The conversation around AI in product design is no longer hypothetical, it’s shaping the day-to-day work of designers, researchers and product teams. Having recently spoken with Martyn Gooding- AI Product Design Manager, who sits at intersection of Design and AI with Microsoft, a few key themes stand out: the pace of change, the rise of polymath design teams and the looming challenges of compliance and trust.
Design roles are evolving at unprecedented speed with the old boundaries between design, research and engineering blurring and in many cases, collapsing altogether due to the rise of AI products. With Designers now able to build in minutes with Vibe Code and Developers able to communicate design where does the line lie between the two roles?
New platforms like Weavy.ai (node-based prototyping) and Figma’s AI-powered features are opening up new possibilities for speed and creativity. Storyboards that once took days can now be generated in minutes and Designers can move fluidly between research, prototyping and iteration in ways that weren’t possible even a few years ago.
But it’s not without friction. Large companies face strict compliance barriers, while start-ups seemingly can test and launch products in a matter of days. It seems enterprise teams are restricted from using some AI tools due to IP and legal risks. For many, only “safe” tools like Adobe Firefly are on the table, creating frustration and slowing experimentation.
Whilst AI adoption is filled with positivity there are some key challenges and conversations emerging in the space that need to be considered.
The first is Legal and Ethical Constraints. Although quick and increasingly more accurate, AI-generated content comes with compliance baggage. As regulations like the EU AI Act mature, designers will need to build responsible patterns into UIs: transparency, user control and trust. These aren’t just nice-to-haves, they’ll be required by law.
Perhaps not strictly an AI generated consideration, but one that’s certainly heightened by the increase in AI implementation is the role of The Specialist vs. Generalist. Design leaders are already asking: do we need deep specialists or versatile polymaths who can research, code, animate and ship? The reality is and likely always will be both. But one trend that does seem to be on the rise is the demand for “Super ICs” (individual contributors who mentor, prototype, and deliver).
For now, many Agencies and Consultancies with specialist AI arms seem to be taking advantage of the goldrush for AI adoption, supporting businesses that want but don’t know how to adopt and implement. But what happens when organisations reach AI maturity and realise, they can build quickly in-house? Clearly agencies and consultancies must redefine their role in a world where software isn’t scarce but strategic guidance and responsible design still are.
The next few years will test product design teams on multiple fronts:
- Compliance-first creativity: how to design experiences that are AI-powered, yet ethical and transparent.
- The rise of polymath teams: not everyone will do everything, but the blend of research, code and design will define the most valuable contributors.
- Continuous learning as culture: echoing Satya Nadella’s “learn-it-all” mantra, curiosity will matter more than credentials.
- Super ICs and the end of silos: fewer managers, more hands-on experts who can mentor and build.
- Agencies at a crossroads: shifting from execution to AI-first strategy and advisory roles.
To summarise a debate and blog post that could go on for pages and pages, AI is not replacing designers as some of us may be fearing but it is reshaping what design means. The future belongs to those willing to embrace polymath skills, navigate compliance with creativity and continuously learn in a space that changes by the week.
As Martyn put it “AI will eat the cheap work. What’s left is the work that really matters – the kind that requires human judgment, strategy and imagination.”