AI transcript
0:00:05 We’re about 5 million housing units short of what we actually need in the country.
0:00:08 Our goal is to enable fully autonomous buildings.
0:00:16 An entire portfolio has the ability to run core operations without requiring human intervention at all.
0:00:20 Housing and health care are the biggest expenses that people have.
0:00:25 It’s pretty self-evident that technology makes the experience better for everyone and brings down costs.
0:00:27 And more people should be working on it.
0:00:34 Elise AI is taking on two of the biggest and most expensive challenges we face, housing and health care.
0:00:41 Joining me today are my colleague Alex Immerman from our growth team, along with Elise AI’s co-founders Minna Song and Tony Stoyanov.
0:00:47 We explore why these industries have resisted technological change, how AI can cut costs and inefficiencies,
0:00:52 and the vision Minna and Tony are building toward, a future with more affordable, accessible services.
0:00:54 Let’s get into it.
0:01:00 We’re honored to announce our latest investment in Elise AI.
0:01:02 Minna, Tony, welcome to the podcast.
0:01:03 Welcome to the portfolio.
0:01:04 Thank you.
0:01:10 Why don’t you guys give us a brief background or give the audience a brief background on why Elise AI, why housing, why health care?
0:01:15 We wanted to use AI to solve real world problems.
0:01:20 And housing and health care are the biggest expenses that people have.
0:01:25 They eat up about 42% of what a typical household makes.
0:01:29 And nationally, these sectors make up about 40% of the entire GDP.
0:01:36 So it’s pretty obvious that we need to figure out how to cut waste in these industries.
0:01:42 It was pretty crazy to us that not enough people were working on these problems.
0:01:48 Top technology people, for example, are not asking the hard questions about how can we actually fix it.
0:01:51 It’s just sort of an accepted tax that we all pay.
0:01:57 So we started digging a lot deeper into how these systems operate.
0:02:02 And once you do that, you can see inefficiencies everywhere you look.
0:02:07 And those really add up to huge costs to all of us.
0:02:13 And it’s also not just about the money, but the quality of these services has a really big impact on people’s lives.
0:02:15 And when they fail, it doesn’t just hurt individuals.
0:02:18 It actually hurts kind of society as a whole.
0:02:21 So really fundamentally important problem for us to solve.
0:02:27 Alex, why don’t you give the perspective from the growth team in terms of there’s been a lot of players in this space over time.
0:02:30 What got you excited about this space and why this team?
0:02:36 Yeah, I mean, as you think about this space, a lot of it ties with what Mina just said, right?
0:02:46 So our partner, Mark, every year, like clockwork, he sends out this updated chart, and it shows consumer goods and services over time.
0:02:52 And if you look at housing and health care, as Mina just said, like prices just go up, up, up to the right.
0:02:57 And any industry that technology has touched has gone down.
0:03:02 So you can see that in computers, TVs, video games.
0:03:08 And we keep asking ourselves, like, why hasn’t software eaten this industry?
0:03:11 Why hasn’t software touched housing and health care?
0:03:22 And right now, it’s like such a paradigm shift with AI where the operational, administrative, and communication burden can really change.
0:03:31 And so you look at Mina and Tony, like two incredibly tenacious technical co-founders, and they were early to this problem.
0:03:38 They started in 2017, and they have gone deep, first in housing, and more recently in health care.
0:03:41 And the results just speak for themselves.
0:03:44 Customers absolutely are delighted with the product.
0:03:53 You see that qualitatively in the feedback we heard, but then quantitatively, the scale, the growth, the efficiency, and we’re thrilled to partner with them.
0:03:58 Mina, why don’t you go deeper in terms of what are the unlocks to actually improve housing affordability?
0:04:00 Why don’t you give some more context on the problem?
0:04:06 Well, for housing affordability, housing supply matters most of all.
0:04:09 That’s the single greatest determinant of housing prices.
0:04:13 So one, we know that we need to build way more units.
0:04:27 We’re about 5 million housing units short of what we actually need in the country, and we need to add somewhere between 1.8 to 2 million units per year just to kind of keep that shortage from getting worse, let alone making up for that deficit.
0:04:36 We’ve only developed about 1.5 million units last year, so we actually need to increase our delivery by about 50%.
0:04:41 And actually, analysts say that the pipeline is shrinking for 2026 and beyond.
0:04:46 So they said it’s going to drop by about 50%, so we’re headed in the completely wrong direction.
0:04:53 So housing supply matters, but in the short term, we can actually get more out of our current supply.
0:05:02 So I’ll give you an example, which is almost half of inquiries that go to a rental apartment building never get responded to.
0:05:04 So you’ve all experienced this, right?
0:05:05 We’ve all experienced that.
0:05:08 We want to look at an apartment, but we get ghosted.
0:05:09 No one responds to us.
0:05:15 And that apartment’s still sitting there available, and you want it, but it’s being underutilized just because the process is broken.
0:05:18 And so AI is managing all that demand.
0:05:21 We can actually turn vacant apartments into occupied way faster.
0:05:24 So we have data that proves that this works, actually.
0:05:34 Earlier this year, we provided data to an organization called ALN and found that buildings using our AI had 2% higher occupancy compared to market.
0:05:40 So we’re working on fixing the affordability problem and the supply problem from a bunch of different angles.
0:05:42 You mentioned we’re going in the wrong direction.
0:05:50 Can you share more about why that’s happening and what are the sort of biggest regulatory or technological bottlenecks that need to be addressed for that to change?
0:05:56 There’s a lot of regulation, a lot of zoning laws that cause parts of this problem.
0:06:02 But even relaxing regulation will not solve that problem by itself.
0:06:06 We also need more capital flowing into housing construction today.
0:06:09 And that’s a big thing that we think about internally at Elise AI.
0:06:13 Capital flows where there are the highest returns.
0:06:18 And right now, housing has lower returns relative to other asset classes.
0:06:28 But we’re actually enabling housing to achieve higher returns because we’re creating these 10x better housing operators that return higher profits to investors.
0:06:37 If housing is a stable and a higher return investment, how much more capital would be flowing to this most fundamental need for society?
0:06:43 So that’s really great for everyone because it drives more supply into the market and supply is really king to fixing the housing crisis.
0:06:48 On the regulatory side, do you think we’ll see full YIMBYism in our lifetime?
0:06:54 Or is your view of there’s some structural reason that impedes that in the U.S. relative to a country like Japan?
0:06:56 And we just got to work with what we’ve got?
0:06:58 I think we really hope so.
0:07:02 I think different cities actually have kind of started making real progress towards this.
0:07:04 Minneapolis is a great example.
0:07:06 They did a big housing reform.
0:07:10 Part of that was actually ending single-family zoning rules there.
0:07:13 And that happened back in 2019.
0:07:18 And I think ever since that, we’ve seen supply has grown three times faster than the national average.
0:07:26 And the rents have stayed actually flat for that whole period compared to everybody else experienced about 31% increase.
0:07:32 So I think we’re seeing some early signs there and hopefully other cities and states take that example.
0:07:42 And then even if we got sort of Tokyo-level zoning tomorrow, how fast could supply respond or is it really just this sort of capital balance that is preventing that?
0:07:48 I think the data is somewhat clear that obviously it will take a few years to see the full impact.
0:07:53 But I think if you let people build, they will go and build and the market will take care of itself.
0:07:57 And obviously there will be a lot more innovation as well as it gets much more competitive of a market.
0:08:02 Why don’t we go deeper into understanding what needs to be true for it to be a more attractive asset class?
0:08:08 Maybe you can sort of walk us through it, explain a little bit how it’s made up and what would need to be true to improve the rate of return there.
0:08:10 It’s very inefficient.
0:08:13 That’s the reality is that we’re dealing with the physical world.
0:08:19 And along the way, real estate has not invested a ton in technology.
0:08:25 So it hasn’t gotten a lot of the efficiencies that an internet company or SaaS company could achieve.
0:08:31 So there’s a bunch of headwinds working against this asset class.
0:08:33 One is labor.
0:08:35 Labor is super expensive.
0:08:38 It’s only getting worse, particularly after COVID.
0:08:46 There’s a bunch of other reasons like insurance premiums and just costs and supply chain disruptions after COVID as well.
0:08:51 But all in all, I think the biggest controllable expense that our customers look at is labor.
0:08:57 There’s not too much they can do always about, it’s not as low hanging fruit as insurance changes.
0:09:03 New York and San Francisco are two markets that have really struggled with housing supply.
0:09:10 Assuming we don’t get more housing supply in these two cities, what do you think can be done to increase the affordability?
0:09:18 Yeah, I mean, I think even if we don’t build more units, SF vacancy rate is at about three and a half percent today.
0:09:20 So there’s definitely room for more efficiency.
0:09:27 You can kind of increase that utilization by making units turn faster, by filling units faster.
0:09:29 For all of that, better technology can help.
0:09:31 You want to cut all the manual inefficiencies.
0:09:39 But there are also other ideas around like you can do smaller apartments, share amenities, more flexible layouts.
0:09:42 Better infrastructure in general also helps.
0:09:50 You know, if you connect Jersey better to New York, obviously that increases the supply in a way in the whole metro area and that increases affordability.
0:09:53 So I think all of these things can help a lot.
0:09:55 To a certain extent, those are band-aids.
0:09:57 We do need to build more units.
0:10:00 And that will be the main way to consistently drive that affordability.
0:10:05 But I would say there’s definitely more room for improvement, even at today’s supply.
0:10:13 Yeah, I mean, of course, we hope that more supply gets built and more red tape gets cut in San Francisco.
0:10:18 I know Eric and I are at least optimistic about Permit SF, led by Mayor Lurie.
0:10:29 But I guess, absent that software probably can be an important lever to resolving some of these issues, where do you see that tangibly impacting affordability?
0:10:33 I think technology can counter some of the cost inflation and headwinds.
0:10:37 But it’s also a sector that historically hasn’t invested much in tech compared to other industries.
0:10:47 So I think, number one, we have to execute really well to get these sort of non-tech adopting audiences to use what we build and accept it.
0:10:52 But if we do that well, the biggest controllable expense is labor.
0:11:00 So AI being used to automate and eliminate a lot of the manual and inefficient workflows can help a lot.
0:11:03 So we’re already seeing customers reduce some of these expenses.
0:11:11 And finding other savings as well, like cutting legal fees because your operations are already more compliant from the start.
0:11:18 Or reducing CapEx costs by optimizing preventative maintenance so things don’t break as much.
0:11:21 So all of these things add up.
0:11:25 And, you know, if someone’s absorbing those costs, and it’s you.
0:11:29 So yeah, we’re creating these sort of 10x operators that…
0:11:31 My landlord is not thanking me.
0:11:44 So we’ve seen, with many of your clients, them be able to centralize a lot of their staff, increase AI as a communication mechanism with their tenants.
0:11:47 And the impact has been dramatic.
0:11:54 I know with Equity Residential, one of your customers, they’ve gotten up to 200 units per employee.
0:12:03 Maybe just walk us through, like, how do you get from half of that, which I think is like baseline expectation, to twice as high?
0:12:06 And then, how do you think about the efficient frontier?
0:12:09 Like, where should that be in five years from now?
0:12:12 Our goal is to enable fully autonomous buildings.
0:12:20 So that means an entire portfolio has the ability to run core operations without requiring human intervention at all.
0:12:33 So when you look at what actually happens on-site at a building, you quickly realize how much of that day-to-day work is just administrative in nature and can be automated away.
0:12:39 So really, when you’re thinking about the physical limits, it’s just truly the physical work that’s left.
0:12:43 The maintenance or things that are maybe legally required.
0:12:49 So those are the parts that I think are a little bit harder and actually put kind of the thresholds on what’s possible today.
0:12:59 But I think going after full automation is a really hard technical challenge that no one has truly figured out yet.
0:13:06 So we really have to sort of reimagine our customers’ entire operating models to be able to develop products that support this.
0:13:10 So I think Equity Residential was a great example.
0:13:17 Really early on, had taken advantage of a ton of technology to get cost optimization and efficiencies.
0:13:20 Brookfield Properties is another one of our customers.
0:13:28 They’re building this centralized model that enables a single employee to service multiple properties.
0:13:36 And they’re actually finding that they can get a single employee to work across 10,000 units using AI in a specialized role.
0:13:37 And so think about that.
0:13:43 A one person managing what used to require dozens of people that were decentralized across multiple properties.
0:13:44 It’s a big difference.
0:13:47 But you need a huge amount of automation to be able to achieve those numbers.
0:13:51 Even the boundaries of what’s actually physical are changing fast.
0:13:55 I think something like door access wasn’t a thing 10 years ago.
0:14:00 And today we see more and more physical keys are being replaced by smart locks.
0:14:03 And now you connect your AI to that system.
0:14:05 You can do key provisioning online.
0:14:12 And I think we’ll see more sensors in the buildings, more decisions being driven, and more planning being done by the AI.
0:14:15 Of course, there’s still some physical boundaries.
0:14:16 The AI is not going to fix the sink.
0:14:20 But I think we can push that boundary quite a lot in the next few years.
0:14:25 Why don’t you talk through where we are today in terms of what’s been automated, what’s not yet automated,
0:14:27 and then we can get to what is the full vision.
0:14:29 And in that full vision, what do humans do?
0:14:32 A lot has been automated.
0:14:41 I mean, maintenance, you’d have physical boards covered in Post-it notes with people trying to keep track of what needs to be done.
0:14:51 Now that can be automated, triaged by AI, prioritized based on urgency of those issues, routed to the right technician, tracked everything automatically.
0:15:00 And we see that some operators with these workflows have cut average work order completion times from four to five days down to under 48 hours.
0:15:01 So that’s really meaningful for residents.
0:15:04 Leasing was maybe one of the worst.
0:15:14 It was people just spending entire days answering emails, the same 50 questions over and over and over all day long,
0:15:16 and just the same basic information.
0:15:22 And now AI can obviously handle that and complete those tasks with all the knowledge of a building or all the knowledge of a portfolio.
0:15:24 Touring was another area of automation.
0:15:33 So you’d have to go meet a broker or go meet a leasing agent and be physically escorted to every single showing.
0:15:40 But now AI can give you access or you can get access through, you know, smart hardware, smart locks, lock boxes.
0:15:45 And the AI can still be there to engage and answer all those questions and do the selling.
0:15:53 So that gives you a ton of benefits and efficiencies where you’re not just having, you’re paying a whole human just to unlock a single door.
0:16:02 And actually cuts down average time for our customers from about 30 days from listing an apartment to leasing it to under 14 days,
0:16:08 because it gives you so much more flexibility to tour around the clock.
0:16:10 Documentation was a big area of automation too.
0:16:14 Lots of people just copying and pasting fields.
0:16:22 Just an industry that was super ripe for technology that just didn’t get it for a very long time.
0:16:27 Yeah, and I think this is only even the first order automation we can do.
0:16:35 I think there’s a whole second order, because all Mino is talking about today is like on that single community level, single building.
0:16:40 There’s this whole question about like, how do you kind of organize the entire ecosystem?
0:16:42 How can you share resources?
0:16:51 Whether it’s people, parts, tools, between many buildings, obviously that increases the complexity.
0:17:00 But for something like maintenance, we expect to see a lot more dramatic gains once you go on the ecosystem level.
0:17:09 And how about the second part of the question in terms of, okay, your vision comes true in terms of fully autonomous or fully automated housing.
0:17:14 Right now there’s a lot of people doing a lot of those activities, or some of them.
0:17:15 What do they go do?
0:17:23 I think as AI takes over a lot of the communication and logistics, human roles don’t all disappear.
0:17:27 They just, these sort of AI-enabled career paths start to emerge.
0:17:29 And I think you’re seeing this in other industries as well.
0:17:31 I think expectations are higher.
0:17:45 People, like you mentioned earlier, expect that renting an apartment is super easy, super frictionless, and it doesn’t require extensive human contact for basic stuff.
0:17:48 And that’s a great opportunity for AI.
0:17:54 So I think you’ll see that these career paths are, in the short term, menial parts of the job go away.
0:18:00 And people are spending time focusing on building relationships with residents, creating communities.
0:18:02 I think people are spending more time at home, right?
0:18:04 They’re working at home.
0:18:05 Their home is their office.
0:18:09 Like, you still need this human connection.
0:18:18 And a lot of our customers, we see that, are creating roles like community engagement and helping people socialize.
0:18:21 I think people will specialize tracks.
0:18:30 So you might become, instead of this sort of generalist on site doing everything menial and complex, you’ll actually see a lot more specialization.
0:18:40 And you might become a renewal specialist who handles the trickiest retention cases or a resident experience specialist that resolves conflicts.
0:18:54 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.
0:19:02 Yeah, and I’ll add up to that, that on the maintenance side, obviously, I think that physical aspect is never going to fully go away.
0:19:12 I think it’ll be a lot more efficient, which I think is really, really needed because there’s just huge shortages from labor perspective.
0:19:16 And a lot of the maintenance technicians today are actually over 50 years old.
0:19:23 So you can see that in the next few years, it’s only going to get worse and worse if there are no more efficiency gains.
0:19:26 Going back to just the future of housing for a second.
0:19:30 So let’s say, you know, 10 years from now, we have robotics.
0:19:34 You know, we’ve made some major advances in longevity research.
0:19:36 We have AGI.
0:19:42 But when you paint, what’s sort of the experience going to look like?
0:19:50 Or how are those impacts, the ones that I mentioned, at least robotics and longevity, going to impact the market and asset class?
0:19:53 I think the population is going to change a lot with AI.
0:20:02 Why I kind of talk about longevity is, I think a lot of AI research is and should be going to extending human life.
0:20:08 But if, obviously, if you’re living longer, there are more people around, staying around longer.
0:20:12 And, you know, we talk about cost of living a lot.
0:20:19 Cost of living is actually one of the, it is the number one reason that people don’t have more children.
0:20:34 But if AI creates a lot more wealth in the world and it brings, and, you know, it does things like bring the cost of living because of the efficiencies similar to what we work on in housing and healthcare, people have more kids.
0:20:36 Again, you have more population.
0:20:44 So, all these things, I think, will really affect, will really affect the housing market because all those people, this is a fundamental need for all those people.
0:20:48 So, yeah, we have to find efficiencies.
0:20:53 Kind of, as I mentioned before, it is more housing supply.
0:21:00 And that’s where sort of robotics can come in and play a huge role, which is, can we use robots, you know, manufacturing?
0:21:03 Can we do, you know, modular housing?
0:21:07 Can we build faster with robots?
0:21:09 Can we bring down the cost of construction?
0:21:15 And I actually think this is an incredibly, that’s like, that’s one area that we’ve never touched.
0:21:19 We’re not, we’re not a hardware company yet.
0:21:26 But it is sort of this big kind of piece of the puzzle in the long-term vision that really needs to be solved by somebody.
0:21:31 And I think you also want to leverage the technology to increase mobility in general.
0:21:36 I think today people are stuck in these 12-month, 24-month leases.
0:21:42 I think you want to, in the future, you want to have, like, flexibility to just move in tomorrow and that to be very cheap.
0:21:48 And you can have, like, much, much greater degree of flexibility.
0:21:53 Yeah, I think mobility in the market is incredibly important and productive for society.
0:22:02 So if you think about it, we are signing these 12-month leases and locked into these contracts as consumers.
0:22:05 And that’s a big commitment.
0:22:06 A lot of people don’t want to sign these leases.
0:22:11 But it’s really laborious to turn over every apartment, not just, you know, the maintenance turnover,
0:22:17 but finding somebody, answering all these, you know, the same 50 questions over and over again, touring.
0:22:22 It’s just, there’s so much labor that it makes it really difficult for an operator,
0:22:28 like a housing operator to find a new resident or a new tenant.
0:22:31 AI doesn’t really care if it’s signing shorter-term leases.
0:22:34 It’s just doing, you know, it’s doing that over and over and it scales.
0:22:41 Then you kind of get the benefit for that, both for the landlord and for the consumer,
0:22:46 that they can be more, they can do it at a cheaper cost and people can be more mobile.
0:22:48 I think that opens up a ton of opportunity.
0:22:52 That’s, you know, people can move for jobs easier.
0:22:55 People can move for their children’s schools.
0:22:58 They can increase, improve their quality of life.
0:23:01 So I think there’s a bunch of different benefits of mobility.
0:23:06 We’ve been talking about technology as a lever here and the need for it in real estate,
0:23:10 and yet real estate spends the least on R&D of any other industry.
0:23:12 Why is that and what could be done about it?
0:23:17 I think solving housing operations is incredibly hard.
0:23:19 The search space is massive.
0:23:22 There’s just a ton of different edge cases.
0:23:23 We face this every day.
0:23:25 Every single building is different.
0:23:29 And it’s a really large expense for people.
0:23:36 So it makes all these things make these interactions with an apartment, like leasing.
0:23:40 It makes these interactions really complex.
0:23:49 So in the past, you’ve really just needed a person because traditional software couldn’t handle the variability that was required.
0:23:54 So if you needed a person anyway, there wasn’t really a motivation to buy technology.
0:23:57 You just leaned on that person.
0:23:59 You leaned on people to do absolutely everything.
0:24:02 Of course, those people got really overburdened.
0:24:07 But also in the meantime, a lot of that critical data was never collected because it just lived in people’s heads.
0:24:12 So now AI has changed what’s feasible.
0:24:15 And it can handle these really large search spaces.
0:24:18 It can handle these really complex operations.
0:24:24 So, I mean, in addition, real estate is so far behind on tech.
0:24:27 It actually has the most to benefit from AI.
0:24:33 So it maybe is going from the lowest R&D spending to potentially one of the highest spenders on AI.
0:24:41 Because AI has sort of finally unlocked automation that was possible that really they couldn’t take advantage or they couldn’t optimize it before.
0:24:54 How do you respond to critics of PropTech who just say, you know, PropTech is here to help residential real estate companies extract more value from their tenants?
0:24:56 That’s honestly a pretty silly argument.
0:24:58 I get it.
0:25:01 I think housing is really an emotionally charged subject.
0:25:10 People apply these irrational expectations to landlords that they never apply to other types of business owners.
0:25:12 So think about other industries.
0:25:22 Like, you wouldn’t want airlines to stick to paper ticketing processes so that they extract more value, so that they don’t extract more value from tech efficiencies.
0:25:26 Or you wouldn’t, you know, if a supermarket didn’t use scanners or barcodes.
0:25:33 It’s pretty self-evident that technology makes the experience better for everyone and brings down costs.
0:25:37 So we actually want landlords to use as much technology as possible.
0:25:43 Because, you know, when they’re slow to innovate, that’s really actually bad for consumers.
0:25:48 Yeah, and we think that the barriers to entry are already quite high.
0:25:50 The operations are very complex.
0:25:53 Everything you have to do is multimodal.
0:25:54 So much stuff is manual.
0:26:00 So I think that limits the amount of people that can get into that business in the first place.
0:26:05 And I think that actually gives a lot more pricing power to the existing landlords.
0:26:11 So you can kind of make the argument that actually, like, all of this inefficiency is really bad for the consumer.
0:26:17 And I think at the end of the day, we believe that competitive markets, you know, take care of themselves.
0:26:24 And I cannot think of a single example where, you know, technology was banned and then costs went down.
0:26:26 I think that just never happens.
0:26:29 Yeah, it’s exactly the opposite, right?
0:26:34 So generally, when technology is introduced, you see a surplus.
0:26:37 And most of that typically goes back to the consumer.
0:26:44 The criticism of PropTech would be, is it all going to the property managers and the owner-operators?
0:26:50 And, you know, hopefully, as more and more AI is adopted, it’s going to address this affordability crisis.
0:26:52 Yeah, you need mass adoption.
0:26:56 That’s where the competitive markets take care of themselves.
0:27:00 So there’s rising repairs, maintenance costs.
0:27:03 These keep vacancies longer.
0:27:06 You know, apartments aren’t occupied.
0:27:09 This leads to higher housing costs as well.
0:27:12 What is a lease doing to address this?
0:27:13 What can be done over the next five years?
0:27:19 Yeah, I mean, obviously, there’s a very physical component that needs to be taken care of.
0:27:23 But actually, where we think AI and technology more broadly can help,
0:27:26 all of these problems are actually very complex.
0:27:31 planning problems that are quite difficult to solve with the current level of technology.
0:27:36 There’s so much computation that you need to do around, like,
0:27:39 how do you get smarter at scheduling technicians?
0:27:40 How do you get smarter at routing?
0:27:48 How do you kind of embed a lot of these common sense things that everybody on the ground knows?
0:27:54 You know, if you’re fixing a dishwasher, at the same time, somebody can go and fix the holes on the wall.
0:27:58 But if you actually want to paint the wall, first you need to fix the holes.
0:27:59 You cannot just paint over the holes.
0:28:06 So kind of like there’s a lot of technology there that we believe we can build that will make all of these planning,
0:28:11 purchasing, purchasing, scheduling, orchestration decisions so much more efficient.
0:28:20 And we’re not even touching, like, what we think can be another big needle around that preventative aspect of, like,
0:28:23 how do you track what’s going on in a property?
0:28:31 How do you know when appliances come near their end of life and replace them in smart and cheap ways?
0:28:36 And we feel like all of these problems can have a really, really big impact.
0:28:46 Because today we see our clients waste days and days without, because, like, some piece of information got lost.
0:28:55 Yeah, every day you shave off from the average unit turn time nationwide unlocks billions of dollars in value.
0:28:58 So there’s a ton of value just by moving the needle a little bit.
0:29:02 The cause of those delays is completely avoidable stuff.
0:29:07 So, like, this part wasn’t delivered, or the data wasn’t input into the system,
0:29:09 so the next person wasn’t scheduled for that job.
0:29:12 And it’s totally addressable through automation.
0:29:15 And those are the problems that I think are really exciting.
0:29:25 So when I met Mina in 2021, she and Tony were building a relatively narrow tool for leasing.
0:29:29 We were catching up a bit over a year ago in 2024.
0:29:35 Leasing had gone to broader residential ops, so maintenance that we’ve talked a lot about,
0:29:37 billing, delinquencies, et cetera.
0:29:42 And then she dropped, we’re launching in healthcare.
0:29:43 We launched in healthcare.
0:29:47 And I thought to myself, like, you know, Mina, Tony, that’s insane.
0:29:51 What do those two industries have in common?
0:29:56 And I kind of just dismissed it, kept it in the back of my head.
0:30:01 And then, you know, catching up a couple months ago, and the healthcare business is humming.
0:30:06 Maybe share what is similar in the workflows?
0:30:07 What is different?
0:30:09 What’s been most exciting there?
0:30:11 Yeah.
0:30:16 We’ve been mostly, like, I agree with you, like, those two fields look very different.
0:30:20 But we’ve been mostly touching the admin piece of the healthcare.
0:30:23 And we found, like, those problem sets are quite similar.
0:30:30 You kind of see, like, these very bloated cost structures that, you know, have so many inefficiencies.
0:30:32 They’re all struggling with staffing.
0:30:36 All of these total costs, you know, gets pushed to the end consumer.
0:30:49 And we think a lot of the causes of that is, like, the very similar dynamics we see between these complex digital physical interactions that are full with regulations.
0:30:55 And we believe AI can help quite a lot, both of them.
0:31:00 We see, like, so much commonality around how they approach things like intake.
0:31:06 You have to collect very structured information around names, preferences, budgets, insurances.
0:31:11 And you keep dealing with this really high volume of repetitive inquiries.
0:31:14 You get the same questions again and again and again.
0:31:20 And it’s all done over the phone, over conversations.
0:31:27 We’ve been able to adopt quite a lot of our technology pretty seamlessly.
0:31:32 We developed our voice technology over the housing space.
0:31:35 And that has translated really, really well in the healthcare space.
0:31:41 And the same thing with a lot of the scheduling optimizations we’ve been doing have translated quite, quite well.
0:31:44 So, they kind of feel very, very different.
0:31:53 But from admin organizational operations perspective, we’ve barely been surprised by anything by transitioning to healthcare.
0:31:58 We spent a bunch of time earlier talking about why housing costs are so high.
0:32:05 It seems like no matter what, healthcare costs remain at a sixth or a fifth of the economy.
0:32:10 Is it that we’re just getting a better product for that cost?
0:32:13 Because is healthcare good that we just keep wanting more of it?
0:32:17 And so, no matter what, we get something better and we’re just going to keep spending?
0:32:19 Is it an elastic in that way?
0:32:28 Or is it that some morass of regulatory challenges prevents technology from really bending that price curve?
0:32:29 What’s happening there?
0:32:31 Why are costs staying the same?
0:32:35 I think it’s both are actually true.
0:32:42 I think healthcare is definitely a very elastic need where people are getting better healthcare, people are getting more healthcare.
0:32:46 I think if costs go down, people would want even more healthcare.
0:32:49 So, I definitely, and that’s a good thing, right?
0:32:52 I think that makes people live longer, happier lives.
0:32:54 And I think that’s super important.
0:32:55 And that’s all true.
0:33:00 But I would say, like, on the admin side, I don’t think we’re getting a better admin experience.
0:33:07 And I think the costs on the admin side have really skyrocketed way faster than anything on the clinical side.
0:33:19 And I think partially people have invested in technology, but it just hasn’t been quite good enough, again, because so much is happening over the phone in these unstructured interactions.
0:33:26 But we think with the current level of technology, you can actually make a really big dent into the admin aspect.
0:33:40 I don’t think in healthcare, there’s been this huge boom of technology adoption that has, we’re surprised we haven’t been, it hasn’t flowed to consumers’ pockets yet.
0:33:47 I think we’re, we’ll see that with AI, but I don’t think the cycle has given its feedback yet.
0:33:49 So I am still hopeful.
0:33:58 But yeah, it can, I think it can arise in either lower costs or better, better outcomes or a combination of both of those things.
0:34:05 In housing, you guys have really gone from leasing to broader resident ops.
0:34:09 You’ve started with scheduling on the healthcare side.
0:34:12 Where do you think the platform goes from here?
0:34:16 We think for us, healthcare is much earlier.
0:34:28 We think there’s so much more that’s happening on the admin backend side of things that we feel like there’s so much inefficiencies that needs to be addressed.
0:34:33 And I think that’s going to take a bit to actually cover all of that ground.
0:34:43 But I think anything from, you know, that first interaction to the billing cycle and more importantly towards like,
0:34:48 how do you kind of keep the communication post appointment with the patient?
0:34:52 Because I think today, you know, you go in and spend 10 minutes with the doctor.
0:34:54 They’re definitely very helpful.
0:34:58 But then you get a piece of paper and it’s like, good luck from there onwards.
0:35:05 I think AI can help quite a lot with engagement on the patient side.
0:35:08 And I think there’s a lot to be done there.
0:35:13 Yeah, you go home from your appointment, you have like four things that you’re supposed to do every night for the next week.
0:35:15 And what is adherence to that?
0:35:16 Pretty low.
0:35:20 But if you got, you know, an Elise message every night, you’d probably do a better job.
0:35:29 Yeah, I think AI plays a great role in education and leaving the outcome on the patient.
0:35:39 If AI can scale and achieve better treatment planned, you know, fulfillment, that’s going to be better for everybody.
0:35:42 It’s certainly going to save us a lot of costs.
0:35:44 You know, it’s one of the government’s largest expenses.
0:35:49 And so we’re all paying for that, those outcomes being poor as well.
0:35:52 Yeah, and this adherence is not easy at all.
0:35:55 Because like, again, patients are very stressed when they go to a doctor.
0:35:58 It’s not an easy thing to do.
0:36:04 And I think AI can help them, give them more time after the appointment to ask questions.
0:36:08 Obviously, there’s things like language barriers that AI can help quite a lot with.
0:36:11 So I think there’s all these benefits that we’ll be able to.
0:36:16 Yeah, and involve family members who probably weren’t able to attend the appointment or the procedure.
0:36:23 Yeah, you have to think about all your questions, right, in the moment when you have that time with the doctor.
0:36:26 And then if you think of something, you’re SOL.
0:36:28 If you think of something too late.
0:36:32 In this episode, we’ve been talking about housing, we’ve been talking about healthcare.
0:36:36 These are two extremely complex markets.
0:36:42 I’m curious if you can go back in time, you know, knowing what you know now, what might have you done differently?
0:36:45 I probably would have started with affordable housing, actually.
0:36:52 Affordable housing has kind of every problem that the rest of the industry has.
0:36:59 Plus maximal complexity because of all the dense compliance and paperwork, all the additional requirements.
0:37:02 And they are the most underserved.
0:37:09 They have the biggest administrative drag, and they are also some of the slowest adopters.
0:37:15 So it just shows that there’s this huge, clear opportunity for them to take advantage of AI.
0:37:18 And it just takes longer to get there.
0:37:22 So that’s, I think, one big thing I would change.
0:37:27 We’re actually kind of approaching healthcare in a similar way, which is start with what is the most underserved?
0:37:29 Because that’s where we can have the largest impact.
0:37:37 The most underserved and the most complex, because if you sort of solve those problems, then the rest of it is sort of easier downstream.
0:37:41 Perhaps let’s close on the ultimate vision for Elyse AI.
0:37:51 If you achieve everything you’re setting out to do, and obviously you’ve achieved a ton to date, what more can you say about what that looks like at scale?
0:37:55 I think our drive always has been cost reduction.
0:38:08 If at some point, and obviously it’s not just one company’s effort, but if at some point we get to a place where housing and healthcare are not cost concerns for the average person, I think that would be amazing.
0:38:26 Yeah, I think if we can take this 42% of what a household spends on housing and healthcare and bring that down to 20-something percent, that is, I think, one of the most important problems we can solve.
0:38:28 And more people should be working on it.
0:38:30 That’s a great note to wrap.
0:38:33 Min and Tony, thanks so much for coming on the podcast and being part of the portfolio.
0:38:38 Thanks for listening to the A16Z podcast.
0:38:44 If you enjoyed the episode, let us know by leaving a review at ratethispodcast.com slash A16Z.
0:38:46 We’ve got more great conversations coming your way.
0:38:48 See you next time.
0:38:52 As a reminder, the content here is for informational purposes only.
0:38:58 It should not be taken as legal, business, tax, or investment advice, or be used to evaluate any investment or security,
0:39:02 and is not directed at any investors or potential investors in any A16Z fund.
0:39:07 Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast.
0:39:15 For more details, including a link to our investments, please see A16Z.com forward slash disclosures.
0:00:08 Our goal is to enable fully autonomous buildings.
0:00:16 An entire portfolio has the ability to run core operations without requiring human intervention at all.
0:00:20 Housing and health care are the biggest expenses that people have.
0:00:25 It’s pretty self-evident that technology makes the experience better for everyone and brings down costs.
0:00:27 And more people should be working on it.
0:00:34 Elise AI is taking on two of the biggest and most expensive challenges we face, housing and health care.
0:00:41 Joining me today are my colleague Alex Immerman from our growth team, along with Elise AI’s co-founders Minna Song and Tony Stoyanov.
0:00:47 We explore why these industries have resisted technological change, how AI can cut costs and inefficiencies,
0:00:52 and the vision Minna and Tony are building toward, a future with more affordable, accessible services.
0:00:54 Let’s get into it.
0:01:00 We’re honored to announce our latest investment in Elise AI.
0:01:02 Minna, Tony, welcome to the podcast.
0:01:03 Welcome to the portfolio.
0:01:04 Thank you.
0:01:10 Why don’t you guys give us a brief background or give the audience a brief background on why Elise AI, why housing, why health care?
0:01:15 We wanted to use AI to solve real world problems.
0:01:20 And housing and health care are the biggest expenses that people have.
0:01:25 They eat up about 42% of what a typical household makes.
0:01:29 And nationally, these sectors make up about 40% of the entire GDP.
0:01:36 So it’s pretty obvious that we need to figure out how to cut waste in these industries.
0:01:42 It was pretty crazy to us that not enough people were working on these problems.
0:01:48 Top technology people, for example, are not asking the hard questions about how can we actually fix it.
0:01:51 It’s just sort of an accepted tax that we all pay.
0:01:57 So we started digging a lot deeper into how these systems operate.
0:02:02 And once you do that, you can see inefficiencies everywhere you look.
0:02:07 And those really add up to huge costs to all of us.
0:02:13 And it’s also not just about the money, but the quality of these services has a really big impact on people’s lives.
0:02:15 And when they fail, it doesn’t just hurt individuals.
0:02:18 It actually hurts kind of society as a whole.
0:02:21 So really fundamentally important problem for us to solve.
0:02:27 Alex, why don’t you give the perspective from the growth team in terms of there’s been a lot of players in this space over time.
0:02:30 What got you excited about this space and why this team?
0:02:36 Yeah, I mean, as you think about this space, a lot of it ties with what Mina just said, right?
0:02:46 So our partner, Mark, every year, like clockwork, he sends out this updated chart, and it shows consumer goods and services over time.
0:02:52 And if you look at housing and health care, as Mina just said, like prices just go up, up, up to the right.
0:02:57 And any industry that technology has touched has gone down.
0:03:02 So you can see that in computers, TVs, video games.
0:03:08 And we keep asking ourselves, like, why hasn’t software eaten this industry?
0:03:11 Why hasn’t software touched housing and health care?
0:03:22 And right now, it’s like such a paradigm shift with AI where the operational, administrative, and communication burden can really change.
0:03:31 And so you look at Mina and Tony, like two incredibly tenacious technical co-founders, and they were early to this problem.
0:03:38 They started in 2017, and they have gone deep, first in housing, and more recently in health care.
0:03:41 And the results just speak for themselves.
0:03:44 Customers absolutely are delighted with the product.
0:03:53 You see that qualitatively in the feedback we heard, but then quantitatively, the scale, the growth, the efficiency, and we’re thrilled to partner with them.
0:03:58 Mina, why don’t you go deeper in terms of what are the unlocks to actually improve housing affordability?
0:04:00 Why don’t you give some more context on the problem?
0:04:06 Well, for housing affordability, housing supply matters most of all.
0:04:09 That’s the single greatest determinant of housing prices.
0:04:13 So one, we know that we need to build way more units.
0:04:27 We’re about 5 million housing units short of what we actually need in the country, and we need to add somewhere between 1.8 to 2 million units per year just to kind of keep that shortage from getting worse, let alone making up for that deficit.
0:04:36 We’ve only developed about 1.5 million units last year, so we actually need to increase our delivery by about 50%.
0:04:41 And actually, analysts say that the pipeline is shrinking for 2026 and beyond.
0:04:46 So they said it’s going to drop by about 50%, so we’re headed in the completely wrong direction.
0:04:53 So housing supply matters, but in the short term, we can actually get more out of our current supply.
0:05:02 So I’ll give you an example, which is almost half of inquiries that go to a rental apartment building never get responded to.
0:05:04 So you’ve all experienced this, right?
0:05:05 We’ve all experienced that.
0:05:08 We want to look at an apartment, but we get ghosted.
0:05:09 No one responds to us.
0:05:15 And that apartment’s still sitting there available, and you want it, but it’s being underutilized just because the process is broken.
0:05:18 And so AI is managing all that demand.
0:05:21 We can actually turn vacant apartments into occupied way faster.
0:05:24 So we have data that proves that this works, actually.
0:05:34 Earlier this year, we provided data to an organization called ALN and found that buildings using our AI had 2% higher occupancy compared to market.
0:05:40 So we’re working on fixing the affordability problem and the supply problem from a bunch of different angles.
0:05:42 You mentioned we’re going in the wrong direction.
0:05:50 Can you share more about why that’s happening and what are the sort of biggest regulatory or technological bottlenecks that need to be addressed for that to change?
0:05:56 There’s a lot of regulation, a lot of zoning laws that cause parts of this problem.
0:06:02 But even relaxing regulation will not solve that problem by itself.
0:06:06 We also need more capital flowing into housing construction today.
0:06:09 And that’s a big thing that we think about internally at Elise AI.
0:06:13 Capital flows where there are the highest returns.
0:06:18 And right now, housing has lower returns relative to other asset classes.
0:06:28 But we’re actually enabling housing to achieve higher returns because we’re creating these 10x better housing operators that return higher profits to investors.
0:06:37 If housing is a stable and a higher return investment, how much more capital would be flowing to this most fundamental need for society?
0:06:43 So that’s really great for everyone because it drives more supply into the market and supply is really king to fixing the housing crisis.
0:06:48 On the regulatory side, do you think we’ll see full YIMBYism in our lifetime?
0:06:54 Or is your view of there’s some structural reason that impedes that in the U.S. relative to a country like Japan?
0:06:56 And we just got to work with what we’ve got?
0:06:58 I think we really hope so.
0:07:02 I think different cities actually have kind of started making real progress towards this.
0:07:04 Minneapolis is a great example.
0:07:06 They did a big housing reform.
0:07:10 Part of that was actually ending single-family zoning rules there.
0:07:13 And that happened back in 2019.
0:07:18 And I think ever since that, we’ve seen supply has grown three times faster than the national average.
0:07:26 And the rents have stayed actually flat for that whole period compared to everybody else experienced about 31% increase.
0:07:32 So I think we’re seeing some early signs there and hopefully other cities and states take that example.
0:07:42 And then even if we got sort of Tokyo-level zoning tomorrow, how fast could supply respond or is it really just this sort of capital balance that is preventing that?
0:07:48 I think the data is somewhat clear that obviously it will take a few years to see the full impact.
0:07:53 But I think if you let people build, they will go and build and the market will take care of itself.
0:07:57 And obviously there will be a lot more innovation as well as it gets much more competitive of a market.
0:08:02 Why don’t we go deeper into understanding what needs to be true for it to be a more attractive asset class?
0:08:08 Maybe you can sort of walk us through it, explain a little bit how it’s made up and what would need to be true to improve the rate of return there.
0:08:10 It’s very inefficient.
0:08:13 That’s the reality is that we’re dealing with the physical world.
0:08:19 And along the way, real estate has not invested a ton in technology.
0:08:25 So it hasn’t gotten a lot of the efficiencies that an internet company or SaaS company could achieve.
0:08:31 So there’s a bunch of headwinds working against this asset class.
0:08:33 One is labor.
0:08:35 Labor is super expensive.
0:08:38 It’s only getting worse, particularly after COVID.
0:08:46 There’s a bunch of other reasons like insurance premiums and just costs and supply chain disruptions after COVID as well.
0:08:51 But all in all, I think the biggest controllable expense that our customers look at is labor.
0:08:57 There’s not too much they can do always about, it’s not as low hanging fruit as insurance changes.
0:09:03 New York and San Francisco are two markets that have really struggled with housing supply.
0:09:10 Assuming we don’t get more housing supply in these two cities, what do you think can be done to increase the affordability?
0:09:18 Yeah, I mean, I think even if we don’t build more units, SF vacancy rate is at about three and a half percent today.
0:09:20 So there’s definitely room for more efficiency.
0:09:27 You can kind of increase that utilization by making units turn faster, by filling units faster.
0:09:29 For all of that, better technology can help.
0:09:31 You want to cut all the manual inefficiencies.
0:09:39 But there are also other ideas around like you can do smaller apartments, share amenities, more flexible layouts.
0:09:42 Better infrastructure in general also helps.
0:09:50 You know, if you connect Jersey better to New York, obviously that increases the supply in a way in the whole metro area and that increases affordability.
0:09:53 So I think all of these things can help a lot.
0:09:55 To a certain extent, those are band-aids.
0:09:57 We do need to build more units.
0:10:00 And that will be the main way to consistently drive that affordability.
0:10:05 But I would say there’s definitely more room for improvement, even at today’s supply.
0:10:13 Yeah, I mean, of course, we hope that more supply gets built and more red tape gets cut in San Francisco.
0:10:18 I know Eric and I are at least optimistic about Permit SF, led by Mayor Lurie.
0:10:29 But I guess, absent that software probably can be an important lever to resolving some of these issues, where do you see that tangibly impacting affordability?
0:10:33 I think technology can counter some of the cost inflation and headwinds.
0:10:37 But it’s also a sector that historically hasn’t invested much in tech compared to other industries.
0:10:47 So I think, number one, we have to execute really well to get these sort of non-tech adopting audiences to use what we build and accept it.
0:10:52 But if we do that well, the biggest controllable expense is labor.
0:11:00 So AI being used to automate and eliminate a lot of the manual and inefficient workflows can help a lot.
0:11:03 So we’re already seeing customers reduce some of these expenses.
0:11:11 And finding other savings as well, like cutting legal fees because your operations are already more compliant from the start.
0:11:18 Or reducing CapEx costs by optimizing preventative maintenance so things don’t break as much.
0:11:21 So all of these things add up.
0:11:25 And, you know, if someone’s absorbing those costs, and it’s you.
0:11:29 So yeah, we’re creating these sort of 10x operators that…
0:11:31 My landlord is not thanking me.
0:11:44 So we’ve seen, with many of your clients, them be able to centralize a lot of their staff, increase AI as a communication mechanism with their tenants.
0:11:47 And the impact has been dramatic.
0:11:54 I know with Equity Residential, one of your customers, they’ve gotten up to 200 units per employee.
0:12:03 Maybe just walk us through, like, how do you get from half of that, which I think is like baseline expectation, to twice as high?
0:12:06 And then, how do you think about the efficient frontier?
0:12:09 Like, where should that be in five years from now?
0:12:12 Our goal is to enable fully autonomous buildings.
0:12:20 So that means an entire portfolio has the ability to run core operations without requiring human intervention at all.
0:12:33 So when you look at what actually happens on-site at a building, you quickly realize how much of that day-to-day work is just administrative in nature and can be automated away.
0:12:39 So really, when you’re thinking about the physical limits, it’s just truly the physical work that’s left.
0:12:43 The maintenance or things that are maybe legally required.
0:12:49 So those are the parts that I think are a little bit harder and actually put kind of the thresholds on what’s possible today.
0:12:59 But I think going after full automation is a really hard technical challenge that no one has truly figured out yet.
0:13:06 So we really have to sort of reimagine our customers’ entire operating models to be able to develop products that support this.
0:13:10 So I think Equity Residential was a great example.
0:13:17 Really early on, had taken advantage of a ton of technology to get cost optimization and efficiencies.
0:13:20 Brookfield Properties is another one of our customers.
0:13:28 They’re building this centralized model that enables a single employee to service multiple properties.
0:13:36 And they’re actually finding that they can get a single employee to work across 10,000 units using AI in a specialized role.
0:13:37 And so think about that.
0:13:43 A one person managing what used to require dozens of people that were decentralized across multiple properties.
0:13:44 It’s a big difference.
0:13:47 But you need a huge amount of automation to be able to achieve those numbers.
0:13:51 Even the boundaries of what’s actually physical are changing fast.
0:13:55 I think something like door access wasn’t a thing 10 years ago.
0:14:00 And today we see more and more physical keys are being replaced by smart locks.
0:14:03 And now you connect your AI to that system.
0:14:05 You can do key provisioning online.
0:14:12 And I think we’ll see more sensors in the buildings, more decisions being driven, and more planning being done by the AI.
0:14:15 Of course, there’s still some physical boundaries.
0:14:16 The AI is not going to fix the sink.
0:14:20 But I think we can push that boundary quite a lot in the next few years.
0:14:25 Why don’t you talk through where we are today in terms of what’s been automated, what’s not yet automated,
0:14:27 and then we can get to what is the full vision.
0:14:29 And in that full vision, what do humans do?
0:14:32 A lot has been automated.
0:14:41 I mean, maintenance, you’d have physical boards covered in Post-it notes with people trying to keep track of what needs to be done.
0:14:51 Now that can be automated, triaged by AI, prioritized based on urgency of those issues, routed to the right technician, tracked everything automatically.
0:15:00 And we see that some operators with these workflows have cut average work order completion times from four to five days down to under 48 hours.
0:15:01 So that’s really meaningful for residents.
0:15:04 Leasing was maybe one of the worst.
0:15:14 It was people just spending entire days answering emails, the same 50 questions over and over and over all day long,
0:15:16 and just the same basic information.
0:15:22 And now AI can obviously handle that and complete those tasks with all the knowledge of a building or all the knowledge of a portfolio.
0:15:24 Touring was another area of automation.
0:15:33 So you’d have to go meet a broker or go meet a leasing agent and be physically escorted to every single showing.
0:15:40 But now AI can give you access or you can get access through, you know, smart hardware, smart locks, lock boxes.
0:15:45 And the AI can still be there to engage and answer all those questions and do the selling.
0:15:53 So that gives you a ton of benefits and efficiencies where you’re not just having, you’re paying a whole human just to unlock a single door.
0:16:02 And actually cuts down average time for our customers from about 30 days from listing an apartment to leasing it to under 14 days,
0:16:08 because it gives you so much more flexibility to tour around the clock.
0:16:10 Documentation was a big area of automation too.
0:16:14 Lots of people just copying and pasting fields.
0:16:22 Just an industry that was super ripe for technology that just didn’t get it for a very long time.
0:16:27 Yeah, and I think this is only even the first order automation we can do.
0:16:35 I think there’s a whole second order, because all Mino is talking about today is like on that single community level, single building.
0:16:40 There’s this whole question about like, how do you kind of organize the entire ecosystem?
0:16:42 How can you share resources?
0:16:51 Whether it’s people, parts, tools, between many buildings, obviously that increases the complexity.
0:17:00 But for something like maintenance, we expect to see a lot more dramatic gains once you go on the ecosystem level.
0:17:09 And how about the second part of the question in terms of, okay, your vision comes true in terms of fully autonomous or fully automated housing.
0:17:14 Right now there’s a lot of people doing a lot of those activities, or some of them.
0:17:15 What do they go do?
0:17:23 I think as AI takes over a lot of the communication and logistics, human roles don’t all disappear.
0:17:27 They just, these sort of AI-enabled career paths start to emerge.
0:17:29 And I think you’re seeing this in other industries as well.
0:17:31 I think expectations are higher.
0:17:45 People, like you mentioned earlier, expect that renting an apartment is super easy, super frictionless, and it doesn’t require extensive human contact for basic stuff.
0:17:48 And that’s a great opportunity for AI.
0:17:54 So I think you’ll see that these career paths are, in the short term, menial parts of the job go away.
0:18:00 And people are spending time focusing on building relationships with residents, creating communities.
0:18:02 I think people are spending more time at home, right?
0:18:04 They’re working at home.
0:18:05 Their home is their office.
0:18:09 Like, you still need this human connection.
0:18:18 And a lot of our customers, we see that, are creating roles like community engagement and helping people socialize.
0:18:21 I think people will specialize tracks.
0:18:30 So you might become, instead of this sort of generalist on site doing everything menial and complex, you’ll actually see a lot more specialization.
0:18:40 And you might become a renewal specialist who handles the trickiest retention cases or a resident experience specialist that resolves conflicts.
0:18:54 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.
0:19:02 Yeah, and I’ll add up to that, that on the maintenance side, obviously, I think that physical aspect is never going to fully go away.
0:19:12 I think it’ll be a lot more efficient, which I think is really, really needed because there’s just huge shortages from labor perspective.
0:19:16 And a lot of the maintenance technicians today are actually over 50 years old.
0:19:23 So you can see that in the next few years, it’s only going to get worse and worse if there are no more efficiency gains.
0:19:26 Going back to just the future of housing for a second.
0:19:30 So let’s say, you know, 10 years from now, we have robotics.
0:19:34 You know, we’ve made some major advances in longevity research.
0:19:36 We have AGI.
0:19:42 But when you paint, what’s sort of the experience going to look like?
0:19:50 Or how are those impacts, the ones that I mentioned, at least robotics and longevity, going to impact the market and asset class?
0:19:53 I think the population is going to change a lot with AI.
0:20:02 Why I kind of talk about longevity is, I think a lot of AI research is and should be going to extending human life.
0:20:08 But if, obviously, if you’re living longer, there are more people around, staying around longer.
0:20:12 And, you know, we talk about cost of living a lot.
0:20:19 Cost of living is actually one of the, it is the number one reason that people don’t have more children.
0:20:34 But if AI creates a lot more wealth in the world and it brings, and, you know, it does things like bring the cost of living because of the efficiencies similar to what we work on in housing and healthcare, people have more kids.
0:20:36 Again, you have more population.
0:20:44 So, all these things, I think, will really affect, will really affect the housing market because all those people, this is a fundamental need for all those people.
0:20:48 So, yeah, we have to find efficiencies.
0:20:53 Kind of, as I mentioned before, it is more housing supply.
0:21:00 And that’s where sort of robotics can come in and play a huge role, which is, can we use robots, you know, manufacturing?
0:21:03 Can we do, you know, modular housing?
0:21:07 Can we build faster with robots?
0:21:09 Can we bring down the cost of construction?
0:21:15 And I actually think this is an incredibly, that’s like, that’s one area that we’ve never touched.
0:21:19 We’re not, we’re not a hardware company yet.
0:21:26 But it is sort of this big kind of piece of the puzzle in the long-term vision that really needs to be solved by somebody.
0:21:31 And I think you also want to leverage the technology to increase mobility in general.
0:21:36 I think today people are stuck in these 12-month, 24-month leases.
0:21:42 I think you want to, in the future, you want to have, like, flexibility to just move in tomorrow and that to be very cheap.
0:21:48 And you can have, like, much, much greater degree of flexibility.
0:21:53 Yeah, I think mobility in the market is incredibly important and productive for society.
0:22:02 So if you think about it, we are signing these 12-month leases and locked into these contracts as consumers.
0:22:05 And that’s a big commitment.
0:22:06 A lot of people don’t want to sign these leases.
0:22:11 But it’s really laborious to turn over every apartment, not just, you know, the maintenance turnover,
0:22:17 but finding somebody, answering all these, you know, the same 50 questions over and over again, touring.
0:22:22 It’s just, there’s so much labor that it makes it really difficult for an operator,
0:22:28 like a housing operator to find a new resident or a new tenant.
0:22:31 AI doesn’t really care if it’s signing shorter-term leases.
0:22:34 It’s just doing, you know, it’s doing that over and over and it scales.
0:22:41 Then you kind of get the benefit for that, both for the landlord and for the consumer,
0:22:46 that they can be more, they can do it at a cheaper cost and people can be more mobile.
0:22:48 I think that opens up a ton of opportunity.
0:22:52 That’s, you know, people can move for jobs easier.
0:22:55 People can move for their children’s schools.
0:22:58 They can increase, improve their quality of life.
0:23:01 So I think there’s a bunch of different benefits of mobility.
0:23:06 We’ve been talking about technology as a lever here and the need for it in real estate,
0:23:10 and yet real estate spends the least on R&D of any other industry.
0:23:12 Why is that and what could be done about it?
0:23:17 I think solving housing operations is incredibly hard.
0:23:19 The search space is massive.
0:23:22 There’s just a ton of different edge cases.
0:23:23 We face this every day.
0:23:25 Every single building is different.
0:23:29 And it’s a really large expense for people.
0:23:36 So it makes all these things make these interactions with an apartment, like leasing.
0:23:40 It makes these interactions really complex.
0:23:49 So in the past, you’ve really just needed a person because traditional software couldn’t handle the variability that was required.
0:23:54 So if you needed a person anyway, there wasn’t really a motivation to buy technology.
0:23:57 You just leaned on that person.
0:23:59 You leaned on people to do absolutely everything.
0:24:02 Of course, those people got really overburdened.
0:24:07 But also in the meantime, a lot of that critical data was never collected because it just lived in people’s heads.
0:24:12 So now AI has changed what’s feasible.
0:24:15 And it can handle these really large search spaces.
0:24:18 It can handle these really complex operations.
0:24:24 So, I mean, in addition, real estate is so far behind on tech.
0:24:27 It actually has the most to benefit from AI.
0:24:33 So it maybe is going from the lowest R&D spending to potentially one of the highest spenders on AI.
0:24:41 Because AI has sort of finally unlocked automation that was possible that really they couldn’t take advantage or they couldn’t optimize it before.
0:24:54 How do you respond to critics of PropTech who just say, you know, PropTech is here to help residential real estate companies extract more value from their tenants?
0:24:56 That’s honestly a pretty silly argument.
0:24:58 I get it.
0:25:01 I think housing is really an emotionally charged subject.
0:25:10 People apply these irrational expectations to landlords that they never apply to other types of business owners.
0:25:12 So think about other industries.
0:25:22 Like, you wouldn’t want airlines to stick to paper ticketing processes so that they extract more value, so that they don’t extract more value from tech efficiencies.
0:25:26 Or you wouldn’t, you know, if a supermarket didn’t use scanners or barcodes.
0:25:33 It’s pretty self-evident that technology makes the experience better for everyone and brings down costs.
0:25:37 So we actually want landlords to use as much technology as possible.
0:25:43 Because, you know, when they’re slow to innovate, that’s really actually bad for consumers.
0:25:48 Yeah, and we think that the barriers to entry are already quite high.
0:25:50 The operations are very complex.
0:25:53 Everything you have to do is multimodal.
0:25:54 So much stuff is manual.
0:26:00 So I think that limits the amount of people that can get into that business in the first place.
0:26:05 And I think that actually gives a lot more pricing power to the existing landlords.
0:26:11 So you can kind of make the argument that actually, like, all of this inefficiency is really bad for the consumer.
0:26:17 And I think at the end of the day, we believe that competitive markets, you know, take care of themselves.
0:26:24 And I cannot think of a single example where, you know, technology was banned and then costs went down.
0:26:26 I think that just never happens.
0:26:29 Yeah, it’s exactly the opposite, right?
0:26:34 So generally, when technology is introduced, you see a surplus.
0:26:37 And most of that typically goes back to the consumer.
0:26:44 The criticism of PropTech would be, is it all going to the property managers and the owner-operators?
0:26:50 And, you know, hopefully, as more and more AI is adopted, it’s going to address this affordability crisis.
0:26:52 Yeah, you need mass adoption.
0:26:56 That’s where the competitive markets take care of themselves.
0:27:00 So there’s rising repairs, maintenance costs.
0:27:03 These keep vacancies longer.
0:27:06 You know, apartments aren’t occupied.
0:27:09 This leads to higher housing costs as well.
0:27:12 What is a lease doing to address this?
0:27:13 What can be done over the next five years?
0:27:19 Yeah, I mean, obviously, there’s a very physical component that needs to be taken care of.
0:27:23 But actually, where we think AI and technology more broadly can help,
0:27:26 all of these problems are actually very complex.
0:27:31 planning problems that are quite difficult to solve with the current level of technology.
0:27:36 There’s so much computation that you need to do around, like,
0:27:39 how do you get smarter at scheduling technicians?
0:27:40 How do you get smarter at routing?
0:27:48 How do you kind of embed a lot of these common sense things that everybody on the ground knows?
0:27:54 You know, if you’re fixing a dishwasher, at the same time, somebody can go and fix the holes on the wall.
0:27:58 But if you actually want to paint the wall, first you need to fix the holes.
0:27:59 You cannot just paint over the holes.
0:28:06 So kind of like there’s a lot of technology there that we believe we can build that will make all of these planning,
0:28:11 purchasing, purchasing, scheduling, orchestration decisions so much more efficient.
0:28:20 And we’re not even touching, like, what we think can be another big needle around that preventative aspect of, like,
0:28:23 how do you track what’s going on in a property?
0:28:31 How do you know when appliances come near their end of life and replace them in smart and cheap ways?
0:28:36 And we feel like all of these problems can have a really, really big impact.
0:28:46 Because today we see our clients waste days and days without, because, like, some piece of information got lost.
0:28:55 Yeah, every day you shave off from the average unit turn time nationwide unlocks billions of dollars in value.
0:28:58 So there’s a ton of value just by moving the needle a little bit.
0:29:02 The cause of those delays is completely avoidable stuff.
0:29:07 So, like, this part wasn’t delivered, or the data wasn’t input into the system,
0:29:09 so the next person wasn’t scheduled for that job.
0:29:12 And it’s totally addressable through automation.
0:29:15 And those are the problems that I think are really exciting.
0:29:25 So when I met Mina in 2021, she and Tony were building a relatively narrow tool for leasing.
0:29:29 We were catching up a bit over a year ago in 2024.
0:29:35 Leasing had gone to broader residential ops, so maintenance that we’ve talked a lot about,
0:29:37 billing, delinquencies, et cetera.
0:29:42 And then she dropped, we’re launching in healthcare.
0:29:43 We launched in healthcare.
0:29:47 And I thought to myself, like, you know, Mina, Tony, that’s insane.
0:29:51 What do those two industries have in common?
0:29:56 And I kind of just dismissed it, kept it in the back of my head.
0:30:01 And then, you know, catching up a couple months ago, and the healthcare business is humming.
0:30:06 Maybe share what is similar in the workflows?
0:30:07 What is different?
0:30:09 What’s been most exciting there?
0:30:11 Yeah.
0:30:16 We’ve been mostly, like, I agree with you, like, those two fields look very different.
0:30:20 But we’ve been mostly touching the admin piece of the healthcare.
0:30:23 And we found, like, those problem sets are quite similar.
0:30:30 You kind of see, like, these very bloated cost structures that, you know, have so many inefficiencies.
0:30:32 They’re all struggling with staffing.
0:30:36 All of these total costs, you know, gets pushed to the end consumer.
0:30:49 And we think a lot of the causes of that is, like, the very similar dynamics we see between these complex digital physical interactions that are full with regulations.
0:30:55 And we believe AI can help quite a lot, both of them.
0:31:00 We see, like, so much commonality around how they approach things like intake.
0:31:06 You have to collect very structured information around names, preferences, budgets, insurances.
0:31:11 And you keep dealing with this really high volume of repetitive inquiries.
0:31:14 You get the same questions again and again and again.
0:31:20 And it’s all done over the phone, over conversations.
0:31:27 We’ve been able to adopt quite a lot of our technology pretty seamlessly.
0:31:32 We developed our voice technology over the housing space.
0:31:35 And that has translated really, really well in the healthcare space.
0:31:41 And the same thing with a lot of the scheduling optimizations we’ve been doing have translated quite, quite well.
0:31:44 So, they kind of feel very, very different.
0:31:53 But from admin organizational operations perspective, we’ve barely been surprised by anything by transitioning to healthcare.
0:31:58 We spent a bunch of time earlier talking about why housing costs are so high.
0:32:05 It seems like no matter what, healthcare costs remain at a sixth or a fifth of the economy.
0:32:10 Is it that we’re just getting a better product for that cost?
0:32:13 Because is healthcare good that we just keep wanting more of it?
0:32:17 And so, no matter what, we get something better and we’re just going to keep spending?
0:32:19 Is it an elastic in that way?
0:32:28 Or is it that some morass of regulatory challenges prevents technology from really bending that price curve?
0:32:29 What’s happening there?
0:32:31 Why are costs staying the same?
0:32:35 I think it’s both are actually true.
0:32:42 I think healthcare is definitely a very elastic need where people are getting better healthcare, people are getting more healthcare.
0:32:46 I think if costs go down, people would want even more healthcare.
0:32:49 So, I definitely, and that’s a good thing, right?
0:32:52 I think that makes people live longer, happier lives.
0:32:54 And I think that’s super important.
0:32:55 And that’s all true.
0:33:00 But I would say, like, on the admin side, I don’t think we’re getting a better admin experience.
0:33:07 And I think the costs on the admin side have really skyrocketed way faster than anything on the clinical side.
0:33:19 And I think partially people have invested in technology, but it just hasn’t been quite good enough, again, because so much is happening over the phone in these unstructured interactions.
0:33:26 But we think with the current level of technology, you can actually make a really big dent into the admin aspect.
0:33:40 I don’t think in healthcare, there’s been this huge boom of technology adoption that has, we’re surprised we haven’t been, it hasn’t flowed to consumers’ pockets yet.
0:33:47 I think we’re, we’ll see that with AI, but I don’t think the cycle has given its feedback yet.
0:33:49 So I am still hopeful.
0:33:58 But yeah, it can, I think it can arise in either lower costs or better, better outcomes or a combination of both of those things.
0:34:05 In housing, you guys have really gone from leasing to broader resident ops.
0:34:09 You’ve started with scheduling on the healthcare side.
0:34:12 Where do you think the platform goes from here?
0:34:16 We think for us, healthcare is much earlier.
0:34:28 We think there’s so much more that’s happening on the admin backend side of things that we feel like there’s so much inefficiencies that needs to be addressed.
0:34:33 And I think that’s going to take a bit to actually cover all of that ground.
0:34:43 But I think anything from, you know, that first interaction to the billing cycle and more importantly towards like,
0:34:48 how do you kind of keep the communication post appointment with the patient?
0:34:52 Because I think today, you know, you go in and spend 10 minutes with the doctor.
0:34:54 They’re definitely very helpful.
0:34:58 But then you get a piece of paper and it’s like, good luck from there onwards.
0:35:05 I think AI can help quite a lot with engagement on the patient side.
0:35:08 And I think there’s a lot to be done there.
0:35:13 Yeah, you go home from your appointment, you have like four things that you’re supposed to do every night for the next week.
0:35:15 And what is adherence to that?
0:35:16 Pretty low.
0:35:20 But if you got, you know, an Elise message every night, you’d probably do a better job.
0:35:29 Yeah, I think AI plays a great role in education and leaving the outcome on the patient.
0:35:39 If AI can scale and achieve better treatment planned, you know, fulfillment, that’s going to be better for everybody.
0:35:42 It’s certainly going to save us a lot of costs.
0:35:44 You know, it’s one of the government’s largest expenses.
0:35:49 And so we’re all paying for that, those outcomes being poor as well.
0:35:52 Yeah, and this adherence is not easy at all.
0:35:55 Because like, again, patients are very stressed when they go to a doctor.
0:35:58 It’s not an easy thing to do.
0:36:04 And I think AI can help them, give them more time after the appointment to ask questions.
0:36:08 Obviously, there’s things like language barriers that AI can help quite a lot with.
0:36:11 So I think there’s all these benefits that we’ll be able to.
0:36:16 Yeah, and involve family members who probably weren’t able to attend the appointment or the procedure.
0:36:23 Yeah, you have to think about all your questions, right, in the moment when you have that time with the doctor.
0:36:26 And then if you think of something, you’re SOL.
0:36:28 If you think of something too late.
0:36:32 In this episode, we’ve been talking about housing, we’ve been talking about healthcare.
0:36:36 These are two extremely complex markets.
0:36:42 I’m curious if you can go back in time, you know, knowing what you know now, what might have you done differently?
0:36:45 I probably would have started with affordable housing, actually.
0:36:52 Affordable housing has kind of every problem that the rest of the industry has.
0:36:59 Plus maximal complexity because of all the dense compliance and paperwork, all the additional requirements.
0:37:02 And they are the most underserved.
0:37:09 They have the biggest administrative drag, and they are also some of the slowest adopters.
0:37:15 So it just shows that there’s this huge, clear opportunity for them to take advantage of AI.
0:37:18 And it just takes longer to get there.
0:37:22 So that’s, I think, one big thing I would change.
0:37:27 We’re actually kind of approaching healthcare in a similar way, which is start with what is the most underserved?
0:37:29 Because that’s where we can have the largest impact.
0:37:37 The most underserved and the most complex, because if you sort of solve those problems, then the rest of it is sort of easier downstream.
0:37:41 Perhaps let’s close on the ultimate vision for Elyse AI.
0:37:51 If you achieve everything you’re setting out to do, and obviously you’ve achieved a ton to date, what more can you say about what that looks like at scale?
0:37:55 I think our drive always has been cost reduction.
0:38:08 If at some point, and obviously it’s not just one company’s effort, but if at some point we get to a place where housing and healthcare are not cost concerns for the average person, I think that would be amazing.
0:38:26 Yeah, I think if we can take this 42% of what a household spends on housing and healthcare and bring that down to 20-something percent, that is, I think, one of the most important problems we can solve.
0:38:28 And more people should be working on it.
0:38:30 That’s a great note to wrap.
0:38:33 Min and Tony, thanks so much for coming on the podcast and being part of the portfolio.
0:38:38 Thanks for listening to the A16Z podcast.
0:38:44 If you enjoyed the episode, let us know by leaving a review at ratethispodcast.com slash A16Z.
0:38:46 We’ve got more great conversations coming your way.
0:38:48 See you next time.
0:38:52 As a reminder, the content here is for informational purposes only.
0:38:58 It should not be taken as legal, business, tax, or investment advice, or be used to evaluate any investment or security,
0:39:02 and is not directed at any investors or potential investors in any A16Z fund.
0:39:07 Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast.
0:39:15 For more details, including a link to our investments, please see A16Z.com forward slash disclosures.
Housing and healthcare make up nearly half of household spending, yet both sectors are riddled with inefficiency and rising costs.
In this episode, Erik Torenberg is joined by a16z Growth partner Alex Immerman and Minna Song and Tony Stoyanov, cofounders of EliseAI, to discuss why they’re tackling these critical industries and how AI can transform everything from leasing and maintenance to patient scheduling and compliance.
The conversation covers:
- Why the U.S. is 5 million housing units short — and how technology can help unlock existing supply
- How automation can cut waste, reduce labor costs, and improve affordability
- What fully autonomous buildings might look like, and how that model could extend to healthcare
This is about the costs that touch every household, and the role AI might play in finally bringing them down.
Resources:
Link to blog: https://a16z.com/announcement/investing-in-eliseai/
Find Minna on LinkedIn: https://www.linkedin.com/in/minna-song/
Find Tony on LinkedIn: linkedin.com/in/stoyan-tony-stoyanov-07690a53
FInd Alex on X: https://x.com/aleximm
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.