How AI and Energy Data Are Transforming Commercial Real Estate Performance

Introduction to AI and Energy in Real Estate

Drew: Welcome back to the Peak Property Performance Podcast. It's me, your host, Drew Hall. Hosting together, I'm here with Bill Douglas.

Bill: Bill, welcome back. Good to see you, Drew. Good to have another recording underway. And before we get started, everybody, don't forget to like, promote, share, all that other stuff. We're always trying to get more followers because it gets the conversation elevated across the industry. So rather than say that last, I thought I'd say it first this time.

Drew: Nice. I like it. Yeah. For those holdouts that don't wait till the end. Now they know what we say back there. Yeah. Well, tell everybody what the theme is today, and then I'll get to introducing our guest, Michael Ansamo.

Bill: Yeah. Today, we're going to talk about energy, data, artificial intelligence, the new performance engine for commercial real estate.

Drew: All right. Today's guest is Michael Ansamo, a cross-disciplinary sales executive working at the intersection of emerging technology, sustainability, and the built environment. Michael combines the technical fluency with commercial strategy shaped by years helping scale innovative platforms. That goes from early stage ventures to IBM's Invisi team. So his work focuses on turning messy, unstructured building data into automation, decarbonization, and measuring measurable ROI across Fortune 500 campuses, higher ed, healthcare, and industrial portfolios. Deeply rooted in sustainability, Michael helps organizations improve resource efficiency, hit carbon targets, and turn compliance pressure into competitive advantages. So Michael, welcome to the show. Glad to have you.

Michael Ansamo: Great. Thanks, Bill. Thanks, Drew. I appreciate you having me on. I'm excited to have our conversation today.

Challenges in Utility Data Access and Management

Bill: Absolutely. Yeah. That intro is amazing. I'm just like, man, this guy has been busy. All right. So let's slide into some topics here. When we think about data, I mean, we know that all this is so central. Data is so central to everything, right? It's driving everything that we talk about, basically. Most commercial real estate portfolios think that they have energy data, but there's often a big gap. They don't actually have usable intelligence. Talk about the most common gaps where you see that. How prevalent is that reality?

Michael Ansamo: Yeah, Drew. It continues to amaze me, the state of a lot of folks' data. There's folks that still don't have access to utility bills. They're having a really hard time just getting the utility bill data, not from just a single building, but their entire portfolio, because it's buried with whoever's getting the bills, has access to it, or within the finance department. And then when you start to look at other things, like sub-metering, BMS systems, lighting control systems, they're really scattered, disparate, and a lot of teams are still working within spreadsheets, and that makes it really challenging to access and drive the data, let alone start to do really intelligent things with it. So a lot of times, these teams, the first thing they need to do is try to lift up, build better processes around their data, accessing it, and that's even before they start to really be able to fully aggregate it into a central depository. We see it across all different levels, and that's really one of the things that I always try to focus on and really understand is, where are our clients with their data, who's using it, and what kind of actual outcomes they're looking to drive from that data.

Drew: Yeah, that's great. So how would you depict, or what kind of real-world scenarios would you say that you would come across in terms of disconnected contractors that are involved in that process, or the BMS vendors themselves, or even the utilities that hold those data? Like those entities that are involved in all of this, how do you engage with them or involve them in this process where those gaps that we just talked about exist?

Michael Ansamo: Yeah, I think the first thing is really people try to just get access to utility bill data because that's really the backbone of the cost structure, understanding what it is, what it looks like, getting it accurate, making sure that from month to month, they're getting that up to date because that's going to impact the next stage of that work as they work with those vendors to get the work done. What is the impact and the ROI of what's happening? So first having access to that kind of cost structure, and then aligning to the kinds of systems that they have within those assets to drive that work. What we're seeing out in the marketplace is across a single building, you have multiple system integrators that are working on different types of systems. You might have someone different that's working on your lighting control system that's working on your VMS system that's working on your security systems, your network systems, and trying to bring all these guys together and harness that data is really challenging for the facilities manager, that engineer to do. And I think when we start talking about data, it's not just the work that they're doing to orchestrate the data and get it to a central place and understand it, the best results at your building, both in terms of say energy savings or efficiency or comfort or safety with those. So we're starting to see that data and centralizing it and normalizing it is helping to better really drive how those different vendors are worked with. And then we start to look at those asset managers, folks that are overseeing parts of portfolios or even global real estate. Now you're starting to look at the same problem, but on a massive scale. How do they start to understand from a top-down approach, how they implement the right kinds of strategies and processes to unlock, you know, a multiplier of ROI and value at those buildings and ensure that they're developing the best practices to help really drive those across their assets.

Bill: Yeah, that's great. You started out by talking about, sorry about Drew, I had a question. You started talking about utility data and then shifted to data with nothing in front of it. So help the listeners understand what you mean by the rest of the data, because you jumped to VMS and utilities and other users, like tell them what you mean by the data. And if they're relying on the disconnected contractors and the sundries that you're going to explain here what they're missing.

Michael Ansamo: No, that's such a great question, Bill. And it really gets down to the basis of a lot of what you guys talk about, not only in your book, but on your podcast. You know, what is that available data? When we work with our clients and we look at this at a building and enterprise level, types of data that we're looking at is utility bill data. This is usually electric, gas, steam, water, you know, wherever we can get. And even across those utilities, some of that's a lot easier to get and a lot more difficult. Then we start to layer in, say, submetering data. You know, do you have submeters? Are you submetering those? Is it submetered for tenants or at different system levels? You don't understand where the building is consuming those utilities.

Drew: Yeah, yeah. What the utilities charging you, right? But where- Because then you start to also look at the time series of that data. So utility bill is just going to tell you what the cost and usage is for the month. So you start to layer in the time series. That's much more higher resolution for your metering. Now you can start to understand what that looks like over time and specific systems. And then in addition to that, you can start to add in IoT sensors. So maybe it's CO2 or occupancy or looking at things like lighting and BMS type data. So how all those lighting systems- That was kind of where our feeling is. You start with what's costing you and then figure out why it's costing you. Is that fair?

Michael Ansamo: Yeah, definitely. Because it gives you both that cost structure and then where that usage is coming from. That's really driving that cost. And that's kind of the data sets that we look at with our clients, is they look at how can my buildings be more energy efficient, but also how can they be more cost efficient and how those two pieces of the puzzle are really affecting each other now.

Bill: Yeah. And another arm of that too. I mean, it was kind of a part of this section in terms of a potential question was just how it feeds into the net operating income itself. I mean, here we are talking about driving out costs, like shining light in the dark spaces with the data, right? And driving costs as you can. But also, I mean, even in spaces, realizing that there are opportunities for new revenue streams in these spaces, depending on what you're newly measuring or what maybe you've always had the potential to measure it with the equipment, with the kit that you have out there, but it's just never actually been gathered, analyzed, and actioned upon, if I could use that as a verb. So, it's just another, right? It's another option within that net operating income, which is-

Michael Ansamo: Totally. You know, when we think about the operations costs, I mean, you guys talk about this. What are the three things? Occupancy, your utilities, or what it costs to operate it, and your insurance. Well, insurance is going up. Occupancy, hopefully, is going up so you get that better use. But utilities is going up. The cost is becoming so much more expensive. And we always thought as an op-ex or an operations cost, that's kind of a sunk cost. We have to use that. It's going to cost us money to operate our buildings, but those are driving up. And it's also always been a place where there hasn't been a strong focus on, you know, operational efficiency because the data wasn't there, or the data was there, but there wasn't anybody to look at it. Or if they were looking at it, they didn't have time to execute on it. Or they didn't anticipate this much of an increase.

Bill: Yeah. Or they didn't- Given that five years is not atypical. And I can assure you, because we're actually going to have a guest on in a couple of weeks to talk about the power issue across this country, both in generation and in distribution. So, and trying to get the adequate power for your property, whether it's a new build or a retrofit is an astronomical challenge anymore. So, that means if supply is continuing-

Drew: So how can you focus on being more operationally efficient there across your systems and you really have to have the data to do that and utilize efficiencies? I think that's where we're going to talk here a little bit about AI to really drive that transition.

AI's Role in Optimizing Building Operations

Bill: Yeah. I was like, you know, you've been doing AI long before it became trendy, like that conference we were just at last month, if it wasn't AI, you couldn't be there kind of conference.

Drew: Yeah. Well, people were great and the topics were great, but I feel like the AI acronym was a little bit oversold, but that's just Bill talking. So how is AI actually reshaping things like HVAC controls or maintenance workflows or peak load management? Give us some examples and how this operator or owner started and how they got to where they are.

Michael Ansamo: Yeah, no, absolutely. So there's a lot there to unpack. First of all, you're right. AI wasn't always AI, although people have been doing AI for a long time. IBM had their AI Watson on Jeopardy. What was that? 10, 15 years ago. So we've been talking about this long time. It's been, yeah, exactly. And you know, what else were you doing? Machine learning. So using data sets to train on specific things. So I think what's really been interesting and you're right, Bill, everyone's talking about it. It's a buzzword. What is it actually doing? I think a lot of what I see in a lot of applications at very big organizations and very strong technology companies is still kind of in that formative chatbot stage. I'm seeing a lot more of using AI in my own work about how I craft proposals and do research, which has been very helpful.

Bill: It is. Yeah. Not machine learning. That's AGI.

Michael Ansamo: Exactly. And that's with that AGI where we're seeing some real advances, especially within how you can drive what you're doing. In your email, for instance, you know, your digital twin, those kinds of things. That's the extent of machine learning.

Drew: So, you know, what kind of ROI are owners seeing from actually using AI in the field?

Michael Ansamo: Yeah. So being able to use that to drive ongoing optimization, it's really creating this kind of closed loop decarbonization and what that process is looking like is rather than having to look at the data and find projects or executing on it, you can really automatically look at that data to bubble up those projects and then connect with your systems integrators or your vendors to actually execute that and create a closed loop where you have additional agents that aren't just bubbling up those projects, but also then ensuring that they have been put in place. And the ROI has been really amazing. I think across different kinds of assets, depending on the systems, it's different. We're seeing anything from 15 to 20% savings. We've seen some buildings that, you know, by driving-

Bill: In Americans?

Michael Ansamo: Yeah, absolutely. Like you can drive within HVAC in some of these big buildings, looking at condenser optimizations, including temperature differentials and sequences of 150K, we've seen some clients that are doing demand response events with automatic demand and load shedding, doing pre-cooling, 60K in six months. So it's really been amazing, the kind of ROI that clients get by putting these systems in place.

Drew: We like to say we could, you know, we expect clients to save 10% on utilities. The numbers you're saying are stronger and I love hearing that. So yeah, we're going to over-deliver. Can you give us some examples about where AI fails without a strong digital infrastructure underneath it?

Michael Ansamo: Yeah. Well, you know, people say, well, why can't I feed all of my data into a chat GPT and get the results that I want to see from someone that has really built a solution that drives these? You know, why do I need to use something special? I can't use just chat GPT, whatever. And it comes down to a couple of different things. One, you have to have all that data aggregated and normalized. So when we talk about normalized data, it's all the same time series, it's clean, it's structured so that you can use it and also having a context built around that data. And I think that's really what's essential. And I think even if you're going in and building a prompt with whatever you want to do using AI, if you haven't built the right kind of context.

Bill: It's only as good as the infrastructure and the data that you feed it.

Michael Ansamo: Yeah, absolutely. So you have to have the infrastructure to get the data, but the prompt is going to be worthless without AI being able to see into your business.

Drew: Exactly. So you have to have this context and you have to have an ontology. Like what do I do? What am I talking about and how are we communicating that? And that's going to become even more important as we start to see more agent to agent communication. So that's going to continue to advance it. I've seen folks be able to build solutions that are much more configured to client needs and their specific use cases much faster because of the way that you can use agents not only to develop it, but how it's also giving you access to the information and context that this one agent is talking about. So that's really where I think things are going to continue to progress.

Bill: Progressivist. Yeah, I think that's where we all aligned at the last conference was we got talking about the connect and collect stages on the 5C. If you don't have that digital infrastructure, you can't begin to connect and get the data out of your vendor system so you can analyze it with, there's that word again, machine learning. So yeah, I don't want to go into the toolbox, but I wasn't trying to lead you, but thank you for that answer because we tend to agree with you wholeheartedly on the numbers you gave us were stronger than I've ever seen. So I love it. And then maybe it's because a lot of clients just don't actually know and they didn't do it before well enough to know that the savings were there.

Michael Ansamo: And it's really hard. That's why this time right now, even with some of these latest models, has it been a complete step change in the kind of results that you can get from these buildings, but it's always going to go back to the data. I talk to folks and they're like, I want to get those results. What do I need? Well, do you have access to your utility bills? Do you have access to any kind of sub-metering data? And more important, do you have a BMS system that has these data points or a lighting control system that has these data points? And I think to solve your points, are they connected? Are they on? And do you have access to the data? It's a mathematical problem, right? You can't just look at the outputs, the engineering formula, right? You have to control the inputs to get the output you want. And there's a formulaic relationship in between.

Drew: Yeah. And I love to talk about it. Based upon other inputs you have, not just dollars, it's people, it's process, it's all those kinds of things, but you still have to know the formula. So what are the inputs? So we started out talking about utility data and that's why I wanted to shift and say, well, it's actually all the usability data inside of the property.

Michael Ansamo: It is. And I always start with utility data because that has traditionally been a place that people still have problems with, especially if you look at these global portfolios that they're trying to drive with, it's like insane.

Bill: Yeah, we do. All right. Well, that was great. Sorry for letting me sidetrack you there for a second.

Understanding Ontology in Building Systems

Drew: No, no, I love it. So Michael, you mentioned ontology, like just a couple of minutes ago, three minutes ago, something like that. Is there anything left in that arena? Cause I know that's a critical component of what you guys, like how you guys kind of formulate solutions as you think about it, so just the relationships between the different systems elements and everything that we've talked about before, is there anything left in the realm of ontology that you can think of? Have you described that? Or anything else pop into your mind there?

Michael Ansamo: Well, first of all, it's so important because that ontology is the naming schema, that context that you need to do any of this communication, any ways that you're using it, and that context gives you so much more power to drive these end results, and that's going to be applicable regardless of what kind of data sets you're doing, what kind of applications you're doing. So, you know, we always used to talk about data management, like you can't manage what you can't measure, you're only as worse as your worst data set. I think there's kind of a new piece to this, and that's about building ontologies and contexts so that it's kind of like the, we went from 2D to 3D. And there's still a lot of work that needs to be done there. Some of the work that we did is, you know, bringing together Project Haystack and BrickSchema. These are two standard BMS naming schemas, but it creates a kind of a schism. And this is one of these things that when you talk about normalizing data, well, how is the data tagged? Who tagged it? How did they name it? And these are one of these places that having a context in ontology, now I can send one of the AI agents as you expose all those BMS points. So all the VAVs, the air handling units, all that different data that who knows how it was named. Now I have an ontology and a context and a tagging schema that can start to put those pieces together. And you can actually really build out a strong digital twin that still needs some oversight by a person. You know, I think there's still a lot of need for people plus tech and all this AI, especially today when we're still at these kind of changing it, but you've got to have ontology. I mean, one of the things that we did is we built out a ontology alignment project that really brings this together, has all these different tags, sets, points, definitions, and that really enables us to do our work.

Drew: And by having that, you can really start to plug in a lot of new applications. So you have this baseline, this independent data layer and context and ontology that now everything else you can work from. It's like opening up your refrigerator and you have all the ingredients. What do you want to cook today?

Bill: Yeah, nice. Yeah. Okay. So I think the last thing I had here in this little area is maybe it's a little bit of a touch on something that we talked about previously, but in terms of carbon reporting or ESG requirements, those kinds of things. Talk about the powerful influence of actionable data with those. I think we touched on that a little bit.

Carbon Reporting and ESG Compliance in CRE

Michael Ansamo: Yeah, this is carbon is such a big topic these days, right? It is. I spent the last three and a half years at IBM with Invisi working with really awesome sustainability professionals all across the globe, across all types of Fortune 500s. And the first thing even for them is getting their data in order. But then the next thing they have to do is reporting compliance. But these are mission-driven people. I'm mission-driven from a sustainability perspective. That's why I love this work. It's really energizing. What they really want to do is decarbonize.

Michael Ansamo: And I think today talking about carbon decarbonization, ESG has become a little tricky because it's become politicized.

Bill: Thank you for bringing that up.

Michael Ansamo: Yeah, it has. It wasn't meant to be that when it started, but it is now. No, it's what it's really meant to be, environmental sustainability is, give us a context and a measurable way to look at it that's comparable across organizations. So are we all talking in the same way about sustainability and how we're measuring our scope one and two and now scope three emissions? And does that give us the tools then to compare the actual work? Because there was a lot of greenwashing going on. So people would say we went out and planted a hundred thousand trees, but that didn't really make any real impact in what they were doing. So sustainability is still important, but it's the action part of that that's really been missing.

Michael Ansamo: So how do we start to see the places that are driving the most carbon output, which has generally been buildings? You know, that's for most organizations and side of certain kinds of energies. And how do we look at things like electric usage, which in buildings contends to be the greatest contributor to that and take action? And a lot of the low hanging fruit has been picked. So did we do our lighting retrofits already? Yes. OK, check that off. Have we started to do power purchasing agreements where we've done more green power? OK, yes. And the one place that's the trickiest and I'm talking about to people and organizations that are very close to their 2030 reduction goals where they're going to be net zero and the biggest place they still have challenges on actioning the results that ESG reporting, all that information that they've collected and looked at is in how their buildings are operating.

Michael Ansamo: So they can do CapEx. They can look at planning capital improvements, improving their BMS systems, putting those systems in place. But it's still that segment of about 20 or 30 percent. I think it's a little bit more, actually, depending on who you talk to, 30 to 40 percent even of their usage that's ongoing. They have to look from an optimization operations perspective. So then if you can start to squeeze that part of the category, reduce it by 20 or 30 percent because you're running your buildings more efficient because you're able to bubble up new no cost, low cost optimization type projects. Are the setbacks in place? Are sensors working so that we can ensure all the systems are working correctly? Are we able to do automatic or ongoing demand control across both our setbacks and our lighting controls? Now we can start to really squeeze that down.

Michael Ansamo: So you go from measuring and understanding and reporting compliance to really being able to take action and do that last mile that's been really challenging. And that's where having the data, the systems and utilizing the AI are changing the game there and really helping these folks do it. And it's still energy efficiency. So you're driving down costs. Electric costs are going up. So if you can drive down those optimizations and it's also about resiliency. So sustainability work hasn't gone away. I think it's gone a little underground. Depending on who you talk to. And I know a lot of people will yell at me for saying that. But you know, when people start to politicize it. Some companies report on it and some don't. So those that have to report it is a lot more important because it's measured versus the ones that are not. It's just one more overhead. It's one more buzzword. It's one more thing that's a pain in the neck versus just trying to find ROI. Either one. And they've made commitments. Versus I want to do it. It's a big shift.

Bill: Yeah. And they go out there and they make these big commitments and they say, hey, we are going to do this. We're going to do this by now. And they get called out if they don't do it. Not by just external people, but their employees and their investors. And I think that gets back to a lot of the market analysts for the REITs out there.

Drew: Yeah. So these make these assets. It's the future. Like you said, it's a little, maybe it's a mindset shift or maybe it's a future shift, but we hear a lot about automated. But really, let's talk about, in your words, beyond buzzwords, remove the buzzwords. What does autonomous buildings truly mean to you? Like not, like paint a picture of the future, but explain what autonomous is.

Autonomous Building Operations and Human Impact

Michael Ansamo: Yeah. And I think we're starting to get there, but it's scary because people don't want to give up control. So having a building that continues to run and adjust to how it's being used. So occupancy, time of day, weather, temperature, and not having that manual intervention by a person. So as you move throughout the day, as more people come to the building, temperatures are automatically adjusted based on the areas where the most people are. As they move around, as you move from morning to noon to evening, the lighting controls continue to automatically adjust, but they also make these adjustments based on variables that are outside of a standard control schedule or sequence.

Michael Ansamo: So we've seen the market move from using smart, right? From, Hey, let's do the smart. It really wasn't smart. It was just collecting information. Now autonomous, and people are saying it's thinking. I want to point out that it's not, the building is really not thinking. It has enough if-then loops and enough real data to where it always knows what to do next. You're allowing it to decide between two things. And maybe there's a thousand if-then loops in the, you know, and it just thinks really fast. It doesn't think, it decides really fast.

Drew: So you're saying an autonomous building is one that's just been programmed to operate by itself, not needing the human intervention. Is that a fair assessment of what you just said?

Michael Ansamo: Yes, but even outside the capacity of say, scheduling and sequences, it's able to actually respond to real world, real time conditions. They're constantly changing. That would generally require the intervention of a person. So doing setback controls because it's extra sunny. And we've got a bunch of people in the office today because we're doing our QBR. So it's hot. And rather than saying, hey, we've got conference rooms too hot, you know, being able to use that data to make those adjustments across all types of systems. So it's really taking that human intervention.

Bill: Speaking of changes in human intervention, how do these integrated systems, you know, we've talked about lighting, HVAC, energy. I'll throw in access controls and video security and other things. How are they reshaping staffing models and operations for the property managers, for the owner operators that are out there?

Michael Ansamo: Yeah, that's a great question, because I think one of the big fears that people have and that we're seeing from the news, you know, thousands of people are being laid off. Does this mean that I won't have a job anymore? And in my opinion, no, emphatically. I don't think it's going to overall reduce. It's going to limit the need to add in the future, but I don't think you're going to have a recurrence or force. No, definitely. Well, one of the challenges. You're going to take your job. Somebody using AI could. Definitely. And that's what it's going to be. So this is already in conversation. I really don't see staff reduction.

Drew: I don't think so either, because frankly, these facility staffs are already understaffed.

Michael Ansamo: Very. I totally agree. But if you don't know and you're just reading the news, the first thing you think, oh, you know, they're coming for my job. Or if you start to implement these systems and you have that job, it's like, oh, my gosh, what we're going to see is it's going to enable these folks to do the real wrench turning that they need to be doing while digging the leap. The leap is to actually build the community and sit in front of the tenant. Yeah. Doing all the higher value work that they'd like to be doing when they're not bombarded by, you know, a hundred red flags of FTDs that they can't do. They don't have time to look at data. So it's actually humans out there like the human side of this.

Bill: Yeah. Skillsets will tomorrow's operators need.

Michael Ansamo: Yeah. So it's going to build capacity in these teams and it's going to rely upon what people still need to do, which is to have that tribal knowledge to be on the ground and to really execute these like multi-threaded projects. So the skill sets that you need to have is still, you know, problem solving and analytical mind.

Michael Ansamo: And an understanding of how these systems work. So you don't have to be an operator, you don't have to be building these AIs, but how does my system work and how do I get the output from it that I require? And who should I rely upon when I have answers? So subject matter expertise and just having a general understanding of how it works.

Drew: I think that's- You said it's going to be more people related because people is actually the revenue. That's where I come from is the people inside of your commercial real estate facility. Unless you're operating a data center, of course, but that audience is not the one we're talking to here. We're talking to buildings with multi-tenant commercial real estate.

Michael Ansamo: Yeah. I think it's still going to be the soft people skills. You should have an understanding of technology and systems. I think people have to have a better understanding of how AI works when we talk about the LMs and all these different... What are all these? Having your little thumb dictionary. What are we talking about? We're biased, but digital infrastructure is the foundation for all that. And the data that that digital infrastructure generates is the value that the book and this podcast are trying to make in commercial real estate. Grab the value of that data. That's all.

Bill: Yeah. And I think that's a great- Anything we've been saying all along here. Well, that's why I picked up this book off the table and Drew came over and I looked at him, I said, Drew. Well, first of all, I didn't know. He's like, I wrote that book. Who's this guy? Who's this guy? I was like, really? I would thumb it through. I was like, this completely aligns to what I'm talking about every day and how I'm constantly educating the folks that I work with and how they're thinking and the questions that they're answering. This is such... It was great. And I learned a lot of great things from it as well and it really helps to focus and instill that thinking.

Michael Ansamo: So ongoing education, just being up on these things because they're going to be the backbone of what comes next. I feel like I've been very fortunate in my life and career that I've always been, as technology iterates and changes and build us on what came next, I think that people have to do that. You can't stay frozen in time, but continue to understand what's being put in place. This thing about the book was keeping a very complicated topic simple. That's why we went for the sports analogies. Stories in the book are real, but we had to use two fictional characters to protect the names of the innocent.

Drew: Yeah. And look, I'm not an electrical engineer and I am definitely not a programmer. Everything I learned, I learned the hard way. And that's what I've liked about my career, being on the edge of emerging technologies. I do, because that's exciting to me. It keeps me energized and moving forward and gives me the opportunity to have really interesting and challenging conversations with people like you and folks at organizations, both from the bottom up and top down about their problems, whether it's on the ground or from a structural change. How do we implement AI in our organization to drive the best ROI?

Personal Insights and Career Advice from Michael Ansamo

Bill: Great question. All right, Michael, so this won't be a surprise to you. You've seen the podcast. So we always end with this extra floor, right? So it's just a shift here. We're going to do a series of five questions. Just give a gut level, short answer. Tell us what you think. So first one, what's a book or a podcast that shaped how you think?

Michael Ansamo: Yeah, I think what's still been the most important to me has been Napoleon Hill's Think and Grow Rich and then also How to Win Friends and Influence People. I mean, it gives you the opportunity to really drive everything that you do from a core values perspective. And that's really been helpful for me and just interacting with people and building trust and driving relationships.

Drew: What's the best piece of career or life advice you've ever received?

Michael Ansamo: Don't run from something, run to something.

Bill: All right, number three, what's a small daily habit or ritual that makes a big difference for you?

Michael Ansamo: I've got three children, five and under, and I don't have a lot of quiet time. So after I drop them off at school in the early mornings, I like to go for about a five-mile walk if I can, just along the waterfront of Brooklyn. And I get to look at the Isle of Manhattan, all these big buildings, all these opportunities to drive efficiencies. And it's a quiet meditative opportunity. But also, sometimes I have nice walking talks or listening to podcasts like this one. And it's good for my health, both physical and mental. And it's really something I look forward to.

Drew: That's awesome. Three under five. Bless you, my brother.

Michael Ansamo: Yeah. That's awesome. Yeah, I have two over now when I'm turning 28 today. I have two over 28. So I'm at the other end.

Bill: Hey, what's the thing you've learned to appreciate more with time? By the way, Drew has two as well. They're high schoolers. So we got the whole gamut covered here.

Michael Ansamo: Yeah, the changes just keep changing, but there's always changes. It's fun. It's fun. Yeah, you have bigger kids, bigger problems. Silence. When it's just quiet. Late at night before bed and everything is bundled down. Especially if you got a fire on, maybe a small glass of spirits. That's the quiet. My life is that. But also, I would say just spending quality time with your friends and family. I think in a very digital world, spending personal time with people is so important.

Drew: Yeah. Well, and maybe that leaks into the fifth and final, but when you're not working, what do you love to do that recharges you?

Michael Ansamo: Well, if I'm not working, Drew, I'm raising these kids right now. So I don't have a lot of time for that, which is fine. These are the things that I love and I'm relishing these times now. But I do think when I go on a nice long walk, get out into the woods and have a proper hike, that's really essential. Someday when I retire, I want to do a lot of the great hikes and pilgrimages of the world and really soak that in. So that's something that I still really love, being outside in nature and just away from the technology. It's probably because I spend so much time with it.

Bill: Yeah, definitely. Definitely. Yeah. I know that Drew and I both enjoy that outdoor time. So as a young father, good on you for keeping that habit up, Michael.

Drew: Thanks. How can our listeners contact you should they want to at any time?

Michael Ansamo: Yeah, that would be fantastic. I love to have these conversations. I'm so thankful to meet with you. I can be reached on LinkedIn, Michael Anselmo, or via my email, michael.anselmo at noda.ai.

Bill: So perfect. Thank you very much. I really appreciate you guys having me on your podcast. I think this is my first ever podcast and I had a lot of fun. I hope I get to do another one.

Drew: Fantastic. Yeah. Well, yeah, Michael, thank you for joining us today. And thanks as always to our listeners for joining us. Be sure to do all the things, follow, like, subscribe, and everything else that goes along with. So just to please keep up with us as we continue to have more fascinating topics and guests as we go through. So thanks a lot for joining us and we'll see you on the next episode of Peak Property Performance Podcast.