Welcome. I'm Mark Bonner, Business Now's editor-in-chief, coming to you live from New York. It's Friday, October 24th. Well, JLL has been on quite the tear this year. In Q1, the firm pulled in about $5.7 billion in revenue, up roughly 13% from last year, and profits climbed nearly 30%. Then in Q2, revenues pushed past 6 billion, up another 10% with earnings per share jumping close to 30% again. In a market still grinding under high rates and slow deal flow, those are rare numbers these days, and all eyes are on JLL's next earnings release coming in a little more than a week on November 5th. But the story behind those numbers isn't just another strong quarter. It's about a company rewiring how CRE is actually operating. While most of the industry is still testing AI, JLL is already scaling it. Its enterprise platform, Falcon, sits on top of decades of proprietary real estate data, turning lease terms, valuations, and forecasts into real-time insight. JLL GPT gives employees generative tools that cut work cycles from weeks to hours. Azera helps clients model space and cost in minutes. And the new property assistant lets landlords ask, 'When's my NOI dropping?' and then they get the answer immediately. It's not a pilot. It's a platform. And it's quietly redefining what it means to be a brokerage, an advisor, and a data company all at once. So today, we're asking, how far can JLL push this transformation? And what does it say about where commercial real estate is heading next? To unpack it, we're joined by the man himself who's driving that shift, coming to us live from Frankfurt, Germany, JLL CEO Christian Ulbrich. Christian, welcome to First Draft Live.
Mark, thank you. What a brilliant introduction. That was very kind of you.
So, let's talk about Falcon. That's become the center of JLL's AI play. Built for commercial real estate and fueled by decades of deal and property data. As we just discussed, it powers tools like JLL GPT, Azera, and the new property assistant. But Christian, give us the quick version here. What exactly is Falcon and what is it doing inside JLL today?
Well, as it says, Falcon is a platform and so that's kind of the back of the house for all our AI tools. It pulls the data in and then it distributes the data to the different applications we have, and the number of applications are growing as we speak. And therefore it is important that you have the framework, the house around it, and that's what Falcon is.
But can you walk me through the system and how it actually works? What does a user have to put into it and then how quickly can it get something out of it to make a real difference in their workflow?
Well, as you know, AI is based on accurate data. So, the story started with us kind of creating a really thorough data platform where all what we do is kind of finding its home. We work very much on the accuracy of that. That is the biggest enemy. And then we pull that data into that platform and then we distribute it out to whatever application we are running. And so the people will only see the application they are using. They don't have to do anything else than using an application like they use any other software. But behind that, that is all hosted under the JLL Falcon platform.
So where are you seeing the first real wins? Leasing, valuations, portfolio planning?
Well, you see wins pretty much across the board. What is probably fair to say that in most organizations who are fully embracing AI, the focus sits on productivity gains. So we are making the life of our colleagues easier because work which they had to do in the past kind of manually and pull the data together, this is now done by an agent. And so we are giving them literally time back. And it's moving from there now much more into client-facing tools. You mentioned some of them in your intro that we now have already tools which our clients are using which is making their life easier. And that's kind of the usual journey which you will see probably across many very large organizations.
So, let's get into the efficiencies that are created by this in a second, but you mentioned accuracy, right? That's critically important. You know, I mean, we've all read or experienced ourselves that AI hallucinates. Maybe it's 90% accurate, but that 10% can represent a huge pitfall if you're not in control of it. How do you guys navigate that from a policy perspective internally in terms of how to trust or to verify what the AI gives back to your workforce?
Yeah, I mean that is a great point because people sometimes think AI will immediately take over instead of the humans. It's the combination. It empowers people but they still have to kind of continue what humans are good at and that is to be critical, to ask questions. And so when you get a response from AI you have to look at that response and see does that really make sense? And I guess we all have played around with different systems in our private lives that sometimes you are amazed about the accuracy of the response and sometimes you look at the response and you know well that's not quite true. And so that is why it's so important that the proprietary data which we have within JLL in the system is as accurate as possible because then that helps obviously our people to build that trust into the systems.
Got it. So you know inside JLL, we're going to get to the efficiency part of this. I know it's cutting cycle times to almost zero. Tasks that took weeks or months now are taking days if not hours. Document review is probably a place where this is really helping your teams. Client reporting, all of it is happening in real time faster than ever probably in your career, Christian, not to put words in your mouth, but you mentioned the time that it's giving back to your workforce. What do people do with that extra time?
Well, hopefully the most important thing they do is that they have more client contact. They spend more time interacting with our clients and that is what we want for various reasons here. First of all, it's always great when they speak to clients, but they have more to talk to the client about because they are based with a lot of facts, data-driven facts which provide insights and that insights makes our clients much more successful. So our people have to bring that information to our clients.
So have you seen that play out in the real world? Like has that actually occurred with your employees? Are they doing that? And what have the outcomes been? Stronger because they have more client contact?
Oh, absolutely. Absolutely. I mean, we see that the productivity they are gaining is turning into higher revenue per head. It's turning into higher success rates when they are pitching. It's turning into faster closings. We have now 56% of the bidders which are generated from our AI tools are the ones who are closing the deal on the capital markets side. So we have tremendous amounts of KPI which are proving the value of the tools and so that's why everything is now going at that very rapid speed level because it's in your face the benefits for your clients when you embrace AI.
Look, I mean, this is obviously a deep competitive advantage that you all have, right? One of the giants of commercial real estate globally. There's probably going to be a lot of people who listen to this conversation who don't work at one of those giants. There may be a middle market firm or a small local firm somewhere in the United States or in Europe or Asia, and they're thinking, 'How can I keep up? How can I realistically compete with the JLLs of the world who are able to pull this off for their teams?' I mean, what would your advice be, Christian, to the majority of the commercial real estate industry, especially in the United States, which is more middle market, and are trying to figure out a way what can we learn from the big boys, if you will, and how can we apply that for our small 50 to 100 person unit somewhere in the Midwest of the United States, for instance.
Well, first of all, what type of companies are we talking about in the real estate industry? If you talk about small investors or those type of developers, those type of companies, they can easily partner with us or with others who have the data in house and we are very happy to help them to be successful as our clients. If you talk about smaller competitors to us, I don't necessarily think there's a question around whether you are big or small because there are advantages of being small because you can move faster. It's probably easier to convince your teammates how important it is to embrace AI in a smaller outfit than in a larger outfit. But the disadvantage is access to data. I think that is for us the biggest advantage, the amount of proprietary data which we are obviously complementing with publicly available data. Now, a smaller outfit doesn't have that much proprietary data, but there's still a lot of data out in the public, so they can still have the opportunity to use AI effectively.
But is part of the answer, okay, but part of the answer is they should work with JLL.
Well, others will probably do the same what we do. I don't think what we do is totally unique. Maybe we went on that journey a bit early but this is nothing which will where you have forever a competitive advantage because everybody will embrace AI otherwise they will be out of business relatively soon.
So the other big thing that's out there is something that everyone's talking about, agentic AI, which basically means systems that don't just answer questions but actually take action independently. You're building that into Falcon. A lot of other of your competitors are as well. What does the general commercial real estate public make of that? How close are we to AI running full workflows inside CRE or even at JLL?
Well, I would say the whole development is in comparison to previous innovations we have seen at lightning speed level and people shouldn't make the mistake that they think AI is just for the simple task. I would say it's the opposite. AI is starting to prove, agentic AI is starting to prove that the most complex tasks are actually the one where you have the biggest advantage because with that operational complexity, AI can really drive additional value. And so you can almost think about the most complex property types will create the biggest kind of value when you apply agentic AI and that's now in the development but it goes really outrageously fast.
