Image generated by the author using Midjourney, modified in Photoshop.

Spoiler Alert: This Isn’t an AI Panic Piece

Every time AI gets better at something — writing, coding, designing — the headlines arrive in a panic. Is authorship dead? Are developer jobs doomed? Has design been reduced to multiple-choice curation?

Great clickbait. But not the kind of question creative minds ask.

Sure, OpenAI and Anthropic predict AI will automate “essentially all of the code” for software. If that’s true, they’ll also take over much of the UI/UX assembly work — remixing the patterns designers spent decades codifying into today’s norms.

That idea can feel alarming. But panic isn’t a creative state of mind. Designers, strategists, and product teams do their best work by asking: What can we do now that we couldn’t do before?

Here’s one answer: if AI can cover predictable experiences for the majority then human designers can finally return to the frontier. To “edge cases” that have been too messy and costly to address, but which will stretch our empathy and creativity. That’s not a nightmare. That’s the work that drew us into this field in the first place.

The Old Playbook: Design for the 80%

For decades, UX followed a simple playbook:

• Generalize audiences into “typical” personas.
• Optimize for the majority.
• Avoid risks.
• Ship fast, scale wide.

If most people were “mostly satisfied,” the job was done. Maybe you added a Spanish version or checked the WCAG box. Then everyone hoped for a bump in conversions.

It wasn’t a failure of imagination. It was economics. Time, talent, and budget were finite. Edge cases drove up costs, raised risks, and threatened to compromise the core. So the few got left behind while the many moved forward.

For a while, this worked. But even “normal” audiences often face friction that the 80% rule can’t solve. Imagine a mother trying to check out on a grocery app with a baby on her hip. Screen timeouts, tiny tap targets, no way to adapt to her reality. That’s exactly the kind of problem rarely solved under the old playbook.

The AI Reality: Speed, Scale, Sameness

Generative AI changes the math. It thrives on predictability — and predictability is exactly what UX has optimized over the last 15 years.

• B2B SaaS: AI can spin up onboarding flows and dashboards faster than you can get through a standup.
• Healthcare: AI already manages reminders, scheduling, and first-line symptom checks.
• Banking: Balance checks, transfers, and bill pay are AI’s bread and butter.

AI doesn’t need to be creative to do this well. It just needs patterns. And we’ve given it decades of them.

We can lament — or we can call this a job well done and move on. The prize isn’t going to be another 2% lift from the mainstream. The prize is at the edges.

The Edges: Small Populations, Big Impact

Edge cases are where life breaks the template:

• A warehouse worker is forced to watch mandatory video training on a noisy factory floor.
• A parent juggling Zoom calls with toddlers and Cheerios flying.
• 12–15% of the global population experiencing migraines.
• 49 million Americans working outdoors where glare makes “subtly beautiful” UI useless.

Historically, these were considered “too costly” to fix. But add them up, and you see enormous opportunity:

• Accessibility: 20% of the U.S. population lives with a condition affecting digital use. Globally, 2.5B people rely on assistive tech. That’s not an edge. That’s a continent.
• Situational Accessibility: Loud coffee shops, broken arms, migraines, grief — at any given moment, we imagine another 20% of the population is temporarily impaired.
• Cultural & Regional Variation: 19.5% of the U.S. identifies as Hispanic. Translating to Spanish isn’t enough; designing for cultural norms like shared family decision-making (“familismo”) opens new adoption.
• Varied Tech Literacy: 10% of Americans don’t own a smartphone. Among adults 55–59, nearly 40% don’t use the internet. Intuitive doesn’t necessarily mean universal.

The AI Dividend: Design Bandwidth to Dive Deep

If AI can deliver competent mainstream experiences efficiently, human designers gain bandwidth to go deeper.

• B2B SaaS: Competitive advantage will come from designing workflows for niche industries no algorithm can guess.
• Healthcare: Breakthroughs lie in human+AI systems that coordinate care for multi-condition patients and their families.
• Financial Services: Loyalty isn’t in automating transfers. It’s in designing for small businesses, cross-border families, and people navigating high-stakes financial events.

This is where churn happens — or doesn’t. Where loyalty is won — or lost. Where tomorrow’s leaders will break away from today’s.

Why Designers Should Embrace the Shift

AI producing familiar artifacts may sound like a door closing. But it’s another door opening: back to the meaningful work that made UX matter.

Designing for edge cases is:

• Invigorating: New research, empathy, hypotheses, and discoveries.
• Self-perpetuating: New patterns will evolve and drive efficiencies that allow the focus to push out even further until the future is almost 100% personalized.
• Creative: AI can remix the past. Only humans can imagine futures that don’t exist yet.
• Impactful: Transforming design team frustration into inclusion and delight.

History proves it. Every time technology automates one layer of design — desktop publishing, responsive frameworks, gamification — design hasn’t died. It’s evolved.

The Business Case: Edges as Growth Engines

What used to be a cost center is becoming a growth engine. Designing for accessibility, personalization, and cultural nuance isn’t charity. It’s strategy.

• Reaching the proverbial 10% of the estimated 3.2B underserved users globally = 320M new customers.
• Supporting ADHD or color blindness unlocks millions of new users.
• Edge-focused personalization builds loyalty in markets where mainstream UX is already commoditized.

In short: the competition isn’t at the center anymore. AI is being positioned to own that. The new competition is at the edges — where adoption, loyalty, and revenue are waiting.

Where We Find Ourselves

Our theory is that the edges are the next competitive frontier. The edges will redefine the center, and the organizations bold enough to invest there will set the pace for everyone else.

We’re already exploring what this looks like in practice. If you are too, reach out. Let’s compare notes, swap ideas, and maybe build something that changes the game.

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Authors’ Note:

This article was co-authored as an experiment in collaboration between Toodd Zerger and Matthew Doty as co-authors, and ChatGPT 4.0 in the role of editor to help us merge our unique perspectives and decidedly different writing styles. Our objective was to test the industry premise that AI can augment our creative and publishing practices without replacing any step we didn’t want to delegate.

An unexpected revelation came when trying to co-author on platforms designed for singular authorship. Rather than stumbling over this limitation we are using it to our advantage - allowing each author to publish to suit their personal brand, while sharing appreciation and credit. If joint efforts between AI and human collaborations are the new norm, maybe co-authorship functionality is also a new edge case worth exploring.

Image Midjourney Prompt:
A Beatrix Potter illustration of an anthropomorphic fox wearing dark glasses and dressed in a tweed suit and walking while using a white cane with a red tip as used by blind people. The fox is walking toward the camera along a narrow path that on both sides overlooks the wild and rocky Northern California coast. Cinematic, highly detailed, surreal.

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Originally published on LinkedIn 10.08.2025 as part of an ongoing series of articles exploring the context and implications of GenAI relative to the creative enterprise.