What a Car Door Taught Me About AI Design for Aging Brains

My first car had a 6-volt battery and a personality. Most mornings it started. Some mornings it needed a push. It was a 1965 VW Beetle, and even on the mornings it needed that push, a 68-year-old could have slid into the driver's seat and felt immediately, completely at home.

The door handle was exactly where your hand expected it. The seat put you in a natural position without adjustment rituals. The dashboard offered a speedometer, a fuel gauge, and nothing else competing for your attention: a key, a choke, a steering wheel. You understood the entire system before you reached the end of the driveway, with no tutorial, no onboarding, and no moment of feeling lost or behind.

That feeling of immediate competence is rarer than it should be. And it turns out to be one of the most important things a well-designed system can give any user.

Now picture a 68-year-old getting into a new EV fresh off the dealership lot in 2026. The central touchscreen is large, sharp, and quick to respond, exactly what younger reviewers love. For an older driver, that same glowing screen, with most features buried deep within menus, is less a convenience and more a source of distraction and frustration before they've even left the parking lot. Add a voice assistant that may or may not understand you, driver assistance systems requiring configuration, and climate controls that no longer have physical buttons, and you have a vehicle that is extraordinary by every engineering measure. But the first emotion it produces isn't confidence. It's friction.

Same task. Radically different cognitive experience. And a completely different relationship between the user and their own sense of capability.

That contrast, between the functional dignity of simple design and the cognitive overwhelm of complex interfaces, is exactly what a leading automotive manufacturer recently brought to AARP's AgeTech Collaborative™ to solve. And what they discovered in the process has implications that extend far beyond the driveway.

The Automaker Who Asked the Right Question

Late in 2025, a major automotive manufacturer engaged the AgeTech Collaborative's Design Thinking team to explore something surprisingly specific: how do age-related cognitive, physical, and sensory changes affect every aspect of how older adults interact with a vehicle? Not just the seat height, not just the door handle, but every touchpoint, from entering and exiting to operating controls to staying confident on the road.

The central design challenge they landed on was this: "How might we create a flexible and intuitive driving experience for older adults as their cognitive abilities change?"

Read that carefully. Not for older adults who have cognitive decline, but for older adults as their cognitive abilities change. That's a meaningful distinction. It acknowledges that aging is not a binary event, a moment when someone flips from capable to incapable. It's a gradual, nonlinear process that good design should anticipate and accommodate across a spectrum.

The team used human-centered design methods: clue gathering from national research data, insight generation workshops, structured ideation. They emerged with four high-potential solution concepts built around reducing cognitive load, enhancing intuitive use, and preserving driver confidence and dignity. They didn't just design for safety, they designed for autonomy.

The Same Brain Walks Into a Doctor's Office

Here's where it gets interesting for those of us working in HealthTech and AgeTech.

The cognitive challenges that make a redesigned EV dashboard overwhelming for a 68-year-old driver are the same challenges that make a patient portal confusing, a telehealth interface frustrating, and an AI health assistant feel threatening rather than helpful.

We know this because AARP Research asked. In a series of focus groups with adults aged 40 to 65, segmented by AI familiarity, the AgeTech Collaborative found that perceptions of AI ranged from negative to mixed, with very few overwhelmingly positive responses. Participants described AI as a "double-edged sword," simultaneously fascinating and scary, beneficial and confusing, simplifying some things while complicating others. Their biggest concerns were privacy and fraud, lack of regulation, and the fear of losing the human touch from interactions and communication.

But here is the finding that should stop every HealthTech product leader cold: many participants didn't avoid AI out of disinterest. They avoided it because they didn't know how to use it. This is not resistance dressed up as a demographic problem; it's a design failure.

The market is interpreting older adults' hesitation as skepticism toward technology. But the data suggests something more specific and more actionable: people who cannot see themselves in an interface will not use it. When an AI tool fails to pick up on nuance, humor, or context, as several focus group participants described, it doesn't just frustrate them once. It closes the door. And in healthcare, a closed door can have real consequences.

What Good Design Actually Looks Like

The automotive case study and the AI perception research, read together, point toward a set of design principles that apply across both domains.

• Design for changing ability, not fixed ability. The automaker didn't design for a static snapshot of "the older driver." They designed for a person in motion, cognitively, physically, and experientially. HealthTech AI should do the same. An interface that works for a sharp 65-year-old should gracefully adapt as that same person navigates changes over the next decade.
• Reduce cognitive load at every touchpoint. The Beetle's genius was that it demanded almost nothing from your working memory. Modern HealthTech often demands everything: new logins, unfamiliar terminology, multi-step verification, menu structures that require a tutorial. Every unnecessary step between a patient and their care is a potential dropout point.
• Preserve dignity and autonomy. This was explicit in the automotive brief, and it belongs in every HealthTech product spec. The goal isn't to manage older adults through a system; it's to give them genuine control: informed, confident, and independent. There's a meaningful difference between an AI that does things to a patient and one that works alongside them.
• Build trust incrementally. The AARP research found that negative early experiences with AI tools, such as a chatbot that missed the point or a voice assistant that couldn't parse an accent, created lasting reluctance. Trust, once lost to a poor interface, is hard to rebuild. This argues for conservative, high-quality first interactions over feature-rich but fragile ones.
• Make the invisible visible, simply. Philips recently identified agentic AI as one of 2026's defining healthcare trends. This is AI that operates within clinical workflows with context and intent. The best clinical AI, they noted, is the kind clinicians barely notice. The same standard should apply to patients. When AI works well in healthcare, it shouldn't feel like AI. It should feel like care.

The Market Is Moving. Is the Design?

The digital health market is in the midst of an accelerated transformation. Telehealth has become a central pillar of modern care delivery. Remote patient monitoring is scaling rapidly. AI is reshaping clinical decision-making across imaging, diagnostics, and treatment planning. Investments are flowing.

But scaling a flawed interface doesn't fix the interface. It just delivers frustration to more people, faster.

The 65-and-older population is the fastest-growing demographic in digital health and one of the most underserved by the design assumptions baked into most platforms. These are not fringe users. In the United States alone, all 73 million Baby Boomers will be 65 or older by 2030. They represent enormous healthcare utilization, significant purchasing power, and genuine openness to technology that earns their trust.

This isn't entirely new thinking in automotive design. Ford has been putting engineers inside age-simulation suits since the 1990s, letting young designers physically experience the mobility, vision, and hearing limitations older drivers live with every day. The automotive industry has known for decades that designing for aging requires more than data. It requires empathy at the drawing board.

More recently, a different automaker took that commitment further still, engaging AARP's AgeTech Collaborative to run human-centered workshops and build solution concepts around what one can call cognitive dignity: the user's right to feel capable, not managed, by the technology around them. That is not a small thing. That is a signal.

The question worth asking is why HealthTech hasn't followed suit.

A Challenge to AgeTech Builders

If you are building HealthTech products, leading an AgeTech startup, or investing in the future of digital health, this is worth sitting with.

The design principles that make a vehicle intuitive for an aging brain are not automotive principles. They are human principles: reduce load, build trust, preserve autonomy, anticipate change, make complexity invisible.

Your users are not resistant to your technology. In many cases, they are waiting for technology that was actually designed with them in mind.

The car door is getting reimagined. The patient portal, the telehealth interface, the AI health companion, these are overdue for the same honest rethinking.

What would your product look like if you started with the question AARP's Design Thinking team asked? "How might we create a flexible and intuitive experience for older adults as their cognitive abilities change?" That question doesn't belong only in automotive design. It belongs on every product roadmap in this space.