Aug 21, 2025 · 40m · a16z
Can AI Fix Housing and Healthcare Affordability?
Mina Song · 18m spoken Tony Stoyanov · 9m spoken Alex Immerman · 4m spoken Erik Torenberg · 3m spoken
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gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions
In this episode of The a16z Podcast, EliseAI co-founders Mina Song and Tony Stoyanov join a16z Partner Alex Immerman to discuss how artificial intelligence can eliminate administrative friction and lower operational costs across housing and healthcare.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. The host holds 9.1% of the talking time here. How this is scored →
The host as informed peer 3.4 Guest teaching 3.6 Guest disagreement 0.9 The host pushing back 1.0
speaking balance: gold is the host, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 25:52 Mina dismisses tenant value extraction premise
When host Alex Immerman raises critical commentary that PropTech exists to help landlords extract value from tenants, guest Mina Song directly rejects the premise, calling it 'a pretty silly argument' and comparing it to denying technology in airlines or supermarkets.
Hardest push from the host ▶ 25:52 Alex challenges guests on PropTech tenant extractionHost Alex Immerman poses the podcast's sharpest challenge by directly asking how the guests respond to critics who view PropTech tools as rent-extraction mechanisms for landlords.
Biggest teaching moment ▶ 6:54 Tony details Minneapolis zoning impact statisticsTony Stoyanov educates the host on the real-world effects of ending single-family zoning, citing Minneapolis data where housing supply grew 3x faster than average and kept rents flat relative to a 31% national spike.
The host holds their own ▶ 12:17 Alex demonstrates knowledge of property management staffing ratiosHost Alex Immerman demonstrates domain expertise by introducing precise operational metrics from customer Equity Residential (200 units per employee baseline) and pressing for five-year efficiency projections.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | The host as informed peer | Guest teaching | Guest disagreement | The host pushing back | Why |
|---|---|---|---|---|---|---|
| The Mission Behind EliseAI | 3 | 1 | 0 | 0 | Hosts introduce their investment thesis and frame consumer price trends using internal charts. Guests respond standardly with macroeconomic statistics about household spending. | |
| Addressing the Housing Affordability Crisis | 2 | 4 | 0 | 0 | Host prompts on supply unlocks while guest Mina details precise figures regarding the five million housing unit deficit and ALN empirical data on occupancy gains. | |
| Regulatory Bottlenecks and Zoning Reform | 4 | 5 | 1 | 2 | Host Erik frames global comparison with Tokyo zoning, while guest Tony educates with concrete data from Minneapolis showing flat rent growth after ending single-family zoning. | |
| Software as a Lever for Constrained Markets | 4 | 3 | 1 | 1 | Host Alex cites specific municipal contexts like San Francisco vacancy rates and local political initiatives, while guests discuss operational efficiency levers. | |
| Fully Autonomous Buildings and Staffing Ratios | 5 | 5 | 1 | 1 | Host Alex demonstrates domain expertise by citing baseline unit-per-employee ratios at Equity Residential. Guest Mina reframes expectations by sharing Brookfield's 1-to-10,000 ratio. | |
| What AI Automates Today in Housing | 2 | 4 | 0 | 0 | Host asks an open question on automation scope, and Mina provides concrete performance metrics on work order and listing duration reductions. | |
| The Future of Onsite Real Estate Staff | 2 | 4 | 1 | 1 | Host asks about labor displacement, and guests gently reframe displaced roles as specialized career paths while pointing out underlying demographic labor shortages. | |
| Long-Term Outlook: Demographics, Robotics, and Flexible Leases | 3 | 3 | 0 | 0 | Host raises macro topics including robotics, longevity, and AGI. Guest Mina connects longevity and fertility dynamics back to housing affordability and flexible leasing. | |
| Why Real Estate Underinvested in R&D and How AI Changes It | 6 | 5 | 6 | 5 | Host Alex delivers direct pushback by asking how guests answer critics who say PropTech extracts rent from tenants. Guest Mina forcefully rejects the premise calling it 'a pretty silly argument'. | |
| AI Orchestration for Maintenance and Unit Turnover | 3 | 3 | 0 | 0 | Host asks about turnover and maintenance delays; guest Tony explains physical dependencies in task sequencing and scheduling optimization. | |
| The Parallel Operational Challenges in Healthcare | 4 | 4 | 1 | 2 | Host Alex recounts his initial skepticism toward entering healthcare. Guest Tony explains how administrative intake and phone interactions mirror housing workflows. | |
| Bending the Healthcare Cost Curve | 5 | 4 | 1 | 2 | Host Erik sets up an economic elasticity trade-off regarding healthcare spending. Guest Tony reframes by separating clinical outcomes from administrative overhead bloat. | |
| Transforming Patient Care Beyond the Clinic | 3 | 2 | 0 | 0 | Host Alex provides a concrete scenario on patient discharge adherence, which the guests expand upon collaboratively. | |
| Lessons Learned: Targeting Affordable Housing First | 2 | 4 | 0 | 0 | Host asks a retrospective question. Guest Mina shares a counter-intuitive insight about starting in high-complexity sectors like affordable housing. |
Statements from this episode (33)
Song: Housing and healthcare consume 42% of household budgets and 40% GDP
“They eat up about 42% of what a typical household makes, and nationally these sectors make up about 40% of the entire GDP.”
Immerman: Tech-impacted costs fall over time while housing and healthcare rise
“If you look at housing and healthcare, as Mena just said, like prices just go up, up, up to the right and any industry that technology has touched has gone down.”
Song: US needs 2 million new housing units annually to prevent shortfall
“We're about five million housing units short of what we actually need in the country, and we need to add somewhere between 1.8 to two million units per year just to kind of keep that shortage from getting worse, let alone making up for that deficit.”
Song: Analysts project US housing construction pipeline will drop 50% by 2026
“And actually, analysts say that the pipeline is shrinking for twenty-twenty-six and beyond, so they said it's gonna drop by about 50%, so we're headed in the completely wrong direction.”
Song: Nearly half of all rental apartment inquiries receive no response
“So, I'll give you an example, which is almost half of inquiries that go to a rental apartment building Never get responded to.”
Song: EliseAI boosts apartment occupancy by 2% over the market average
“Earlier this year, we provided data to an organization called ALN and found that buildings using RAI had two percent higher occupancy compared to market.”
Stoyanov: Minneapolis zoning reform kept rents flat while US rents rose 31%
“Minneapolis is a great example. They did a big housing reform. Part of that was actually ending single family zoning rules there. And that happened back in two, 20,019. And I think ever since that we've seen like supply has grown three times faster than the na…”
Song: Real estate historically underinvests in technology compared to SaaS companies
“Real estate has not invested a ton in technology. So it hasn't gotten a lot of the efficiencies that, you know an internet company or, you know, a SaaS company Could achieve.”
Stoyanov: San Francisco's residential housing vacancy rate is approximately 3.5%
“SF vacancy rate is at about three and a half percent today”
Song: Labor is the largest controllable operating expense in property management
“The biggest controllable expense is labor.”
Immerman: Equity Residential manages 200 housing units per employee using EliseAI
“I know with Equity Residential, one of your customers, they've gotten up to 200 units per employee.”
Song: EliseAI aims to enable fully autonomous buildings with zero human management
“Our goal is to enable fully autonomous buildings. So that means an entire portfolio has the ability to run core operations without requiring human intervention at all.”
Song: Brookfield Properties uses EliseAI to let one employee manage 10,000 units
“Brookfield properties is another one of our customers. They're building this centralized model that enables a single employee to serve as multiple properties. And they're actually finding that they can get a single employee to work across 10,000 units using AI…”
Song: EliseAI workflows cut maintenance completion times to under 48 hours
“And we see that some operators with this new, these workflows have cut average work order completion times from Four to five days down to under 48 hours, so that's really meaningful for residents.”
Song: EliseAI cuts apartment listing-to-lease times from 30 to under 14 days
“Actually cuts down average time for our customers from about 30 days from listing an apartment to leasing it to under 14 days because It gives you so much more flexibility to tour around the clock.”
Stoyanov: Multi-building AI maintenance sharing will unlock dramatic efficiency gains
“But for something like maintenance, we expect to see a lot more dramatic gains once you go on the ecosystem level.”
Song: Real estate jobs will shift to AI-enabled roles rather than disappear
“I think as AI takes over a lot of the communication and logistics, human roles don't all disappear. They just, these sort of AI enabled career paths start to emerge.”
Song: Real estate workers will eventually manage large workforces of AI software
“But I think in the long run, people will be managing big workforces of AI and sort of overseeing these automated systems that are mainly running most of the work.”
Stoyanov: A large proportion of current property maintenance technicians are over 50
“A lot of the maintenance technicians today are actually over 50 years old”
Song: Cost of living is the primary reason people forgo having children
“Cost of living is actually one of the, it is the number one reason that people don't have more children.”
Song: AI automation makes short-term rental leases scalable and affordable
“AI doesn't really care if it's signing shorter term leases. It's just doing, you know, it's doing that over and over and it scales. Then you kind of get the benefit for the, both for the landlord and for the consumer that they can be more, They can do it at a …”
Song: Traditional real estate software failed because it couldn't handle operational variability
“In the past, you've really just needed a person because traditional software couldn't handle the variability that was required. So, if you needed a person anyway, there wasn't really a motivation to buy technology.”
Song: Real estate could shift from lowest R&D to top AI spender
“Real estate is so far behind on tech, it actually has the most to benefit from AI. So it maybe is going from the lowest R and D spending to potentially one of the highest spenders on AI.”
Stoyanov: Banning technology in an industry never leads to lower consumer costs
“I cannot think of a single example where, you know, technology was banned and then costs went down. I think that just never happens.”
Immerman: Economic surplus created by technology typically accrues to consumers
“So generally when technology is introduced, you see a surplus and most of that typically goes back to the consumer.”
Song: Cutting nationwide apartment turnover time by one day unlocks billions
“Every day you shave off from the average unit turn time nationwide unlocks billions of dollars in value.”
Stoyanov: Voice AI built for housing translated directly to healthcare administration
“We developed our voice technology over the housing space and that has translated really, really well in the healthcare space. And the same thing with a lot of the scheduling optimizations we've been doing have translated quite, quite well.”
Stoyanov: Healthcare and housing share nearly identical administrative operational structures
“So they kind of feel very, very different, but from admin organizational operations perspective We, we've barely been surprised by anything by transitioning to healthcare.”
Stoyanov: Healthcare administrative costs have grown significantly faster than clinical care costs
“And I think the costs on the admin side have really skyrocketed. Way faster than anything on the clinical side.”
Song: AI-driven treatment plan fulfillment will significantly cut government healthcare costs
“If AI can scale and achieve better Treatment plan fulfillment. That's going to be better for everybody. It's certainly going to save us a lot of costs. You know, it's one of the government's largest expenses. And so we're all paying for that. Those outcomes be…”
Song: EliseAI would have launched in affordable housing first if starting over
“I probably would have started with affordable housing, actually.”
Song: Solving the most complex market segment first eases downstream expansion
“We're actually kind of approaching healthcare in a similar way, which is start with what is the most underserved, because that's where we can have the largest impact. The most underserved and the most complex, because if you sort of solve those problems, then …”
Song: AI can reduce household spending on housing and healthcare to 20%
“I think if we can take this 42% of what a household spends on housing and healthcare and bring that down to, you know, 20 something percent. That is, I think the, one of the large, most important problems we can solve and more people should be working on it.”