI tool, we admit it will evolve and avoid mandating it. Our goal is simply to get better over time by learning from our teams’ experiences.”

53% of our respondents said they use company-funded external tools. Still, 42% report paying out of pocket for approved tools, and 21% use unsanctioned tools.

Last year, we noted that AI experimentation was bottlenecked by legal, security, and compliance constraints—now, many designers are routing around them or just building their own.

The companies unblocking adoption seem to be loosening control, not tightening it. Katie Dill, Head of Design at Stripe, notes three key tool adoption barriers that used to slow her team down:

• No room for risk. People felt stretched thin and didn't feel safe experimenting on top of their regular workload.

• Unclear permissions. Designers didn't know which tools were sanctioned or secure to use.

• No payment path. Even when tools were permitted, there was no obvious way to pay for them.

Stripe now offers "a cornucopia of options, no single prescribed tool," celebrates experimentation, and offers a library of internal agents anyone can leverage and add to.

At Samsara, David Stinnette gives every designer a $50/month tool stipend. At Ramp, everyone across the organization gets access to AI coding tools by default on day one. Designers can make PRs using a tool called Inspect, and Glass, their custom internal AI workspace, makes it easy for anyone to build their own apps from scratch.

As more designers experiment with AI tools and build custom workflows, design operations as a function may become increasingly important as a way to help design teams converge around a stack, surface experiments and lessons, and stay aligned as the pace and volume of work increases. 

Michelle Morrison, Senior Staff UX Program Manager at Google, points out that as teams gain the ability to generate many more design possibilities, this also creates more decisions that need to be made. She writes, “As execution becomes easier, organizations require rigor for understanding what work is happening across teams and why. Design Ops can help create visibility into experimentation, connect learning across projects, and support the pathways that turn exploration into direction."

In the past, design leaders may have brought in Design Ops to help scale a team. Now, with AI changing what a small team can do, it may be needed as a foundational role much sooner.

The lines between design, product, and engineering are continuing to blur. Many respondents (65%) say they’re doing more work that traditionally falls into PM, engineer, or design engineer territory, like implementation, coding, prototyping, research, and validation.

Designers are owning Linear tickets end-to-end, rather than handing them off. They’re also using agents to query company tools they didn’t previously have access to and piping real customer data into their prototypes to bring them closer to production. 

And on the flip side, 40% say their PMs and engineers are now doing more design work.

A third of respondents (34%) say collaboration has become messier, with roles and ownership less clearly defined than before. To complicate this, AI tools without collaboration features are creating version control challenges and silos where people work too independently. 

Taken all together, 20% of our respondents said that collaboration has decreased—4x more than 5% in 2025.

At the same time, the conversations we’ve had paint a nuanced picture. Many designers describe working more closely with engineers than ever before—by pair programming, reviewing code, and consulting on what one another is building. They’re working on the same surface with a shared language.

More designers are becoming orchestrators of AI systems, tools, and workflows—what Jessica Rosenberg, Head of Brand at AirOps, calls “Agent Captains.” They’re building the infrastructure that raises the quality bar for everyone by preloading design system components into coding tools so that any prototype starts at a shared quality baseline. They’re creating prompt libraries and AI skills that embed brand guidelines into workflows. See examples in Tools.

As professional boundaries blur, design is positioned to play a connective role that translates between disciplines, holding the vision and maintaining the quality bar. The shape of the role is changing too. “T-shaped designer”—deep in one specialty and broad across the rest—was the dominant model for years. Some are now describing a “block-shaped” designer instead, with strong capabilities across multiple disciplines at once. 

We’re seeing this shift in titles, too. Over the last few years, we’ve observed that "UX or UI designer" has become less common, with many teams opting for "product designer" to reflect end-to-end ownership rather than a narrow function. AI is accelerating that trend. Some companies are placing less emphasis on the distinctions between design, product, and engineering altogether, in favor of a shared focus on building and shipping.

Garrett Fowler, design recruiter and founder of Offsite, sees a deeper shift in how design roles are starting to split. “Over the last two decades, we've developed blueprints for what great design looks like—in mobile apps, growth design, vertical SaaS, and more,” he says. 

“Now, the blueprints are gone. We need people who think in blueprints again. Maybe we call them 'systems architects' or 'design architects,' while others are 'design crafters.' There will also be room for the best craftspeople—craft needs to be as high as ever, and the ability to work ambiguously with your craft.”

As tools give more non-designers the ability to create experiences—think Canva, Lovable, and Claude Design, with hundreds of millions of users—professional designers have a chance to go deeper and broader than we ever have before. Ultimately, designers need to stay accountable for the user experience, bringing empathy to solve problems, even when the surface area of who’s “doing design” expands.

Many designers feel the bar rising. Overall, 73% report feeling expectations rising. 45% indicate faster turnaround times, and 37% point to higher expected output volume.

The ground is shifting but still broadly unsettled. While these designers feel new expectations, just 28% of leaders said they’ve implemented formal changes in their organizations. A combined 13% of leader respondents have already updated their official performance review metrics or hiring practices. (Interestingly, a little over a third say they haven’t changed their expectations.) 

Half of respondents, including executives, managers, and ICs, say their teams haven’t made significant structural changes. Only 7% say their teams have added new AI-focused roles, like “AI design lead” or “AI design producer.” We believe we’ll see growth here in the coming years. 

19% report that their company has reduced headcount while expecting the same or more output. Only 8% say that the ratio of designers to engineers or PMs has shifted.

When we asked design leaders about their ideal makeup of a product team today, “product designer” was the most-selected role—but only 71% of leaders chose it, meaning that nearly a third of responding leaders may no longer see a product designer as essential to every product team.

Among the leaders who didn’t select “product designer” as a core role, 72% selected “design engineer” and 44% selected “AI design specialist.” 

This doesn’t mean the product designer is going away, but it suggests that teams are changing into new configurations that better match how AI-native teams work.

28% of design leaders surveyed plan to grow their teams, and 32% expect to keep headcount the same (while increasing output expectations). Meanwhile, 10% expect to reduce, and 21% aren’t sure yet. 8% say they’re shifting investment toward hybrid roles like design engineers. 

Even in organizations where headcount holds steady, expectations are expanding. In late 2025 and early 2026, engineering teams have accelerated output more dramatically with AI than designers have so far. 

The result: Each designer is being asked to cover more surface area, supporting a higher volume of engineering and product work without necessarily seeing proportional growth on the design side.

Half of the leaders we surveyed report that when they hire designers now, they’re placing greater emphasis on AI fluency, followed by systems thinking and strategic skills. 22% are placing more emphasis on technical or coding skills. Quality and polish are still important: only 5% are placing less emphasis on execution craft.

In qualitative responses, leaders described a landscape of hiring priorities that include technical skills, business sense, and good old craft fundamentals. And, perhaps most important of all: adaptability. 

Joel Lewenstein, Head of Product Design at Anthropic, says, “Because the job is changing so fast, we look for people who have explored a lot of the tools and really rethought their design process—you have to go through that molting almost every couple of months now. 

“We also look for strong opinions about what AI is going to mean. I wouldn’t expect candidates to know the right answer, but having thought through that set of problems to say, ‘this is the type of software I think people will be using in 3, 6, 18, 24 months.’

“The best designers I’ve seen are capable of mode shifting really fast between shining a spotlight on a mountaintop and saying, ‘That’s where we’re going,’ then putting the flashlight in front of them and taking a few steps forward. They’re writing production code, generating mockups quickly, and getting user feedback quickly to keep teams moving at the blistering pace we’re all moving in.”

Designers who can hold a vision of the future while executing on the details are more valuable than ever to teams navigating this new world.

Like leaders, designers value AI fluency and rank it as the top skill they want to cultivate. While 43% of respondents value coding abilities, even more selected capabilities like strategic problem framing, creative direction, storytelling, systems thinking, and business judgment.