Episode summary
Can AI Fix Housing and Healthcare Affordability?
The a16z Show
· · Hosts: Erik Torenberg · Guests: Alex Immerman, Minna Song, Tony Stoyanov
Summary
The discussion argues that housing and healthcare are both huge cost centers because they are operationally inefficient, highly regulated, and still run with too much manual labor. A guest said housing and healthcare together absorb about 42% of a typical household’s spending and roughly 40% of GDP, making them obvious targets for AI-driven waste reduction.
On housing, the guest said the U.S. is about 5 million units short, with annual supply still below what is needed and the pipeline for 2026 and beyond shrinking. The panel argued that AI can help even before new supply arrives by improving leasing, maintenance, turnover, compliance, and utilization; one example cited was buildings using the product reaching 2% higher occupancy than market.
The conversation also focused on the limits of regulation and capital. A guest said zoning reform matters, but so do returns: if AI makes operators more efficient and profitable, more capital should flow into housing construction. The host and guests extended the same logic to healthcare, where they said administrative workflows, scheduling, intake, and post-visit follow-up are structurally similar to housing operations and still ripe for automation.
Key takeaways
- A guest said housing and healthcare together consume about 42% of a typical household’s spending, making them the clearest targets for AI cost compression.
- The guest said the U.S. is about 5 million housing units short and needs roughly 1.8 to 2 million new units per year just to stop the gap from widening.
- The guest said AI is already improving housing utilization, citing data that buildings using the product had 2% higher occupancy than market.
- The guests argued that labor is the biggest controllable expense in property operations, so automating leasing, maintenance, and scheduling can meaningfully improve margins and affordability.
- On healthcare, the guests said the biggest near-term opportunity is the admin side—intake, scheduling, billing, and follow-up—not the clinical side.
- The guests said the long-term goal is fully autonomous buildings and more AI-enabled healthcare workflows, with humans shifting toward relationship-heavy and specialized roles.
Notable quotes
“We're about 5 million housing units short of what we actually need in the country”
“Housing and healthcare are the biggest expenses that people have. It's pretty self-evident that technology makes the experience better for everyone and brings down costs”
“Our goal is to enable fully autonomous buildings. An entire portfolio has the ability to run core operations without requiring human intervention at all”
“we found like those problem sets are quite similar. you kind of see like these very bloated cost structures that um you know have so many inefficiencies”
“the biggest controllable expense is labor. So AI being used to automate and and eliminate a lot of the manual and inefficient workflows can help a lot”
How the episode opens
We're about 5 million housing units short of what we actually need in the country. Our goal is to enable fully autonomous buildings. An entire portfolio has the ability to run core operations without requiring human intervention at all.
Housing and healthcare are the biggest expenses that people have. It's pretty self-evident that technology makes the experience better for everyone and brings down costs and more people should be working on it. Alex, we're we're honored to announce our latest investment in Elise AI.
Mina, Tony, welcome to the podcast. Welcome to the portfolio. Thank you.
Excited. Why don't you guys give us give us a brief background or give the audience a brief background on on on why lease AI? Why housing?
Why healthcare? We wanted to use AI to solve real world problems. And housing and healthcare are the b biggest expenses that people have.
They eat up about 42% of what a typical household makes. And um nationally, these sectors make up about 40% of the entire GDP. So it's pretty obvious that we need to figure out how to cut waste in these in industries.
It was pretty crazy to us that not enough people were working on these problems. Top technology people, for example, are not asking the hard questions about how can we actually fix it. It's just sort of an accepted tax that we all pay.
So we started digging a lot deeper into how these systems operate and once you do that you can see inefficiencies everywhere you look and those really add up to huge costs to all of us. And it's also not just about the money but the quality of these services has a really big impact on people's lives. Um, and when they fail, it doesn't just hurt individuals, it actually hurts kind of society as a whole.
From the episode’s captions: roughly the first two minutes, lightly cleaned. Keep watching on YouTube →
Topics
- ai for housing
- healthcare scheduling
- property automation
- housing supply shortage
- regulatory and capital barriers
Companies and tickers mentioned
- EliseAI
Watch the episode
Watch “Can AI Fix Housing and Healthcare Affordability?” on YouTube
Summary, takeaways and quote selection by Octagon. Quotes are short excerpts; the full conversation is in the episode.
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The a16z Show, this episode and its artwork belong to Andreessen Horowitz. Octagon is not affiliated with the show; this page is an independent summary.
