KP Unpacked
Join serial entrepreneur KP Reddy for conversations and discussions around innovation, technology trends, and AI for startup founders, innovation catalysts & investors focused on the built environment (and beyond!)
KP Unpacked
Disrupting Construction with AI
To open today's episode, we peel back the layers on why a fresh identity matters in today's market, delving into the nuances of personal brand equity, and confronting the maze of brand confusion.
As we shift our gaze to the construction sector, get ready to unveil how AI is poised to rewrite the rules of the game. We're talking about computer vision's groundbreaking potential to catapult construction management into a future where progress tracking and safety are seamlessly blended with a new kind of transparency—one that mirrors the instant gratification we've come to expect from services like Uber. Yet, it's not all algorithms and analytics; we're also tackling the human element. Prepare to grapple with the emotional intricacies of working under the watchful eye of technology and how this shift might reshape the construction landscape's emotional fabric.
Want more discussions like this? You can connect with KP Reddy at https://kpreddy.co/ and follow him on LinkedIn https://www.linkedin.com/in/kpreddy/!
You are listening to KP Unpacked with KP Ready, a weekly dose of insights for innovators and startups from the built environment and beyond. Want more discussions like this? You can connect with KP Ready today at kpreadyco that's K-P-R-E-D-D-Y dot co. And additionally follow him on LinkedIn at wwwlinkedincom. Slash I-N slash KP Ready. Again, that's spelled K-P-R-E-D-D-Y.
Speaker 2:All right, welcome back to KP Ready Unpacked or Unpacking KP Ready. My name is Jeff Eccles. I'm senior advisor and head of marketing here at KP Reddy. It's a new thing. We ought to talk about that for just a second, I guess. But as always, I'm joined by KP Reddy, the man himself, and this is my weekly opportunity to ask KP hey, when you posted that on LinkedIn, what was it that you were thinking about? What inspired that post? And this is our opportunity to unpack one of those posts. And we started giving you a heads up about a week out or so. This is what we're going to talk about. So that's the format, KP, as always. Thanks for joining me. Glad you're here today.
Speaker 3:Absolutely Good to see you, Jeff.
Speaker 2:It's interesting. I'm looking at your background. It's throwing me off a little bit. You're not at home today. You're out and about today, which is, I think it's sort of symbolic of everything that's going on right now in our world. We've transitioned the name of the company from Shadow Partners to KP Ready Company, or KP ReadyCo as we call it. Your new book literally hit the shelves yesterday and here we are now unpacking another one of your posts. So just real briefly, for those that are listening, kp ReadyCo is the new name. What do we need to know about that?
Speaker 3:I think a lot of it was maintaining brands, and actually I talk about brand in my dude book. It's a painful thing and you know we already have. When I started shadow ventures, we poured a lot of energy into the Shadow Ventures brand. Friends of mine in the brand world still continue to say that you know, my personal brand is actually there's more brand equity in my personal brand than there is in my company's brand, and there was a lot of brand confusion happening between Shadow Ventures and Shadow Partners and there was a lot of brand confusion happening between shadow mentors and shadow partners, and so I've always resisted naming companies after myself.
Speaker 3:It just feels odd to me in this day and age. But kind of everybody convinced me into. You know, you're the one with all the followers on LinkedIn and you have the brand, so why are you to go spend money? Because it all costs money. Why are you to spend money to build a brand from scratch when you already have a great personal brand? So just run with that. So much to my chagrin, we went with it. I think it's working out well. It's a little weird, right? It's a little weird to hear you use my name as a company and then also refer to me. Um, but uh, one of my kids said, dad, like I don't think jp morgan had a problem with it, yeah, and I was like, well, that's one way to look at it it.
Speaker 2:It is and and you know we we don't have the ability right now to ask jp mor Morgan that question, but it's also not unprecedented, right? We've got Tony Robbins, you've got Dave Ramsey, you've got there's a lot of examples like this out there. You know part of the convincing piece of it. A lot of what we bank on, a lot of the currency of what was Shadow Partners, what's now KP Ready or KP Ready Company going forward, is thought leadership. It's understanding, it's knowledge of the industry, it's being able to break down what you see, which is one of the reasons we come here every week to record this right, to talk about what it is that you're seeing and what you're thinking about.
Speaker 2:You know, and you mentioned your book. I think this is actually a pretty decent segue. Your book is a piece of thought leadership. It's what you've seen, it's what you've learned, it's what you understand, it's what you're projecting, predicting, et cetera, around thriving in an AI-driven world, as I said in the open that hit the shelves yesterday. So, just briefly, what do we need to know about the book?
Speaker 3:Well, I think, like most things, even my content on LinkedIn and the pod, it's mostly me out in the world.
Speaker 3:I have the best job in that I get to go out in the world and talk to 20 to 100 people every week. I mean it's insane. And from that I get to glean lots of insights. And I think those insights are factual data-driven stuff that I also write white papers on and things like that, but also it's just also this emotional aspect of what people are going through, which I think those are always connected. It's not just about data, it's also about how people feel and what their sentiment is in the world. And so last year, when I was running around, like I do now, talking to lots of people and AI became part of the forefront, and I saw CEOs talking to me about AI and these same CEOs never talked to me about them. They never talked to me about IoT, they never talked to me about cloud. They all started wanting to talk about AI with no technical background because they were playing with it.
Speaker 3:And from all those conversations it kind of yielded a narrative of, basically, that people are in a tough spot like they don't know what to do next, and while we can learn from history history a lot of times there's a data point. It was what happened then was then what happens in the future TBD but we can learn from it. And so really, I kind of said, look, I started writing a book through these conversations to say, like, how do we get people to feel comfortable about that? We've been in similar situations before, maybe not the same, and learn from that history and learn from that. And then also set out a framework for how to thrive in an ai driven world, which my belief is. We're in an ai super cycle, we're super early innings of it all. But it is incumbent upon employees to re-skill themselves, knowing these tools and different technologies coming available, and it's also incumbent on leadership to guide their employees and guide their organizations, not just to manage through it but to actually thrive in it.
Speaker 3:And I think that's the difference maker and I think when I did all this work and analysis and wrote the book, it was pretty clear that most companies do not have not formed the skill sets to be intangible. They've been very tangible to take problem solution, problem solution and I think if people and firms aren't careful it's a race to the bottom. You know like, think about what we do to produce our content. It's so much easier. You're in a different city than me, we're not going to a studio, we don't have a mixing board.
Speaker 3:We don't have a drove of video editors and audio editors out there, like we're using a lot of AI to do this stuff and we're using a lot of technology, and so I think, as you look at that, if you don't think about all these tools and think about what's coming, um, it's just gonna be a race to the bottom and then next thing you know you're, you're a commodity are you tired of being asked what your annual construction volume is just to get software pricing?
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Speaker 2:Many people that express fear around AI, I don't think are necessarily using the word commodity, but that's what they're afraid of ultimately, and so I think that all creates a good segue to what we're here to unpack today. You said you're out in the world, and I know when I don't even know how many of these we've recorded today that I've had to sit down and take a look at that, but it's quite a few at this point, and the way that you have always explained this to me is you're out in the world, you're talking to people, and that's what inspires a lot of these, a lot of the things that you post on LinkedIn. So, as you're listening out there, if you're not following KP Ready on LinkedIn, you're missing out. I mean, I mean, I mean I, quite literally, you're missing out. I mean, I mean, I mean I quite literally, um, you're missing out. You should be following him because you, you have the ability to glean from the insights that he's sharing there on LinkedIn a couple of times a day usually, and, uh, we only unpack one a week.
Speaker 2:You can go back through the archives of the podcast and listen to those, and you can, you can join us live inside the Catalyst Network if you'd like to experience the live recording sort of behind the scenes piece of that, or you can listen going forward in the podcast. But every week we come here and unpack one of those posts. So, kp, what we had talked about unpacking this time was the post on AI and construction sites. You still want to do that one.
Speaker 3:Yeah, let's do that.
Speaker 2:All right, so I'm going to read this. I'm going to read what KP posted. As I'm looking at it, it looks like he posted this on about, let's say, april 25th or so. On LinkedIn Right now it says six days, and so I'm counting on my fingers and looking at a calendar and it's getting pretty complex. So I'm guessing about April 25th, but it reads like this KP wrote AI on construction job sites is big opportunity.
Speaker 2:I was teaching a building construction class at Georgia Institute of Technology so Georgia Tech yesterday. Many of the students have work experience and were intrigued by the case studies that I shared. Their feedback was that they spend a lot of time chasing people down for information to make decisions, but it's such a huge lift that by the time they have all the info that they need, it's old. So let's unpack that for a minute. First of all, been there, done that right in past life, and I completely understand where those students are coming from. I also teach and I understand where they're coming from, from that direction as well. But what's important about this, as you look forward, you have access either through our incubator or through Shadow Ventures, all the conversations that you have there, knowing founders, knowing corporate startups that may or may not be a part of our incubator. You've got a lot of insights around that, so what's important about this idea of AI on construction job sites and where it's headed?
Speaker 3:No, I think so.
Speaker 3:I said there's a couple of things to think about is if you are provided, as a decision maker on a project and a company, whatever it is, as a decision maker, if you're provided the right information, the decision becomes self-evident.
Speaker 3:It doesn't take a lot of rocket science to figure out and make the right decision based on having great data and relevant data. The challenge is on a construction job site, there's so much data floating around, information floating around that people run around to gather the information, whether it's a scope issue, whether it's a safety issue, whether it's schedule cost, all the above. They're running around and collating all this information and the decision makers still don't know enough, and so that's when the experience kicks in. Right, like 80% data, 20% experience. But quite honestly, that experience starts to become de minimis if you have great information, if you have great real-time data, and so this class it's. You know, it's a lot of students that are working in the world, in the real world, and this is like they're getting their degree on the side. They were just sharing that they spend most of their job gathering information and running around versus actually learning about a project.
Speaker 3:The comment was like we're glorified administrators at some point on a job site.
Speaker 3:So when you look at a lot of the AI, information, ai technology that's out there, I think for our industry, you know the number one leading AI technology is computer vision. Everything we do on a construction job site has everything to do with our eyesight. You know we're not tasting anything, we're not feeling anything there's, there's, you know, in the world of senses it's pretty much eyesight, maybe the occasional audible like watch out, that's when yelling at you, but outside of that it's mostly visual. So you think about that. You think about we build off of things that are very visual. Again, right, we're, we're reading drawings, we're reading specs, where it's all visual once again. So we're taking visual components that are in documents or drawings or whatnot and then applying them into a 3D space, the real world, visually. And so to me the biggest technology that's changing the game for our industry is computer vision. Biggest technology that's changing the game for our industry is computer vision One. It's got great eyesight right, it's got great resolution. It's amazing what you can get with cheap cameras almost disposability of the hardware. These days you don't need anything special. Yeah, you can deploy LiDAR and other technology, but honestly, the camera $100 camera is good enough these days.
Speaker 3:The other thing is, as an individual with great eyes, you can't be at every angle of the job site at all times, and then you still have to process that visual data and apply it to make decisions. So the ability to use something like computer vision to see what's going on in a job site real time and then apply that to, for example, scheduling or we're behind schedule by building this piece of the building, by building this piece of the building, so progress tracking which is an interesting idea that why do, as an owner, give me an update, where are we at? Then the contractor runs around and gets a bunch of information to kind of where are we at? And then also has to massage it to make the customer feel better because it's probably behind, it's probably over budget. So there's this interpretation that happens versus the owner just being able to say hey, this is my project, I want to know what's going on real time and I want to know on my iPhone, I don't want to have to call you, which is what we've done with everything in our personal lives. We get reservations online.
Speaker 3:If you think about the Uber case study of why people like Uber versus taxis is when I call a taxi, I have no idea where they're at. When I call an Uber, I know exactly where they're at and how far away they are. That's good data for me to understand. Even if they're running 15 minutes late, at least I know they're 15 minutes late and I can go get a cup of coffee while I'm waiting, so it allows me to make decisions.
Speaker 3:And so when you look at AI on the job site, besides use cases around safety, it's really about transparency, which is good news. Bad news. Transparency is one of those things. Don't turn on find my location for your teenager if you don't want to know, because the good news is you'll know exactly where your teenager is at any given day. Maybe you don't want to know that, maybe some things are left with them and their friends and you don't need to know all the details as long as they get home safe. And so I think there is something to be said around this transparency that exists today. This AI technology exists today. The challenge I really say is back to the feelings, like when I talk about developing my book. How does it feel to be ultimately like that transparent, from whether it be a trade to a sub, a sub to a GC, a GC to a design team and then ultimately the owner and the owner.
Speaker 3:This is what the owners have owners, they have banks, they have financing, they have endowments, they have people they're accountable to. So how comfortable are we living in the facts versus leveraging feelings to get the bad news down? So I think it's fascinating times. We've made some investments in that space. We continue to look at that space. I'm not here to plug my portcodes so I'm not going to get into that but I think it's a huge opportunity and the only headwind, really, it's not cost, it's not productivity it checks all the boxes of feature benefit it's people. People are the problem. The emotions like do I really want to share that data? And I always say like I'd rather have the truth and honesty faster so I can make decisions. You know, bad news is not fine wine. It does not get better with age, and so I think that's what everybody wants, and I don't think we want the facts being massaged to make us feel good, but I think it's a cultural shift.
Speaker 2:Yeah, it's. You know, as you say, that it reminds me of a quote from Colin Powell. You know, former general in the US Army, former Republican candidate for president, and he was talking, you know, looking back at his time in the military. You know commanding troops, obviously at the highest level, and he said you need between 40 and 70% of the information in order to make a decision. If you have less than 40%, you're going to make a poor decision.
Speaker 2:If you have more than 70%, you probably took too long to get that and you know it may have already passed by now, and so I think, you know, as you were describing, that I wonder how he would revise that now, because he has the ability to get much more than 70%, much faster. You know, and I think the feeling, as you're talking about, the feeling of making decision based on 40 to 70% of the information, there's some gut going on there, right? There's some um, there has to be. If that's the way I'm, I'm making a decision right. I think you're, I think you're exactly right. I think, um, you know, we've talked about this before too the ability to separate fact from feeling, the ability to have the information I need to mitigate risk, I think is also very important. You know, having all that information the facts don't lie so fascinating topic to cover here.
Speaker 3:Now, like I said, I think we have to all start getting comfortable To your point. It shouldn't take that long to get 70% of the data you need to make a decision, and there is so much inefficiency when we talk about optimizing construction and optimizing, you know whether it's the cost or the timing. If you can get people better data faster to make decisions, projects go better, I mean I don't think we need to. You know, we don't need to do a research report on this. We don't need to do a ton of academic research on this. Get better data faster, make better decisions. I mean, that's all it is, and I think it's a fascinating time.
Speaker 3:You know, I'm surrounded by a lot of friends in construction and real estate and I always say, like I'm so glad I'm in tech because I can kind of command and control and know everything via my laptop, via my phone. They have to sit there and use a lot of judgment on any given day in terms of what's going on on projects, and it sounds terrible. It sounds like a really tough way to live a life, so to speak. So I think my hope is that industry starts to think about this, that transparency is good, and then I think owners will also start to. I think owners are already starting to demand it.
Speaker 3:I'm hearing it from owners that are saying, oh, this technology exists, why are my contractors not using it? I just want to log in the first inkling we saw that was with job site cameras. Some friends of mine in Atlanta started a company called Ox Blue and they were on job sites. They just were streaming just video footage. It wasn't anything analytical and owners loved it. I remember doing business. I used to do a lot of consulting for Safeway grocery stores and they had a command center because they were building stores all over the country where they didn't have construction personnel. And they had a command center because they were building stores all over the country where they didn't have construction personnel and they would sit there in their office and in California and like checking on the streams and see what was going on.
Speaker 2:Yeah, you saw a lot of that during COVID too, a sort of an explosion of that out of necessity, right? Oh, we can't have people close together on job sites, even though it's outdoors, et cetera. So there's a huge advancement in the use back then as well, and it's only accelerating at this point. It's pretty exciting times, I think.
Speaker 3:I would agree. I would agree.
Speaker 2:Well, kp, thank you for unpacking this post for us today.
Speaker 2:Again, I'll read it again. It's relatively short. If you're not following KP, why? Why aren't you? As I scroll down through his LinkedIn feed right now he's talking about startup founders, which actually I think we'll talk about next week. Startup founders, which actually I think we'll talk about next week. He's talking about VCs, and in this post he's talking about AI and construction job sites, so maybe more tactical in terms of the types of use cases that are out there. And so this post from about April 25th or so it reads AI and construction job sites is a big opportunity.
Speaker 2:I was teaching a building construction class at Georgia Tech yesterday. Many of the students have work experience and were intrigued by the case studies that I shared. Their feedback was that they spend a lot of time chasing people down for information to make decisions, but it's such a huge lift that by the time they get all the info, it's old and true statement, absolutely true statement. So think about that and hear what KP has to say here as we talk about better information, faster and being able to make decisions. So again, kp, thanks for joining me on this journey today to unpack this post. As I said, next week we're going to talk about maybe not all founders are cut out to be CEOs. We'll see as we unpack that one Engage with KP over on, especially in the Catalyst Network.
Speaker 2:It's a great way great place to engage with them on, as in the Catalyst Network. It's a great way great place to engage with him on. As we're recording this. Actually, tomorrow he's going to host the Founder Circle over there. So it's basically office hours with KP tomorrow. Tomorrow at 11 am Eastern. So again, thanks, thanks for listening, thanks for watching If you're watching this live now inside of the network and we will see you again next time. Thanks everybody.
Speaker 1:Want more discussions like this. You can connect with KP Ready today at kpreadyco, that's K-P-R-E-D-D-Y dot co. And additionally follow him on LinkedIn at wwwlinkedincom. Slash IN slash KP ready Until next time.