3514: How JLL Is Reshaping Commercial Real Estate Through AI

[00:00:03] - [Speaker 0]
In today's episode, we're gonna turn our attention to how AI is reshaping commercial real estate and the environments that we live, work, and spend our time. And my guest is the global CTO at at JLL, and she's an inspirational lady. Let me tell you that much. And we're gonna explore together today how the company is bringing intelligence into property operations and doing so through a new AI powered property assistant, one that's built on their JLL Falcon platform. But we're gonna have to look a lot deeper into this today from practical performance insights for property teams to the wider investment roadmap shaping the future of real estate.

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We're gonna look at how AI is moving from experimentation into real operational impact across retail, office, and industrial spaces, and we will also finish on an incredibly powerful message too. Before I bring today's guest on, I just wanna give a massive thank you to my friends at Donodo because after visiting over 25 different events in 2025, One of the phrases I keep hearing is no data, no AI, and Agenic AI simply needs better data. Now Agenic AI is here, but it only works when the data behind it is complete, governed, and in real time. And this is one of the areas that Denodo helps because Denodo gives you a logical data foundation that accelerates AI, boosts lakehouse performance, and turns your information into reusable data products and for every team. So CIOs, architects, and business owners each get the data that they need instantly, and their global partners help you get up and running faster than ever.

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So if you want AI that doesn't hallucinate but actually delivers real business outcomes, visit denodo.com and start making your data work harder. But now let's get today's guest on. So a massive warm welcome to the show. Thanks for joining me today. Can you tell everyone listening a little about who you are and what you do?

[00:02:20] - [Speaker 1]
Well, thank you for inviting me to the show. It's it's a really exciting opportunity for me to be able to talk to you. I have been listening to your podcast, and so I can't believe I'm on the show now. So I'm I'm Yael Warren. I'm the chief technology officer at JOL.

[00:02:38] - [Speaker 1]
I'm responsible for JOL's global technology strategy, product development delivery. On a day to day basis, I oversee a centralized engineering group of about a thousand team members. And it has been a really amazing journey working in JOL, which is a commercial real estate company. We really, you know, seeing technology, data, and AI being its differentiator and being its part of its core strategy.

[00:03:12] - [Speaker 0]
Well, it's an honor to have you join me. I've had a few people from JLL on the podcast throughout the years. Of course, JLL has been investing heavily in AI across its global portfolio. So when you look at the commercial real estate landscape today, I'm curious from everything that you're seeing here, what pressures or inefficiencies made the case for building an AI powered assistant for property teams? Because everyone's talking about AI, but this year, in particular, it's it's all about, well, what problem we're solving?

[00:03:43] - [Speaker 0]
What's the measurable difference? So tell me about that.

[00:03:46] - [Speaker 1]
Yeah. I I think it's it's the thesis for building AI power system for a commercial real estate company is actually quite, you know, I I would say it's it's really powerful. If you think about it, you know, take JLL for example, we manage over 5,000,000,000 square feet globally and 42,000 leasing transactions annually. You can imagine the scale and the complexity of that such a global scale, the volume of transactions we need to manage. So you can imagine the team the property teams will face constant pressure from, you know, all these different workflows from, you know, managing work orders to, you know, managing tenant communication and then making sure we pay the bills correctly.

[00:04:43] - [Speaker 1]
And you can see why AI is such a perfect technology that can really help to reduce that complexity and also increase the efficiency. Right? And then and we recently have done the research across our industry. It really underscores every every practitioner in this field which really seen that opportunity and the urgency to adopt AI. Just a quick some quick stats.

[00:05:14] - [Speaker 1]
We have about 88% of our investors that get surveyed and 92% of the occupiers who are they don't own the buildings, but they occupy in a commercial building, all trying to pilot AI. Mhmm. Because it's just really it's really a clear case for AI where a system can really reduce the complexity and help with the volume.

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And after doing a little research, I quickly learned that property assistant sits on top of JLL Falcon, which is your enterprise grade AI platform. But for everyone listening, how would you describe the technical foundation behind Falcon? And what advantages does it give you when building tools that need both scale and domain specific intelligence? Again, quite a big balance, I would imagine, but you you make it look easy. I'm sure there's a lot of work going on there.

[00:06:06] - [Speaker 1]
It's it's a lot of work, and I will I'm so proud of it, you know, personally and for JOL. Because you if you think about it, the going back to the scale. Right? And to really support the 110,000 employees, 5,000,000 square feet of manage you know, property under management, you really need to think about how do we do everything at scale, but also has to provide the flexibility of accommodating different requirements, different geographic differences. So JL Falcon is no different than than that.

[00:06:49] - [Speaker 1]
It's one is it's built for scale. It's it's built on a very flexible yet scalable architecture that can really help us to continue to evolve what we can provide for developers to build different applications. For example, we have been leveraging the the as you you you know, Neil, every every other day, you will see a new LLM models coming up. It's like, oh, it's already GPT five and Gemini three, right, from yesterday. And so we wanna make sure that as we have GelFalcon, we one is we make sure that we can adopt the newest and greatest from an AI technology perspective and our model perspective.

[00:07:40] - [Speaker 1]
But we also want to kind of abstract away the complexity so that when developers or when our employees using those, you know, AI technology and and newest and greatest LLM models, they don't need to think about what exactly am I using. Because, like, we abstract our way through JLFalcon so that they can actually trust the platform instead to instead of having to worry about what behind what is behind the scenes. So that's a very important part of the scalable and flexibility for Falcon. The other thing is one of one of the competitive advantage and what we truly believe is a company asset is our data. We you know, JL has been around for more than two hundred years.

[00:08:36] - [Speaker 1]
We collect all you know, we I think we have the biggest datasets in commercial real estate and most comprehensive because we also cover at a global scale. We have all these different business lines. So we have amazing data within JLL. And so if you think about it, as AI technology is getting easier and easier to use, then, you know, the being able to use AI is not your differentiator. It's, like, the data behind it.

[00:09:09] - [Speaker 1]
And so in JLFalcon, one of the key thing for us is really making that data JL data very accessible through JLFalcon. So that's another important aspect to it. And lastly, but and also very importantly is the security. Right? And, you know, you know, you know, all this if you with the news, as many great breakthroughs we read on the news, we also read a lot about, you know, AI just wipe off the an entire code base, and then the company, you know, disappear.

[00:09:48] - [Speaker 1]
Right? Or AI just people accidentally leak salary information or, you know, financial information online because they use AI inappropriately. So, like, for JL Falcon is built to really also making sure we have the monitoring, the security app in place so that we can help manage that. Because one is JL demands it, and then also our clients demands it.

[00:10:18] - [Speaker 0]
I love that. And looking at it here, Alec, one of the big promises of the property assistant is faster data driven decision making for teams that are handling multiple assets. So, again, to bring that to life, can you just walk me through a real example of how this assistant

[00:10:34] - [Speaker 1]
Yeah.

[00:10:34] - [Speaker 0]
Can turn raw data into a clear recommendation that a property manager can act on straight away?

[00:10:41] - [Speaker 1]
I I love that because, like, if you've commercial real estate sometimes can feel like, well, you know, why does that have anything to do with me? Right? But if you think about it, commercial real estate is in your everyday life. So anything that's not your own house is a commercial real estate building. Right?

[00:10:59] - [Speaker 1]
You go to the mall to buy to to shop. You go to a restaurant to to eat. You go to, you know, grocery store. They are all commercial real estate buildings. So, actually, commercial real estate is very real.

[00:11:12] - [Speaker 1]
And then the application of AI in commercial real estate is actually very real, and then you can feel it. One of the things that I'm sure that you you and a lot of the listeners probably have experienced is, okay. We are coming back to the office, but all the meeting rooms are are occupied. And then you have to go walk around for ten minutes to find a meeting room. So property assistant actually really help, you know, solve this kind of day to day problem.

[00:11:42] - [Speaker 1]
For example, just take that example I just mentioned. We we can a lot of the buildings nowadays have sensors to monitor the occupancy, how much traffic there is in all these areas. And then so property assistant will automatically monitor those sensor data and then start flagging the problem. But flagging flagging the problem is actually the easier part, and then the first part, right, is what it will recommend you to do. Because there are a lot of different things you can imagine you can do that.

[00:12:19] - [Speaker 1]
Right? You can go from, hey. We I'm just going to release some of the meeting rooms that are booked, but not actually having anyone in it. You can release it right away. Or you can that's, like, short term tactical things.

[00:12:34] - [Speaker 1]
Or you can go to the long term. It's like, maybe we just need to get more space, and then the space or location need to be be changed. Right? So, like, the property assistant can go from data to recommendation of different solutions from short term to long term, really helping the property team to make decisions based on data, and then also really take the burden of having to think through all the possible solutions. And I I find it really real, and then our property team has been reacting to that kind of efficiency gain and then the hopefulness of thinking through the solutions.

[00:13:17] - [Speaker 0]
And I think everything you just said will resonate with so many people that have been walking around those corridors with their laptop open trying to find a meeting room. We've all

[00:13:25] - [Speaker 1]
been Yeah. Me too. I have definitely had that, experience before.

[00:13:33] - [Speaker 0]
And, of course, operational efficiency is a reoccurring theme in real estate, but the problems are met are very often messy, human, and context dependent. So Mhmm. How does the assistant help teams spot issues in tenant sentiment, work orders, or task prioritization Yeah. They become those bigger challenges?

[00:13:53] - [Speaker 1]
Yeah. No. I I think you hit you hit, like, a a really important question. Actually, beyond, I think, property management or commercial real estate is a lot of problems we are dealing with are messy. Mhmm.

[00:14:11] - [Speaker 1]
And then there are a lot of context and a lot of human element to those problems. So it will be quite superficial to say, well, AI is gonna solve all the things and AI is going to do everything for us like end to end. Right? To me, AI is a perfect partner for a human to really think through the context and the messiness. And so I I think I think where I I see AI and how AI can help teams spot issues is really continuously monitor structure and unstructured data streams and really summarizing that for a human to react to.

[00:15:01] - [Speaker 1]
And then I think that's a a really great usage of AI and system to because that's not really what human is good at. It's like looking at massive amount of data and then trying to make sense of it. I think that's what AI can do and and and help humans to do that. Then we'll have human to really help understand, put the human lens to it, to put the context around it, to really make make from the data to really solving the messy problem. And I I I I love the question that you posed because it's just such a important aspect as we really build AI in a really useful way.

[00:15:48] - [Speaker 1]
Because, like, you have to really think through how AI and human can work together seamlessly to solve real problems, not just theoretical problem.

[00:15:58] - [Speaker 0]
Completely with you. And there is a lot of talk at the moment around it being three years since ChatGPT first dropped and the world became obsessed with AI and how it's changed so much. But I would argue that commercial real estate has gone through structural change long before AI. If we go back five years ago with the introduction of working from home at scale, the evolution to hybrid working, flexible retail formats, the new and the new industrial demand. So I'm curious.

[00:16:27] - [Speaker 0]
How do you see AI shaping tools influencing the future design and use of these spaces over the the next five to ten years? Because how we use buildings and real estate is changing.

[00:16:38] - [Speaker 1]
Yeah. A 100%. And I think AI can play a really big role here. If you think about it, designing a building, doing all the fit outs, takes a lot of work. You have to gather the layouts of the office.

[00:16:52] - [Speaker 1]
You have to, you know, really do a lot of different measurements, taking pictures. And then to redesign a, you know, space is not small task and takes a lot of effort, a lot of, you know, data gathering. I think what AI can really help is, again, AI can quickly gather those data for a designer or architect or a property management team to really help facilitate this redesign process and, you know, helping that helping the property team to react at a much much faster speed to the different demands of of the, you know, commercial real estate space. And just going back to the example of, you know, there's an area that people are constantly looking for meeting rooms. And those data can help the property team to really and AI can also help too.

[00:17:58] - [Speaker 1]
And the property team is like, maybe you can put more meeting rooms in this area and create more coworking space. And and based on those data, and AI can make suggestions of it. And that will be so much faster and provide a continuous data and continuous feedback loops for for the property team to redesign the space at a much faster speed. And then so that we can actually really get ahead of the demands. Right?

[00:18:28] - [Speaker 1]
And before to your point, Neil, like, before the tenants start complaining about it, we will already anticipate it. Oh, I I already see that you have been struggling with this space, and let's let us help you to redesign it. So I think I think it's, like, a really, really exciting direction of travel.

[00:18:50] - [Speaker 0]
Completely agree. And another area we must talk about, of course, is security and trust also becoming major concerns for owners and occupiers around the world. So how do you balance that need for personalized AI driven insights with that flip side, the responsibility of protecting sensitive data across global markets with different regulations, again, I would imagine is quite a big challenge.

[00:19:14] - [Speaker 1]
It's it's definitely a very big challenge. So that's why we take the JRFalcon approach, you know. One is Falcon has a lot of built in security measure and monitoring, so it's not just reactive to, you know, security demands, but continuous monitoring it. Use we use also certain AI technology to help us to detect the possible. One is unethical use of data, and second will be compliance violation.

[00:19:53] - [Speaker 1]
So we also have technology to continuously monitor it to making sure that we address it in the front. Right? So that's and then second is we also don't want to and we the centralized platform idea is also a key to this, is that it's it's gonna be really hard if everyone has their own approach to how to build AI applications, to have, like, all this one off applications, then it makes the security the cybersecurity monitoring and problem a lot more complex. So we want to aggregate all these different activities on one platform. So and then have taking a really centralized approach where one is we can be more focused on our investment in that one platform and making it secure and and, you know, really protect the our data that is going through the platform.

[00:21:04] - [Speaker 1]
This this is absolutely essential when it comes to AI applications. JLL is a global brand and that the brand and the trust of our clients in us as JLL is is so I I can't underplay the the significance of it.

[00:21:27] - [Speaker 0]
And we are recording our conversation at the 2025. So as you look beyond property assistant, start thinking about 2026. Are there any other broader AI, initiatives on your road map that JLL was is looking at? And where do you see the biggest opportunities for AI to improve financial performance, sustainability, and tenants experience? I appreciate you.

[00:21:50] - [Speaker 0]
You probably locked down town, which you can share. Are there any teasers that you can offer?

[00:21:55] - [Speaker 1]
No. You're like, you cover everything. It's like we there are so many opportunities that we are looking at. You know, one is we have you know, if you think back JL's journey, we released our JLGBT, which is our proprietary chat app built on JL Falcon about two years ago, and we have massive, massive adoption. Right?

[00:22:22] - [Speaker 1]
There are we have a 110,000 employees, but we have almost 90,000 active users on the platform. Wow. You can see the adoption. And and then just today, there are, like, 26,000,000 prompts that get submitted in the past two years. We have been very busy using AI.

[00:22:43] - [Speaker 1]
So to to JLL, it's the the reason why I bring this up is that to JLL and JLL employees, AI is not a new thing anymore, and it's not something that we just do experimenting. And it's something that we really believe in it. We use it on a daily basis. And 2026 is really all about, you know, bringing that real impact to our business to your point. Right?

[00:23:10] - [Speaker 1]
So if you can think about it, there there are a few different things that you can from a financial performance perspective, one is, you know, productivity gains to increase our margin profile. And the other thing is how do we serve our clients better and then providing the right insights for our clients so that we have we generate more revenue with our clients. Right? So those are definitely the two focus areas we want to do. And then there are many there are already many innovations I in we have already deployed in production, and property assistant is just one of the many.

[00:23:55] - [Speaker 1]
Right? And then we have a very strong pipeline of more than 50 AI agents, AI assistants in the pipeline that we are gonna roll out. This covers both for our clients and for our employees to continue to gain that productivity. So I'm I'm very excited about all the the the the innovations that is going on in in in JLL. I do want to touch a little bit on the sustainability part because it's such an important thing for JLL.

[00:24:31] - [Speaker 1]
And JLL has such is in such a unique position to really do have a really positive impact on sustainability. So we already have a few AI products that are addressing that. We have a product that is optimizing our energy usage and then automatically help adjust, for example, the the air temperature, the the lighting, and provide energy saving automation there. And then we also have different another tool that to help us to do portfolio optimization so that we can do the right site selections for for sustainability goals for our clients. So we already have quite a few in place, but we have more in the pipeline that we have I'm I'm personally very excited about.

[00:25:25] - [Speaker 0]
Exciting times ahead. A busy year ahead. And what I've also got to say as well, you are you've been a visible leader in the global tech community for some time now. And one of the things that I'm noticing is the more we we implement AI and agents, Agents, Agentsica, and all these different things, we're creating more complex problems which require diverse perspectives to fix. Yeah.

[00:25:46] - [Speaker 0]
So how can the industry create more opportunities for women and underrepresented groups to deliver those diverse perspectives in AI and retail estate technology? And and how does wider representation influence the pace and quality of innovation in this sector, do you think?

[00:26:02] - [Speaker 1]
Neil, this is such a wonderful and deeply important question, and and I really thank you for asking it. It's it's a personal passion for me, and I know that JLR as a company is also very passionate about this topic. To be to be very honest, for a long time, this responsibility of being a visible leader for women and underrepresented groups felt a little bit heavy heavyweight. Right? There's, like, this pressure of being a perfect role model to have all the answers.

[00:26:39] - [Speaker 1]
But over time, I I really have come to see it very differently. I I I see it as a sweet burden where it's actually a privilege for me to be in a position where I can actually at least try to make a difference in however small it might be. Because I I know, like, from my personal experience, like, how it feels like to be on the outside. And even with, like, the similarly success I have, I am very fortunate to have, it's there's a part of me still feels like that ugly duckling, just a little bit different who worries about her quirks, will be seen as flaws. And, you know, like, I have a very long personal journey to really trying to learn to turn that ugly duckling feeling to a source of really sense of purpose and also driving me to really giving back to the community.

[00:27:40] - [Speaker 1]
So you asked, how do we create more opportunities? And then I have two pretty practical steps that I'm trying to practice, and then I hope the listeners that of your show can think about it. I I think it's it goes beyond, oh, I just need to hire a diverse team. I think it goes beyond that. What the first thing is I I I really truly believe we need to change from a passive mentor mentorship to a active sponsorship model for women and underrepresented group.

[00:28:21] - [Speaker 1]
The difference is mentor just would give people advice, they are sitting on the side. A sponsor is really the putting their own reputation on the line, really helping you to advocate and, you know, giving you the right opportunity whether you sit in the room or not. Because a lot of the sponsors sitting in the room that, you know, you are not in, and then they the sponsors can really make a difference in that. The second thing as a leader, I think what I'm trying to do is I I want to make sure that people feel belong. It's it's a really important metric that JLR measure.

[00:29:02] - [Speaker 1]
How do you how how much do you feel like you belong here? Because if if you just hire a diverse team and not really making an environment to make people feel like they can bring their authentic self to work, don't make make them feel belong and where they can have all the quirks and, you know, their own personality, then I think it's all for nothing. Right? So my personal goal as a leader is to help to build those environments where I can actually make people to feel like they belong. And why that's important in in the in the context of AI innovation is technology at its core is is global.

[00:29:49] - [Speaker 1]
It has to be really built for a very diverse group of people with diverse perspectives. A good technology product has to be good for the users that they are serving. So that's why the team that is building that innovation is really important to have the different perspective. Otherwise, there are gonna be a lot of blind spots and then you have a lot of assumptions that, oh, how the user would feel only from your own experience. And having a diverse team can really help to eliminate a lot of these blind spots.

[00:30:33] - [Speaker 1]
The I know there are there are a lot of other benefit for it, and, you know, I'm not going I think we're running out of time, but I'm I'm just I'm absolutely passionate about this topic. I would so like to to just to just end this. It's like this is such a important aspect of being a leader, and I feel, like I said, I feel very fortunate to be at a position where I can do that. And every time I use my position to open a door for someone else, making the path easier for both than it was for me. I really it it fills my heart and it propels me as a leader.

[00:31:24] - [Speaker 1]
And then I want all the other ugly ducklings out there recognize that they are actually swans, and their quirkiness, their unique perspective is not just a it's not a flaw. It's actually their strength. And, you know, I love this. So thank you so much for asking that question, Neil.

[00:31:47] - [Speaker 0]
No. Thank you for finishing this podcast today on an incredibly powerful message and a beautiful message as well, and it's such an important one. So kudos to you for using this to to send this message out there, and I would encourage anybody listening that is inspired by your words out there to contact me or or yourself there and see what we can do together to to write some of these wrongs and celebrate the quirkiness. I'm I'm all for that all day long. And for anyone listening that would like to find out more information about anything we talked about today or connect with you or your team, obviously, JLL is a huge business.

[00:32:23] - [Speaker 0]
So where would you like to point everyone listening?

[00:32:26] - [Speaker 1]
Yeah. You can you can get a lot of our news and insights on jl.com, and then, obviously, you can find me on LinkedIn, Jan Warren, and that's the best way to connect with me.

[00:32:41] - [Speaker 0]
Awesome. Well, I will add all the links to the show notes so people can find you nice and easy. Check out the website if you're interested in finding out more about this AI powered assistant for property teams that sits on top of JLL Falcon. And I would also urge people to check-in with you on LinkedIn, especially on your powerful message. I don't think you realize just how powerful that message is, so a a big call to action for everyone listening there.

[00:33:04] - [Speaker 0]
But thank you for sharing that and your story today. Really appreciate it.

[00:33:08] - [Speaker 1]
Thank Lingko, thank you so much for giving me the opportunity to be here and then give me a platform to talk about all the amazing AI innovations at JLR, and also let me share that leadership message for diversity and inclusion. Thank you so much.

[00:33:25] - [Speaker 0]
I think that was a fascinating look at just how AI is beginning to redefine commercial real estate from the inside out. From property level recommendations to broader strategies around data, performance, and tenant experience. Our conversation today for me highlighted how technology is changing the way spaces are managed and experienced. So if you wanna learn more about that or thinking about the AI road map, please check out the website. You'll find all the relevant links on the show notes, and please connect with my guest if you were impacted by that powerful closing message.

[00:34:00] - [Speaker 0]
And over to you, I'd also love to hear from you too. Are you seeing AI influence the spaces around you? Feel free to share your perspective with me. Techtechtalksnetwork.com. You can get me on LinkedIn, x, Instagram, just at Neil C Hughes.

[00:34:16] - [Speaker 0]
I'll be speaking to you on those platforms, dad. But most importantly, I'll be speaking directly into your ears tomorrow with another guest. See you all then. Bye for now.