How AI is reshaping the way organizations design, build, and ship.

The State of AI in Design report provides insight into how AI is reshaping digitally native, product-led organizations where shipping digital products and services is core to the business. These organizations are using AI to rethink how products are planned, designed, built, and delivered, often with experimentation and process evolution as a natural part of how they operate.

Reading the report, however, we couldn't help but think about the broader enterprise market. From our own experience, many of these organizations are on a different trajectory, cautiously integrating AI into existing processes, governance models, and operating structures. Unlike organizations built around digital product development, they're balancing decades of technology investment, regulatory requirements, and organizational complexity. The result is a slower, more measured pace of change.

As AI adoption accelerates, a gap is emerging between organizations that are fundamentally changing how they design and build, and those that are simply optimizing existing ways of working. That's an important distinction, because not every organization is able to evolve at the pace of startups and scaleups.

Whether you're building digital products inside big tech or leading digital transformation within an enterprise, the trajectory may be different, but the challenge is the same: how do you leverage AI to create meaningful value for customers while evolving the way your organization designs, builds, and delivers better digital products and experiences?

The report raises important questions for organizations of every size. Below are the four themes that stood out most to us, and why we believe they matter well beyond the design function.

AI is reducing the cost of experimentation.

One of the clearest themes throughout the report is that AI is changing the speed at which ideas can be explored and validated.

According to the survey, 91% of designers now use AI every week, with many incorporating it across nearly every stage of the design process, from early research and ideation through to prototyping and implementation. Half of respondents report having shipped AI-generated code, while interactive prototypes are increasingly replacing static mockups as the primary way to communicate and evaluate ideas.

This points to something bigger than productivity gains. AI is dramatically reducing the time and effort required to move from concept to something tangible. Teams can generate more ideas, test them earlier, gather feedback faster, and iterate before significant time or resources have been invested.

For organizations investing in digital products and experiences, this changes the economics of innovation. Experimentation becomes less expensive, feedback loops become shorter, and product development becomes more iterative.

Ultimately, the biggest advantage isn't that AI helps teams produce more work. It's that it reduces the cost of learning. Organizations that can validate assumptions, learn from customers, and adapt more quickly will consistently outperform those focused solely on increasing output.

Competitive advantage is moving upstream.

One interesting point raised in the report is that while AI is accelerating execution, it isn't replacing the need for strategic thinking. In fact, respondents consistently ranked understanding users, strategic framing, creative direction, systems thinking, and visual judgment as the areas where human expertise continues to deliver the greatest value.

As the effort required to produce concepts, prototypes, and even production-ready code decreases, the questions that matter most become: What should we build? Who are we building it for? How does it create value?

These have always been important questions, but AI makes them even more critical.

As execution becomes easier, the quality of decision-making becomes a greater source of competitive advantage. Which opportunities deserve investment? Which customer problems matter most? Where should organizations differentiate? AI can accelerate execution, but it can’t decide which direction is worth pursuing.

Organizations that deeply understand their customers, identify the right opportunities, and create distinctive products, services, and experiences will continue to differentiate themselves, regardless of how quickly competitors can replicate them.

This is also why brand continues to increase in importance. As AI lowers the barriers to building software and digital experiences, competitive advantage increasingly comes from creating distinction, building trust, and communicating value in ways that are difficult to replicate, a theme we explore in our article: Why brand matters more than ever for B2B technology in the age of AI.

AI isn't reducing the need for strategic thinking. It's increasing its value. As execution becomes faster and more accessible, organizations that make better decisions before the work begins will create stronger, more enduring competitive advantage.

AI is changing how organizations collaborate.

While much of the conversation around AI focuses on individual productivity, one of the more significant shifts outlined in the report is how teams are starting to work differently.

Across many digitally native organizations, the traditional boundaries between design, product, and engineering are becoming more fluid. AI is making it easier for specialists to contribute beyond their traditional disciplines. Designers are experimenting with code, engineers are contributing earlier in the design process, and interactive prototypes are becoming the shared language of product development.

The result isn't the weakening of specialization. Instead, it's a more connected way of working, where teams spend less time handing work from one function to another and more time solving problems together. Conversations shift from debating concepts to testing real experiences, enabling faster decisions and shared ownership throughout the process.

For enterprise organizations, this transition will likely take longer. Existing structures, governance models, and ways of working are often deeply embedded. But the direction is becoming increasingly clear. AI isn't simply changing how individual roles operate. It's changing how organizations design, build, and deliver digital experiences.

The organization becomes the competitive advantage.

Perhaps the most interesting takeaway from the report isn't about AI adoption itself. It's what AI adoption reveals about where competitive advantage is shifting.

Digitally native, product-led companies are using AI as an opportunity to rethink how products are conceived, designed, built, and delivered. They're redesigning workflows, redefining roles, shortening feedback loops, and creating operating models that support continuous experimentation and iteration.

Many enterprise organizations, by comparison, are taking a more measured approach. Rather than redesigning how work gets done, they're integrating AI into existing processes, governance models, and approval structures. Given the complexity, scale, and regulatory requirements many enterprises face, that approach is understandable.

This has implications far beyond technology. As AI capabilities continue to advance, the limiting factor is becoming less about access to the technology itself and more about an organization's ability to adapt. While new tools can be deployed quickly, evolving governance, decision-making, incentives, and ways of working takes considerably longer.

The question is no longer whether organizations will adopt AI. It's whether they're prepared to evolve alongside it.

Closing the divide.

The State of AI in Design report is ultimately less about AI tools than it is about organizational evolution. While its findings are rooted in digitally native, product-led companies, the lessons extend well beyond technology and design. They offer a glimpse into how customer experience, product development, and collaboration are likely to evolve across every industry.

Enterprise organizations don't need to operate like startups to be successful. But they do need to recognize that AI represents more than a productivity gain. As execution becomes faster and more accessible, the opportunity is no longer just to improve existing workflows, but to rethink how products and experiences are conceived, built, and delivered.

The most significant divide won't be between organizations that use AI and those that don't. It will be between those that rethink how they design and build, and those that simply layer AI onto existing ways of working.

Be sure to check out the full State of AI in Design report here.