James Cook: We are in an AI revolution right now in the business world. We're getting personalized recommendations in finance. We're seeing optimization of supply chains in retail. Even medical diagnoses are happening with the assistance of AI. But what about in my industry?

What about in commercial real estate?

Raj Singh: I think the industry as a whole has not particularly followed the trend of increasing use of technology in order to produce results. So, if you look at other industries like the financial services industry, retail and e-commerce, for example, even places like medicine and healthcare, there's been a lot more technology deployed than there has been in our industry.

There are good reasons for that. Chief amongst them has been that the commercial real estate industry has been an extremely profitable place to be for decades. But we all know that things have changed a little bit since then.

My name is Raj Singh. I am the Managing Partner of JLL Spark Global Ventures, and we are the corporate venture catalogue of JLL.

James Cook: Today, we've got two guests with expertise in AI and commercial real estate. First, we're going to be joined by Raj Singh. He's going to shed light on the evolution of AI, where it's headed and what are the crucial investments that companies should be making right now. And later on in the show, I'll talk with Jeevan Kalanithi. He's the CEO and co-founder of OpenSpace. He's going to talk about how his company uses generative AI and computer vision to track the progress of a construction site. So, let's get into it. I am ready to embrace the future of real estate technology. It's time to talk AI and PropTech.

This is Trends and Insights: The Future of Commercial Real Estate. My name is James Cook, and I am a researcher for JLL.

James Cook: So, Raj, Let's say we're at a cocktail party, I don't know anything about real estate or venture funds. How do you explain to the lay person what it is that means like what you do?

Raj Singh: the way I usually go about it is, I talk about how large companies have evolved over time by being very good at certain things. That's how they get to be large and successful. But once they get to be large and successful, it becomes increasingly harder for them to be able to innovate, to do new big successful things because they already have a lot of success going on and there's less appetite and enthusiasm to go blow that all up and go do something else.

So, what a venture capital group does is it invests in startups that it believes will be successful by bringing a product or service to the marketplace. And a corporate venture capital group is a venture capital group within a corporation that says, you know, we want to continue to innovate, we want to continue to find new ways of bringing value to our customers, and so we've created this little group, we've given them some money, and they go out there and find startups that they think are going to be successful in our space, ones that will be strategic to us in some way, i. e. we can change the trajectory of the company by using the products and services that the bring to the table.

James Cook: Today, I want to pick your brain a little bit about AI. So, in my non real estate world, I am blown away by what generative AI and large language models can do, from creating DaVinci style paintings to composing songs, writing poetry, translating, telling me anything I want to know on chat GPT. It's Amazing. So, I don't think it's a flash in the pan, but I am curious what you think its impacts will be on commercial real estate. And is it right around the corner or is it going to be a while?

Raj Singh: I think the answer to the timing question is both. This form of AI is the latest version of 50 years of research. The name generative AI is really particularly apt because it allows you to create something that's new from the information that it understands in the past.

We have a huge amount of data in contracts and leases and building code and zonal codes and all those things and getting all that information to a form where you can actually develop an insight is really hard, and generative AI is the first tool that's come along that would allow you to throw everything into a large language model and get insight out of it without having to do all the pre structuring. It will have a very strong impact. Longer term, however, what will happen is everybody will do that, it will become just like, the price of doing business.

And then we'll get another peak where people start to understand, well, okay, how do I change the way I do business? Not just getting these insights, but how do I change the way I do business using AI in order to be able to sort of restructure the economics of what I do. The way that I think about this is that, in the macro world, we have a few trends going on. One of those trends is increasing automation, right? So, we see robots and we see technology everywhere. Another trend is that we do not see people entering the industries that we would like them to enter in order to be able to power the services we have today. We will have to turn to automation in order for those tasks to be done in the future. And so, an industry that has been largely tech phobic is now facing the reality, which is that they're going to have to adopt tech if they want to do things in the way that they've done in the past to be successful for the future, but they're also going to have to retool their processes, and that retooling will be painful, but the end result will be a much better economic way of doing business.

James Cook: One of the, the barriers I've always seen, particularly with commercial real estate, is this data problem where it's all this specialized information. A lot of times it sits in no centralized place. And oftentimes it’s proprietary. Do you think that there's a barrier to success in that these tools just won't necessarily have access to the most accurate and up to date information?

Raj Singh: We have an opportunity to do better here. And that opportunity is by giving people AI tools that they interface with so that I don't have to ask them to enter information into a system. By the very nature of doing their job, the information comes, and so they no longer have that sort of annoying admin staff work that they need to do afterwards. We can extract that from what they're doing on the day to day. That would be very timely and up to date and accurate without them having to take any further effort. So, I think there is an opportunity for us to do that.

We have to be careful. Not all data is created equal. Some data is protected and privileged. Some of it belongs to our clients, some of it belongs to us. The A. I. tool has to be smart about what can be done with what sort of data, and that's the path that we're going down right now, which is, let's use our own data, the information that we know we own and have the rights to and start there, and then over time we may end up creating many versions of these tools, spinning them off in a way that would allow a customer to put their data into the tool and that data won't spread to anybody else, won't be used by anybody else, and will be confidentially and securely held for their benefit.

I honestly do think that plus my previous comment about taking that unstructured data we already have, putting it into the model, and hey, presto, more or less, the combination of those things is actually going to be extremely powerful for us, and I think we'll be able to unlock data in a way which we've never been able to do before.

James Cook: As you're looking at new technology out there, what's an example of something that you've seen that you think is interesting?

Raj Singh: There's company called QBIC, Q B I Q, and what they're doing is allowing you to take a two-dimensional floor plan, let's say of an empty floor in a commercial building somewhere, And view that in 3D. So, the AI generates a 3D image of that space and it's become a very powerful way of visualizing that space, obviously we are 3D beings and that's how we think and operate. Looking at a floor plan gives you one level of understanding, but seeing the actual space as it might be gives you a whole other level.

There's a company called EliseAI based in New York. They have created a virtual chat bot that it acts as a kind of leasing agent. You can Ring it up and it will talk to you, or you can text with it, and it will give you all the information that you need to know about a particular building that you might be interested in, including setting appointments and that's all using generative AI, as well.

And then I recently saw a company called TestFit that is allowing you to understand whether a particular site would be an appropriate one for a distribution center or a warehouse.

I think what you'll find is that these sorts of ideas are cropping up now. And they’ll be like mushrooms. They’ll be everywhere.

James Cook: So, Raj, so much of what you're describing, you know, you describe a chat bot that gives you information on a building, that sort of sounds like a junior leasing associates job or taking a bunch of reports and coming up with insights, hey, that's my job. I'm the research guy. So, my question for you is, how does that translate? Does that mean, oh, we've got just more help, more insight on the team, or is it actually replacing team members?

Raj Singh: The way that I like to describe it is that the AI will replace tasks, not jobs. So, if you think about anybody's daily routine, there are some tasks that require them to be really thoughtful, to lean on the experience that they've had over many years in the industry, where they're really adding value to their client. And there are some tasks that are frankly boring and repetitive that we all kind of have to do as part of our daily routine. And so, what I would say is that the AI is really good at the boring, repetitive stuff. What I imagine will happen, or this is one possibility, is that we take the AI and we strip out a lot of the boring repetitive stuff, the stuff we have to go search for things we don't know what's going on, the stuff we have to fill in forms, and let the AI do that for us. We then have the option to be able to verify it's done it correctly. So, there's always a human in the loop. And then that compression of the time taken for those boring tasks frees up a lot of other time. Ideally, what then happens is those people say, you know what, I can add more value here. I have the time to do this. I can go more in depth. I can be more precise. I can come up with new ideas because I've been freed up from all this, you know, drudgery that I would normally do.

At the same time, let's be intellectually honest. Many people will use it as a way of replacing other people. That's honestly been the pattern throughout our evolution. One of my favorite statistics is that, in the year 1900, 41% of the U. S. population was involved in agriculture. Today, that number is around 1%. Now, you don't see hundreds of thousands of farmers on the streets today complaining about not having a job, right? People have evolved. They're doing different jobs. And what you tend to see with these sorts of technologies is that you do see a dislocation, first, when the technology starts getting rolled out. But then over time, what you see happening is that people find other niches because machines aren't really able to replace humans. They're just able to enable humans. So, at the base case, yes, you might get more machines and fewer people, but if you do it right, you're giving people even more interesting and rewarding jobs to do, and the machines enabling that.

James Cook: I love it. That's a great vision for the future. Let's imagine for a moment that there's an investor that owns a bunch of commercial property and they've hired you to consult with them. And they're saying, Raj, how do I prepare for all of this? I don't even know how to deal with all of this new potential technology, what would you advise? How should an investor, a developer, property owner get ready for the future?

Raj Singh: My advice to them would be to start trialing now some of the different generative AI solutions out there to understand what they can and can't do. What they will find is that having the technology alone is insufficient. The technology is not a magic bullet. But by having those trials, they will start to understand where the gaps are between how their process works, what data they're collecting, how their people like to operate and what the technology can do. And once you've got that, you can then start iterating around, well, what part of the technology do I need to change to suit my use case? And what part of how I do business do I need to change in order to take advantage of technology? And that second part is actually really important. I'm old enough to remember the advent of SAP and all of this huge sort of enterprise management systems. And time and time again, we saw large organizations spend millions of dollars on customizing the technology to suit their process, whereas the question ought to have been, how do I make my process more efficient and change it to take advantage of technology. That process is the thing that I think people should be starting on now because whoever does it right will have a huge cost and time advantage versus their competitors. And it's one of those things that it's really hard to recover from if you didn't go down that path,

James Cook: Raj, this has been a fascinating conversation and I feel like, you know, we could catch up every year and a million things would have changed and been different because this is moving so fast. So, thank you so much for joining me today. This has been a wonderful conversation.

Raj Singh: It's my pleasure, James.

James Cook: And now we're going to continue to look into AI and commercial real estate prop tech with a single case study. We're going to hear about OpenSpace. That's the company that's using AI and computer vision to tackle an age-old construction pain point.

Jeevan Kalanithi: Hey, my name is Jeevan Kalanithi and I am the CEO and Co-Founder of OpenSpace.

James Cook: I have asked you here today, Jeevan, to dig a little bit into the intersection of PropTech and AI and sort of tease out like. you know, what's reality? What can we expect in the future? And maybe what's more science fiction?

But to start, tell us what open space does.

Jeevan Kalanithi: OpenSpace is a computer vision and AI company and what we do is really pretty simple. If you're maintaining or building any physical space, we make it incredibly easy to have a full visual record of that space. In addition to that, we have a layer of AI technology that will be able to identify things in that building, specifically during the construction phase. And so, we can measure progress: Say your drywall is behind schedule. It's 30 percent complete, supposed to be 40.

James Cook: Oh, I see. That's interesting. So as opposed to having somebody actually go in and report on progress, the AI is just doing that for you?

Jeevan Kalanithi: That's exactly right. It does it for you. And it does it in a way that's objective. It does it in a way that's really auditable. So, you can just go click and see like, well, the system tells me it's 30 percent complete, I can just go click a button and look around virtually from my computer without having to have someone physically walk around and check every last assumption. So, it just makes life easier and creates that transparency layer for builders.

James Cook: I wonder, do you ever run into a client whose expectations are through the roof because of what they're seeing in the world? You know, they see like a Dahli making a Jackson Pollock out of nothing or something, and they say, well, hey, can't AI do everything now?

Jeevan Kalanithi: I think it afflicts all technology companies in every space all the time. You certainly see that in robotics where people will see a cool video of a robot walking around, and they're like, oh my god, that should just work. It's like, well, no, that's a really controlled environment that, that robot video you saw on YouTube is, it's not ever going to work in, in real life in prime time. And it is a problem because there's an incentive, not just for academics to put out cool videos, but for technology companies to claim they can do more than they really can. So, I think it's a challenge. And ultimately what you have to do really in any business is try to deliver something of value, have someone try it and then say, yeah, this works.

James Cook: So that was one challenge. What do you think is the biggest challenge either for you or for the greater Proptech industry?

Jeevan Kalanithi: Just the fact that the industry we serve is incredibly complex, and that the incentives for behavior are incredibly complex. And what might seem like a good idea, if you read it in the McKinsey report, or think of it on your kitchen table, it may not really motivate people to use your solution.

It's a very nuanced world. And so, I think that's always a challenge. It's always a challenge to make sure you're solving a problem that your customer really feels as a pain and will pay money for. And the other thing that exacerbates that is what people need and what they want in prop tech, it changes relatively rapidly because the market is very sensitive to economic conditions. So, you have to be very nimble and make sure that whatever you're putting out to the market is something that makes sense across a variety of contexts, such that you don't build something that's only optimal for like, 2021 second half of the year and then is irrelevant after that.

James Cook: Let's talk a little bit into the future. I don't know, say midterm horizon. What do you think we should expect from OpenSpace in the future that currently you're limited by what technology can do today.

Jeevan Kalanithi: For technology, like ours, we see our customers just grow to depend on it. Where being able to just look and see what's there without having to like worry about someone misdescribing something to you, it just becomes standard.

So, where I see the technology going is just to enable that more and more, help them find things in the data much more easily that can use very standard technologies and also some very advanced AI that can help search these incredibly complex visual data sets. I think that's gonna be pretty exciting.

Our ability to track more and more things customers care about grow as well. So, you can really have this all seeing copilot to help you do your job. We don't believe it's going to replace what people do. Like it's not wise, but it just helps you answer things in a way that's much easier.

James Cook: It seems to be, it's both, the promise and the anxiety around artificial intelligence is that it's going to take on human tasks, at first the distasteful tasks, but Oh no, what if it's my task? You know? So when you think about the Proptech industry as a whole, is it a similar vision for the future where just over time, more and more things are able to be managed by an AI?

Jeevan Kalanithi: I think I would divide this into construction specifically in Proptech broadly. So for people in construction, I think it's just a straight up boon every way around. It's just going to make life easier. And there's so many things that builders have to do that are paperwork related that they can potentially dispense with and this focus on doing what they do best, which is to build awesome buildings on time and on budget. I think AI doesn't bode too much of an issue because so much of that work is done in real physical reality and it needs humans to do it. I don't expect robots, for example, to replace humans in 3D space in any meaningful way.

There will be robotic tools, but they'll be like super tools as opposed to like Terminator bots with nail guns or something. In that sense, I think construction has a lot to look forward to. PropTech, broadly speaking, it is a good question. I do think that there are a lot of things which are considered bureaucratic things like paperwork things, that can start to get automated. And that may threaten some people's jobs, it's true. Although I think it's going to enable more people than not to focus on business decisions as opposed to box checking.

I don't have the crystal ball, but I don't think that you'll see like massive changes in the workforce of who's in Proptech, but more enablement of good deals to happen, ideally sooner with less hassle. Like ideally development projects for example, you get started much sooner because AI can do a much better job of analyzing the risk of a given project. So, I'm hopeful about it.

James Cook: Thank you for taking some time out of your, your busy schedule to talk to me today. It's been a fascinating conversation.

Jeevan Kalanithi: More than happy to do it. Thanks for having me.

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