From Where I Sit: Episode 12 with Marc Jensen Transcript

Tom McGee:

Welcome to From Where I Sit, I’m your host, Tom McGee, President and CEO of ICSC, the preeminent membership organization serving the commercial real estate and retail industries. Each episode, I’ll be joined by top experts to explore the trends impacting communities and commerce and the spaces where people shop, dine, work, play and gather.

I'm happy to welcome Marc Jensen, Chief Innovation Officer at space150, to the latest episode of From Where I Sit. Marc is an expert in all things augmented reality, virtual reality and artificial intelligence. Marc has more than 20 years of experience at space150 alone, where he is currently focused on identifying new opportunities for the agency and its clients. Adweek named him a top technologist, and he frequently speaks about new technology and innovation at events across the country, including at ICSC's own events.

Marc, thanks for coming on the show. Look forward to our conversation.

Marc Jensen:

Tom, thanks for the invite. I appreciate the time. It's great to be here and great to see you again.

Tom:

It is great. Marc and I have had a chance to meet a number of times and Marc, as I mentioned in the introduction, has spoken at a number of ICSC events so I know this will be a great conversation.

Let's start with space150. Describe for the group what space150 does, the nature of your work and work for clients.

Marc:

Yeah, we're a tech-driven creative agency. We were founded in Minneapolis and now we have people across the country. And our focus is really on helping people understand new technology, the impact it has on society, what it means for them. And we really kind of like to help our companies, you know, our partners that we're working with, see around the corner, know what's coming up, know what it means to them, know how they can basically take advantage of that so that they can win compared to their competitors.

Tom:

And Marc, you've been in the technology industry or around technology for your entire career for many, many years. What drove you to your interest in technology? When people think advertising, they're not necessarily thinking technology. So what drove your interest in technology and then maybe how technology impacts the core advertising industry?

Marc:

Yeah, it's interesting. I didn't come from this industry. I definitely came from a place of technology. My background is mathematics and computer science. And I grew up in Northern kind of rural Minnesota and Minnesota and Apple had a really early connection in the late ‘70s and early ‘80s to get computers in schools. My dad taught geology and he happened to bring a computer home one summer and said, “I need to figure out how to use this thing. Let's unbox it and figure out what this is all about.” And Tom, I remember it like it was yesterday. We unboxed this thing. opened it up and I didn't know what to do. I was kind of staring at this blinking ring cursor. And I just decided to type in a really big number multiplied by a really big number, and I just assumed it wouldn't be able to do that. And I hit enter and it came back immediately with the answer. And at that point, my mind was just blown. And I remember it so vividly. And I just remember at that point, I'm going to figure out everything this could do. And it felt like this time machine into the future. That's really what set me down this path.

Since then, I've seen the desktop computer revolution take place. I saw the desktop internet revolution take place and mobile and kind of mobile internet. And I quickly got onto wanting to understand what changes in technology mean, how they impact society. And that's really been my kind of role at space150.

So what we do is we experiment a lot on ourselves. We figure out what new technology makes possible, and then we kind of deploy those. So we experiment a lot on ourselves and bring that to our clients. And that's really been my goal in the role that I'm in right now.

Tom:

I didn't realize there was that connection between the early days of Apple and the state of Minnesota. I remember Apple in the early days, people used to think of Apple as really the use in academic settings, as not necessarily in commercial settings. That's changed quite a bit over the years.

Marc:

Yeah, and if you're part of the game Oregon Trail—

Tom:

Oh, yeah!

Marc:

—that came out of Minnesota, Minnesota Educational Computing Consortium. So that was one of my early windows into how amazing educational and kind of game experiences can be on computers.

Tom:

Well, you've seen a lot through your career, been at space150 for over 20 years, and have been interested in technology for a lot longer than that. In your view, if you kind of think about all the change that's happened, is there a particular change that you think has had the most profound impact from a technological perspective on society and day-to-day living?

Marc:

Yeah, I've been around long enough where I've seen a number of waves of technology come about. Like I said, the desktop computer revolution. I was in college and grad school during that, you know, Windows, that sort of thing. Saw the internet come up and see it connect us all. And then the mobile internet really kind of connected to everybody on earth. Right? And for knowledge workers right now, a lot of us still have desktop computers or laptop computers, but for the average person on earth, every single person has a mobile phone and are constantly connected. And that to me has absolutely been the biggest impact that I've seen, it's just changed things.

And I remember, and a good way to look at this is, if you think about when mobile phones first came out, specifically the iPhone and Android around that time in 2007, everybody kind of looked at them and said, well, it's not as good as my computer. It's slower, it's more expensive, the screen is smaller. But then you realize it's just so much better in all these other ways. It's always with you. It has a camera, it knows your location, and you can run applications. So I think that was, that's probably the biggest shift I've seen just in how we use computers.

And I think the generative AI era that we're in right now, that has been the most surprising thing I've seen. All these other waves have come up in a certain timeframe, and generative AI is just coming so much faster than anything before. The rate of increase in use is just off the charts when you compare it to previous technologies.

Tom:

It’s interesting when you talk about mobile technology, I recently had an issue with my smartphone. So I was without it for about a 24-hour period. The one died, I had to get another one and I had to download everything from the iCloud, which had some complexities to it. I mean, you really feel like you're kind of useless without that.

Marc:

I'm surprised you're still here, Tom.

Tom:

I mean, it was, I didn't know what to do with myself. I mean, you really felt out of connection with your coworkers, with your family, all those types of things without that phone. It really is amazing how it's become integrated into part of life.

You mentioned AI, augmented reality, and how it's blossomed over the last number of years. Let's talk about the basic level. So, first of all, we're going to talk a little bit about AI. We're going to talk about augmented reality, virtual reality. Describe each of those three things, if you wouldn't mind, and how they differ from each other and how they complement each other.

Marc:

Yeah, absolutely. And the connection between these is really interesting. And that's kind of where I am right now at the intersection of those. So, at the high level, artificial intelligence, the best definition I like is software that does intelligent cognitive tasks. So, anything a person can do. And the surprising thing is that AI is a very wide ranging field. It's been around since just after World War II. So the late 40s, early 50s is when the field started up. And the early field were very simple things. You think about like a calculator, it's very good at doing, you know, basic mathematics that, you know, could be considered artificial intelligence. In the, you know, late 70s, 80s, 90s, there was something called symbolic AI and it was basically artificial intelligence, but people would program every single use case, every single thing that artificial intelligence do. So, it was really kind of manually created and that worked for a certain number of cases, things like credit card fraud is, a classic example of that. You know, if somebody charged something in New York and five minutes later, they charged something in LA, you know it couldn't be the same card. And that was, there were kind of use cases built up around all those, all those possible scenarios. In 2010s, things really changed. And we got into something called machine learning. And that's where a computer is going to analyze a whole bunch of data using something called neural nets that are roughly structured like our brains. And they're able to kind of pull information out of that. And that's when things really started to take off.

And the era that we're in right now, when people say artificial intelligence, they usually mean generative AI. And that's an AI system that can basically generate things. So, it can be text, it can be images, it can be video, that sort of thing. So, when people say AI today, they generally mean generative AI.

And then on augmented reality and virtual reality, I kind of lump those together into something called immersive computing. And virtual reality is something where you put on a headset and right now you don't see the real world at all. You see a completely synthetic environment around you. And it can be used for games and a lot of entertainment purposes, but you can also use it to say, you know, design stores, planogram areas, do things like that. It could be really powerful. And augmented reality is a version of that where you see the real world, but you see an augmented layer on top of that. So, I could picture being at my desk and seeing a virtual monitor, that's called augmented reality.

And what's interesting with AR and VR and the kind of immersive computing space is it's been, you know, I've been in this since, it's been over 10 years now and it's been a real focus of mine. But it's been hard to adopt because we've been missing some things and generative AI is really kind of the unlock that this world needs. So, we can talk more about that, but I think the intersection of these two things is really interesting.

Tom:

Going back to AI in everyday life. Are there are examples where people are using artificial intelligence and don't even realize that it's supplementing the task at hand? I mean, day-to-day tasks that you can think of, whether it's something on your smartphone or some other daily chore or aspect of life where AI is integrated and we don't really even realize?

Marc:

I love that you brought that up, Tom. That's such a good example of, it's kind of been invisible in the background for a long time. So, if you think about even simple things like spell checking or auto correct, or, you know, sentence completion, that's all artificial intelligence. And there's this real paradox in AI that the minute something is solved, we stop calling it artificial intelligence and we just call it software. So that's kind of a joke in the industry, but you'll notice all these little things appearing. Say you take a photo of a plant with your phone, you can swipe up on most phones and they'll tell you what type of plant that is. And that's artificial intelligence in the background analyzing your photo because it's seen a photo of everything in the world and it kind of knows what that is. So, I use that all the time and that's a good example of it's just kind of built in and becoming more ambient.

Tom:

So, I am admittedly not well-versed in technology. I'm a real novice in it, but I'm fascinated by it. I'm sure a lot of our listeners are like that. A lot of people are like that. They use it, but they're not necessarily well-versed in all the different aspects of it. What are two or three things that somebody like me should get up to speed on to really help advance your understanding of where technology is and where it's going?

Marc:

I'm a big believer in using it for yourself to help understand what this means to you. So in the AI space, what I would say is I would recommend if you haven't tried one of the chatbots, one of the LLMs, I would say download and try OpenAI, do a paid plan, they're $20 a month and you'll get access to everything and then you'll be able to control where the information you upload gets used. So, I would recommend that first. And what I've found is AI can be daunting. You can see these headlines and it can say it's going to take over and destroy our jobs and destroy the world. And you can, you can hear all these real sensationalist headlines, but in the end it becomes a lot more approachable when you personally experiment with it. So, my recommendation is to download and try it. That's a good one to start with. That's what I would recommend.

And there's a few ways to get started. One is if you ask a question about something you know a lot about, then you'll get an answer back. So, you can use it to kind of gauge how good it is. And I've mentioned this before in some of my presentations, but if you ask a real simple question, you'll typically get back a real simple answer. But if you ask a really complex, nuanced, detailed question, you'll get an answer back that kind of matches that. So, AI kind of matches you there. And a lot of times, people think about generative AI as being chatbots that you communicate with, but there are other things you can do. Increasingly, AI is what's called multimodal. So, you can take a photo of something and ask what this is. You can turn on video and have a conversation. I think the conversation one is really interesting to me.

So, if you picture going to visit a client, you've got maybe a half hour drive in front of you, you can just start a conversation with AI and ask about them and get background, get history and have this conversation. I think you've tried that too, Tom, you mentioned. I think that's a really good example of, it's something most people just don't know exists. And when you try and show it to somebody, it immediately becomes part of their kind of tool set that they use.

Tom:

I did do that after you and I were together about a year ago, you presented to our board and I went and played around with tools like you just said. At that point in time, I was fascinated by Irish history and Irish immigration into the United States because I'm of Irish heritage. And so I had a pretty detailed conversation around Irish history, Irish immigration to the States, what prompted it, what the different stages of immigration. I was fascinated because you can ask follow-up questions and get more detailed and nuanced answers.

You made the reference to headlines and actually timing is everything. Right before I came on, I was on CNBC and I saw a headline that Perplexity is an AI tool. They're out raising capital now at like a $14 billion valuation. And I'm going to presume that there's going to be a lot of additional news around that because it was a major headline. What is Perplexity? What do they do and how do they fit in the world? What's their role?

Marc:

Yeah, they're doing something really interesting. So, for the last, I would say 25 years, the business model of the internet has been you open a browser and start with Google typically, and you search for something that you're looking for and you end up either getting a link, you know, 10 blue links to it, that sort of thing. And then it's up to you to kind of follow the right one, find the answers. And what you'll notice in Google search to kind of map this out really clearly, if you do a Google search now, you'll often see an AI summary.

So, what it's doing is it's basically trying to answer the question for you so that you don't have to follow those links, but you're just going to get the answer. And Perplexity kind of bills themselves as an answer engine. So what they'll do is they'll go out and do the research for you and come back with an answer. I use it all the time for quick research. If I want to know something about a specific company or a specific product, I'll go and ask it there and you typically get a really good answer back. And the interesting thing, and I think they're trying to basically be the Google replacement. I think a lot of people see that the world is changing. And I think this could ultimately upend the kind of the business model of the web. It is changing for sure. They've also added shopping capabilities. So, you can say, I'm looking for this specific product. And then what they'll do is they'll go out and kind of do research for you and come back and say, these are what we recommend. And for some of the products, you can buy them right within the app. So, they're really trying to kind of close that loop.

Tom:

It moves so quickly, the advancement. It's crazy. One other basic question, because I had also read briefly about this, but I'm not sure that I am in command of the differences. the phrase is “agenic” AI, I think?

Marc:

Agentic AI, yes.

Tom:

How does that differ from generative AI?

Marc:

So this is a pretty incredible thing and this is something I would say I would definitely recommend experimenting with. If you're used to using any of the modern AI tools, you're often conversing with them. Let's just take the text example. You're typing something, you're getting an answer back, you're typing something back, you're getting another answer back. So, it's kind of like using chat or instant message, right? And what agentic AI is, it's basically that, but you give it more clear direction upfront and then it basically operates on your behalf.

So, a good example of that is I was going down to speak at ICSC+OAC in March. And I wanted to know a bit about all the companies that were on the board. And what I did is I said, I'm going down to speak at this event. And I gave it a link to the OAC page. And I said, can you look up all the companies that are represented on the board of ICSC, do research on all of them, and then give me the common kind of opportunities and threats that they have in front of them? And what was really interesting is it goes off, typically it asks a few clarifying questions before it starts, and it will go off and do its work for between five and say 30 minutes. Typically, I find it to be 15 or 20 minutes. It went through and did all of that and it came back with results. And Tom, what's amazing is it really mirrored what I saw at the Board of Trustees meeting a year ago. So that's just such a good example of, picture having a research assistant with you all the time that you can set down a path and do that. This to me is the coolest thing I've seen in AI probably since the introduction of ChatGPT originally.

Tom:

Is Perplexity that? There sounds like there's some similarity there in regards to, it's kind of answering or solving a problem for you.

Marc:

Yeah, it is. It's similar. I think Perplexity is meant to be kind of a quicker hit, get you an answer right away. And ChatGPT's version of this in the paid plans is called Deep Research and it's really kind of meant to go deep. So, it's basically how much time it'll spend doing that. It's incredible. And I would say definitely try that. And you could even say a competitive audit of these companies or, you know, another thing you can do is say you're looking to lease some retail land and you have two or three different people looking at it, could do research on all three of them and find out which companies may be the healthiest. Look at the last three years of reports like financials and tell me which one you think would be the best one to lease to, for instance.

Tom:

If that's where—makes sense—that AI is going in that direction. You can see how it could be quite disruptive to professional services, consulting, legal, even financial analysis, that type of stuff. You can let your mind wander a little bit in regards to all that. But we're here on our commercial real estate focused show. And so, I wanted to talk a little bit about commercial real estate, retail, retail real estate specifically. First of all, how do you perceive AI right now, its implications for, let's just use retail. Where are we at in that? What are some of the typical use cases right now?

Marc:

Yeah, I would say, and this holds for everything we're going to talk about today. We're only about two and a half years into this kind of LLM era that we're in. So, it is still very early days. And if you remember back to, I like using mobile as kind of a frame of reference or a lens to look back on. When mobile phones first came out, we knew they were going to allow and enable different things, but we didn't exactly know what the best use cases were. So, what we're seeing is like, we're still in early days here and people are doing a lot of experimenting. And one thing I'll say is that when new technologies come out, what we do is we tend to use them to do the same things in new ways. So, we'll tack on AI to something. So, if you think about Google and Gmail, for instance, now they have little, you know, rewrite my email with AI. So that's good. It's a nice addition. It helps, but it's not a revolutionary thing. So, with that said though, there are some really interesting products being launched.

If I end up at, say, a home improvement store, Tom, something has gone wrong with my day and I'm not, that's not my wheelhouse. I'm more of a computer guy, right? And I really lean on like someone there in the store, like, Hey, I need to solve this problem. What do I need to do here? And sometimes you find the person that's an expert and that's amazing, but oftentimes you don't. Lowe's has launched something called Mylow and it's basically a play on “my Lowe’s.” And basically, what they have is they've built, in partnership with OpenAI and ChatGPT, a version that's basically trained in all the information they have. So, you can ask them questions about something. It'll get back to you really quickly using this. And they've also launched a version for their associates. So, say, you know, and some associate may be an expert in plumbing, but not in flooring. This will basically give them and kind of fuel them with all that information. I think that's a really good example.

Another example to me that's really interesting too, is that combination of deep research and product recommendation. So if you think about retail, going to a physical store, it still really does either start with your experience with that store in the past, or maybe you do a Google search to say, I'm looking for something, where can I find that nearby? So, another great example is I wanted to buy my sister a specific coffee mug for her birthday. I'd maybe waited a little bit too long between you and me and I guess the listeners of this podcast to go buy it. So, I used Deep Research and I said, want this coffee mug, I want to be able to pick it up locally in the Minneapolis area, find me where I can buy this. And what's really interesting is it didn't just go to the big retailers because they can ship it to me, but it went deeper and it looked for places that said, yes, we have these in stock. And I thought what was really interesting about that is it said, here's a couple of retailers that will likely have it in stock near you. Here are also some small coffee shops that would have personalized versions of the mug at the same price, but with their logos or their designs on them. And I actually bought one of those and I thought that was a really interesting way to send me to a place I wouldn't have known to go to that. So that's an interesting kind of foot traffic change for sure.

Tom:

It takes informing a customer, but also customer engagement to a whole different level. I mean, with that kind of information, you mentioned home improvement. The thing that I find myself doing—I'm like you, I'm not all that handy around the house, but there's things you need to do. And I go to YouTube a lot and look up what I need to do and find videos of somebody else doing it. So, I learned how to do it.

Marc:

Same. Isn't that just amazing?

Tom:

Yeah, it really is. It's quite helpful.

Are there risks a brand should be thinking about? If you think about the use of AI, the examples you've described are helpful and increase engagement and traffic, but are there risks associated with using AI in a retail setting?

Marc:

I think there's risks and rewards. So, if you think about the early days of the internet, you remember when retailers, brick and mortar retailers, specifically maybe before the web came up, they were really concerned that people would have smartphones in their store and could do real-time price comparison. And now that's just the world we live in, right? There's transparency across the board. So, when I think about risks as a retailer, what I would say is there are risks that you don't leverage AI. So, what we see is companies need to have a kind of stance on how they want to deploy AI at their company. So, at a minimum, it could just make your company more efficient. So, one example would be if your employees can spend less time doing things that are the work they have to do, they could spend more time doing the work they want to do, and that really makes a difference. And if you're not doing that and your competitor is, they're just going to be able to service you better. Like, that's just flat out there.

One example I would say for us is we recently posted a job for a new software engineer we wanted, and we want it to be local to Minneapolis area. We got 1,300 applications for one job. So how do you sort through those? We have an HR platform, which is powered by AI, which helps us distill it down to the top picks that meet a certain amount of the criteria. And at that point, it becomes manageable. So, what that allows us to do is we don't have to have someone else working in HR. We can put those people into more direct staff, you know, that do work for our clients.

So, at a minimum, I think that's an interesting way to look at it. If your organization could be more efficient, where do you deploy that extra energy? And a lot of that could be in making the customer service or customer experience better.

Tom:

You mentioned being more efficient and you understand our membership base in our industry by virtue of participating in a number of ICSC events. Let's talk a little bit about the real estate side of the equation a little bit and the use of AI both in managing properties, developing properties, leasing properties. Any observations in that regard?

Marc:

Definitely, you know, one thing that we've been, I found that we've used a lot that translates really well to that is think about leasing documents specifically. Those are big challenging documents. And when we've done them, you know, we have a lot of time spent with lawyers working through those. And there's a company real interesting to me, and I can't speak to how good it is in particular, but it's called Prophia. And what they do is you upload leasing documents to their service and what it does, it analyzes a few hundred different data points in any given lease. So what you can do is you can upload two different leases, say in two different formats completely, and it allows you to kind of do an apples to apples comparison. I think that's a no brainer. And if you think about all the time spent doing that, that's just going to free you up to do other things. And we've done that a lot too. We've also noticed, say, can you compare these two versions of the documents together? And it may spot something that wasn't redlined, but should have been. Nothing meant to happen intentionally, but like, those things do happen.

Tom:

I remember when you were at our board meeting, Marc, you also showed an example of a vacant storefront and modeled it out in different designs, different uses. It kind of blew my mind when you showed it because you took this vacant space and you showed all these different utilizations of it. It would seem to me like that could be quite profound.

Marc:

Yes, that's a good example, I think, Tom, of the general tools. So, say you have a year ago, if you were using something like any of the major AI tools, none of them would really do that well. So, we were using a more focused tool and the example I showed there was basically showing a deserted store being re-envisioned as something new. And that's the kind of thing that can take people a lot of time. So, if you're out, talking to someone about leasing this space, rather than having to go back to a team and have them model it or do Photoshop or do that kind of stuff, it's literally the kind of thing you can do on your phone right now. Take a photo, describe what you think, like envision this as a copy shop or envision this as a grocery store and you can see that. And that was about a year ago, Tom, and that was just kind of becoming possible and in a really cool way. And what's happened in the last few months is OpenAI released something called their image model 4.0. And now what you can do is you can just upload an image to ChatGPT and say, can you envision this as whatever you want to be envisioned as? And it will do that. And I'll say it's not quite as good as the kind of focus tools, but it's getting there and it's going to get there. And I think that's really amazing. You're right. It's a no-brainer use case.

And I think another way of how that's going to impact online and offline retail is—I did this in my living room. I took a photo of my living room and I've got one area that's kind of empty and I want to put a floor lamp there. So, I said, can you, I said, this is a photo of my living room. Can you analyze my aesthetic here and recommend the lamp that fits in the corner and that would fit in with what I have, also be kind of interesting? And then it came back with three questions and said, you know, what type of bulb do you want? Is there any other requirements you have? And I said, you know, answered the questions. And it went off and found some, and it gave me the top three recommendations. I asked for the top three, didn't want 20. I didn't want one. I wanted a little bit of choice there. They were all really good. And the one I actually picked, I said, now can you create an image of my living room with this lamp in it? Just think about that. That's the idea of kind of a virtual store. So, it's like a personal, you know, home stylist and it's recommending it. It's showing me where I can buy it and I can envision it there. That's just something that was not possible before. And just think about the change that that could bring.

Tom:

Well, it's huge. And it brings up another topic. And we often talk about omnichannel retail, the convergence and the integration of the digital and physical world. And stores really being a billboard for a retailer's brand, creates a sense of awareness. It's a very effective way to market and drives both traffic in the store and online. The use of AI and that convergence of the digital and physical world, how could AI be used to, one, help drive more traffic to stores on one hand, but also grow your e-commerce platform on the other?

Marc:

I think there's a number of ways that could happen. That example I just shared, that right now is possible, but it's on me to do that. So, if I was a retailer, I would be building that tool into my app right now. So, I bet you've gone to an app where you can see a chair, you can see a coffee maker, and you can kind of view this in your space. But this takes it to the next level where you can say what chair would fit here. I think that's an interesting way to drive someone to you. And I always feel that the people that have the best tools are the ones people gravitate to and then they get used more. So, I think that's where being a first mover or being there before your competition kind of sets you up as the place people go to there. That's a really good example.

Tom:

You go in with a problem and you show a picture and it offers a solution to it. Talk about engaging with your customer. And great customer service. It’s that classic rule of retailing, good merchandising, great customer service and good price still always win, you're using technology to help.

Marc:

Absolutely. And one thing I think that is really interesting, if you look at, say, we've done some work for, say, very high end retailers, right, where they do the individuals, they have a transaction history of everything they've purchased. And it's kind of that more bespoke shopping experience. I think what we're going to see is artificial intelligence is going to enable things to come down to the next tier of stores, where a picture someone has never met this customer before, but they have a log of everything they've ever purchased. And you could ask genAI to basically say based on what we have in store right now, the sizes they buy, the styles they typically buy, what would you recommend? I think that's something that was previously not scalable at a certain level, but now that may be. And a lot of times those recommendations are okay based on people that bought this also bought this, but then you could start to ask interesting questions. What did I buy five years ago? What did I buy this year? What would kind of be the natural evolution of that I think is interesting for sure.

Tom:

I would imagine there's a generational aspect to this as well. First of all, the comfort level around technology. And my presumption is that, and certainly the surveys we've done have supported this. There's some things that may on the surface not seem logical. For example, Gen Z and younger consumers who are the most adept at technology and enjoy technology, they like to shop in store the most too. And I'm going to guess that your research has also supported that the younger generations, millennials, Gen Zs are probably more comfortable with AI than the Boomers are or Gen Xs.

Marc:

Absolutely. think it skews, I would say it skews younger. And I'm glad you asked this question because this is an interesting one. And if you think about the people that were born after 2000, we generally call them digital natives because they don't know a world without computers or the internet. And people that are, say, in high school now, or roughly that age, they're going to basically be AI natives. And I think any young person entering the workforce now, they're not just going to be open to the idea of using artificial intelligence, they're using it in school right now. And they can't imagine going to a place where you couldn't use that. So, it's really a divide there. And as a company, you have to think, how do you attract those people? Sometimes it can be a challenge to attract people to work for a company. If they start and it feels like it's 10 years behind what they're used to, that's not good.

Tom:

I was recently listening to a podcast on an unrelated topic, but the guest was someone who understood AI, had a view on AI. And they were asked what they thought five years from now, some of the common applications of AI would be. And one of them, to your point around younger generations and using it as school, they had proffered that all students will have kind of their own personal tutor, that AI will be their personal tutor. They'll learn how they learn and that they'll be available to them to help them with their math homework and help them with writing their essay. Not doing it for them, but helping them.

Marc:

Yes, and I'm personally a lifelong learner. So, I think if you're using AI to do the assignment for you, you're not going to learn much. And a lot of going to college, Tom, is like learning how to learn. But if you are a lifelong learner, want to learn something new, there's never been an excuse, but now there's no excuse. There's so much at your fingertips. And I think again, like, you know, we're in earlier days and what you're starting to see right now is AI being applied to things that exist. But what I'm really excited about is the next generation of founders and people creating companies and products are going to be created with the assumption that generative AI is a thing. And that's just a baseline assumption. And that's new and that's where this really gets interesting.

Tom:

So, let's talk about the folks that are quite concerned around AI right now. And I was at a non-ICSC conference and AI was a topic on the agenda. And I got in a conversation with someone who was convinced that we are going to enter into a phase where massive unemployment, loss of jobs, painted a very dark vision of the future because technology is going to kind of take over and you're going to have a massive wealth gap. I know it's going to be disruptive, but do you see AI dislocating thousands and thousands and millions of jobs and massive unemployment? Or do you think that will just kind of evolve and there'll be new jobs that are created for millions?

Marc:

History would show us that new jobs exist when new platforms get rolled out. I think about—social media influencer wasn't a job 10 years ago and now it's a career for many people. I do think AI might be slightly different though. And I'll say this, nobody can tell you exactly where this is going to go, but I will say there is going to be profound change. And one of the things that companies, government, society has to do is when change happens, it's re-skilling people and being prepared for that.

And it's interesting, Tom, I get a lot of those same questions and what people say like, it can't we just put this on pause? Is there any way to stop this? And there is no way to stop the future from happening. It's going to happen. We know that. And I think the more we understand what that change will be like the sooner, the more we can prepare for that. We haven't typically done a very good job of that. Here you think about the traditional automation work that's happened in robotics. A lot of those jobs have gone away and we weren't the best at kind of helping those people find new jobs.

Now it's coming for a different type of worker, the knowledge worker, the white-collar worker. And these people are now realizing it's kind of coming for their jobs. So, there will be efficiency gains. And I think at a high level, any company can look at this and say, okay, if my whole workforce is more efficient, say just at a minimum, I could do the same with less people. I think the people that are going to win are going to look at that and say, I now have 30% or 40% more bandwidth with the same team size I had before. What can I do with that? And I think that's, those are the companies that usually lead rather than the companies that kind of cut back and just take the efficiency gain.

Tom:

You can paint different pictures of the future. I tend to agree with you. The winners usually figure out how to take that extra capacity and do something new or different with it.

Marc:

Absolutely.

Tom:

Before we leave, are there things that we're underestimating about AI? There's a lot of conversation, a lot of attention placed on it, but even in this conversation, we scratched the surface of some new things that I don't think everybody was aware of. Are we underestimating its impact? Are there certain things that we as everyday Americans don't realize that are going to profoundly change in the next five to 10 years because of AI?

Marc:

You know, five years is a long time. We've only been with the LLMs about two and a half years. So, I hate to make two bigger predictions. And even some of the AI companies, the founders are saying they're not predicting anything more than six months ahead because of how much things change. But I will say there's this quote I do like, and I've used it in presentations, but you know, we overestimate the short-term impact and underestimate the long-term impact. And that's often attributed to Bill Gates, but it's Roy Amara. He made that quote in 2006. And I think what that gets at is you can see what's going to happen tomorrow. I can tell you next week or next month, you know, the changes that are going to be, but it's those second and third level, you know, kind of impacts that are just impossible to predict.

A good example of that kind of close to you would be, you know, the interstate freeway system after World War II, that enabled the creation of suburbs and malls and shopping and things like that. But it wasn't obvious looking forward that that was going to happen when you look back and go, you know, of course that makes sense. So that's what I try to do is I try to think about you know, not only, you know, what can we gain in terms of efficiency, but, what is possible now that you couldn't do before. And that's such a powerful example. And when you start to think about what are the parts of our business that we've maybe tried to solve in the past, tried to come at a different way and just weren't possible. That's what I think is so interesting with genAI is computers are now good at things they've traditionally been very bad at. And if you look at it through, you know, we've tried that we can't solve it. It's impossible. You'll never get anywhere.

So that's where I think you have to balance this kind of, I would say, you know, experience and age. You know, you're very good at what you do, but you're kind of set in a way of doing things. And that's where I think having that blend of people that either are young at heart or think young or just are young and aren't tied into a specific way of doing things. And they tend to be the most adept at figuring out how to do their job in a new way.

Tom:

So true when you talk about the current future versus farther into the future and you think of what we started with, mobile technology, the smartphone, the networks really as a result of just the internet. And when we were talking in 1996 or 1997 and the internet was emerging at that time, I don't think we all thought we were going to be walking around with smartphones and apps and social media and all those types of things. But today it kind of makes sense because we're connected, which is what the internet does. And so I think you're right when you look back, whatever it is, 10 years from now, there's going to be some things that we're doing in our everyday life that make a lot of sense because of artificial intelligence, but we couldn't anticipate what they're going to be.

Marc:

Absolutely. Yep. And I think if you look back, mobile is such a good lens for this, Tom, because you can think about when everyone has a smartphone that knows their connection can run apps, all these businesses, right? Think about Uber, it wasn't possible without mobile phones. All these businesses, DoorDash, they were enabled by this. And it's those generation of businesses kind of built on artificial intelligence or people that reinvent themselves using artificial intelligence. I think that's going to be the really fun stuff to watch over the next, say, five years.

Tom:

Yes, I think Uber and DoorDash are two great examples. They're so integrated in our day-to-day lives. Back to that personal experience I had where I was without my phone for 24 hours. I couldn't use any of those things and I was completely locked.

Marc:

You were living like someone from the 1900s.

Tom:

Yeah, I felt that way, but it was really not that long ago. I grew up that way, but I felt lost. So, speaking about the future, you know, looking a few years into the future, let's say in retail and real estate, how would you hope that they leverage AI? Maybe we don't know exactly how they will, but what are some of the things that you would hope that the industry leans into as it relates to artificial intelligence?

Marc:

Yeah, I think my recommendation there is a lot of companies will look at something and I think the bigger companies tend to do this. They'll look at something and go, there's a lot of risk here. Let's just not expose ourselves to any risk. So, I think companies really should reflect themselves and say, yes, there's a risk, but yes, there's also a reward. And we're working with some very large companies. I would say they've taken very progressive use in artificial intelligence. And what will happen is there's no, you know, do this and you'll succeed. That doesn't exist right now. So, I really do think it requires experimenting with new technology and as a leader at a company that means enabling your team to experiment. We're about 100 people so it's easy for us to do this at our company but we have a stipend where we let people use new tools to try them out—again carefully, without, you know, don't ever upload kind of private information—and a lot of times what you do in your personal life and how you understand how AI works will map very well to your business life so we support that.

We have weekly meetings, we have an AI channel in Slack where we all kind of communicate. But I think it's really about experimenting and the people that are doing a job are typically the best people to understand how AI could help do that job. So, I think it's a top-down permission to do this, but a bottom-up kind of way of understanding how it's really going to impact you. So, it really is a combination of those two things. And we've seen that it's not top-down typically that comes up with the best solutions. It's people doing the job and they can be people at anywhere in the organization at any level.

Tom:

That's great counsel. And so many of the tools are so accessible and affordable right now. So, Marc, any final comments for the audience around AI or the topics we covered?

Marc:

Yeah, I would say again, my call to action is if you're not using this and you've been hesitant at all, just start and Tom, I think you spoke from it, but you know, I spoke at ICSC CENTERBUILD in 2023 and then 2024 and I saw a lot of the same people and my first year the call to action was don't be afraid, start, do these things, experiment on something that you know. And the number of people that came up to me and said, I just needed that little push to kind of start. And then you can find out how it in your life. And I think it's just going to be incredible. And one thing I'm really particularly interested about is the immersive computing front. So this year we're going to get next generation glasses from Meta and from Google and Samsung. And they're going to have AI built into them, which some of them do already, but you'll be able to kind of ask questions, just have it ambiently on you. And what I found, Tom, is that I keep my phone in my pocket. I use my glasses more because when you've just got it there all the time, that to me is really amazing. So, we're going to see new things become unlocked that just weren't possible before. That's the part I'm most excited about. And at space150, we say tomorrow will be different. And thanks to generative AI, there's, it is going to be so different. We won't recognize it looking back for sure.

Tom:

We didn't touch on immersive technology in that way, but the applications that are out there, the hardware that's out there, and it's only going to get better and better. That's the one lesson we've learned in technology is that it gets more and more powerful and easier to use and glasses will somehow become a lapel pen at some point in the future or something of that nature.

Marc:

Absolutely, and I don't wear glasses. Thankfully, I haven't needed them yet, but I wear these all the time and I have them on me and it's been so useful. And to me, you it's not the end game where we are right now, but it shows you a step along the way. And just like the early mobile phones were maybe a little slow, a little expensive, a little low resolution, time will take care of all that and they'll just get better and better. So, it's a good window into the future if it's not just the future yet.

Tom:

Marc, thank you. It's been a pleasure to talk to you. I tried to cover a lot of ground and appreciate you going with it.

Marc:

Thanks for the invite. really enjoyed the conversation. Tom, good to see you.

Tom:

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