Overview

In Part Two of our series on AI in construction, we examine where technology is delivering measurable value on major capital projects and what owners should expect as adoption accelerates. Jessica Busch is joined again by Chris Thompson, Kris Lengieza, and Dareen Salama to discuss the difference between simply purchasing tools and truly enabling teams to use them well. The conversation explores time savings, improved cash flow, and the role of strong data governance, along with the growing need for education, standardization, and clear operating procedures. The group also outlines how owners and contractors are structuring their technology ecosystems, why data relationships matter, and how these shifts will influence the next phase of industry transformation. This episode offers a grounded view of the gaps still ahead and the opportunities for organizations ready to rethink how they deliver projects.

Podcast Transcript

[00:00:00] Jessica Busch-Garrett: This is the Construction Insiders Podcast. I’m Jessica Busch bringing you the newest trends in strategies in construction, essential to anyone in the industry. Welcome back to Part Two of the Construction Insiders Podcast. I’m Jessica Busch and we’re gonna continue our conversation with Chris Thompson, Kris Lengieza, and Dareen Salama on AI and tech enablement in the construction world. 

[00:00:27] Kris Lengieza: Thank you. Thanks for having us.  

[00:00:28] Jessica Busch-Garrett: So, let’s pick up where we last left off.  

[00:00:31] Dareen Salama: Now. The value of data is much clearer than it was before.  

[00:00:36] Chris Thompson: Almost always, I’m able to spend less time searching for information and more time applying that information and analysis and expertise.  

[00:00:45] Kris Lengieza: We no longer have this group that are coming into the industry that have never used a tablet before. They’ve never used a mobile device.  

[00:00:52] Chris Thompson: There isn’t yet a button push. That I’m aware of that replaces key workflows and key expertise in what we do.  

[00:01:00] Kris Lengieza: There is. We just haven’t told you yet.  

[00:01:02] Chris Thompson: That, okay.  

[00:01:02] Kris Lengieza: We didn’t want you to get upset.  

[00:01:03] Chris Thompson: We’re gonna talk about that happening.  

[00:01:06] Jessica Busch-Garrett: I wanna get in the weeds a little bit more, if everyone’s up for that. 

[00:01:08] Okay. One of the most critical questions when talking about technology , really, how is it impacting these outcomes on these large scale construction projects? Are we seeing measurable improvements? And if we are, is it quality, timeline, budget, performance? Where are we seeing these actual results and diving in and using these technologies to their full potential.  

[00:01:35] Kris Lengieza: So, I had mentioned the report that we did with Dodge previously and one of the stats that we found as I mentioned, was 90% of owners stated that they were able to do more construction work. What does that actually mean? Those who reported that they were saving time, it was five to six hours a week. 

[00:01:52] Of time that they were actually saving on a project when they said that they were saving at least 20% of their time each week, which is, I think, a [00:02:00] huge improvement for many folks. There’s also the aspect, of hey, the risk factor and the quality factor that goes along with that, but maybe even more importantly, is the cash flow factor sometimes. 

[00:02:12] And owners also reported that those who were highly adopted, 83% of them said that they had improved cash flow on their projects when they were using these systems. So, when you put that into real world, it’s hey, people are getting paid on time. We’re putting our cash to work, or our capital to work as effectively as possible, especially when it’s across a very large program. 

[00:02:34] We’re saving our individual workers, our people, the end users, five to six hours a week and those are really tangible benefits that people can put their fingers on.  

[00:02:44] Jessica Busch-Garrett: Is that the difference then? ’cause that was gonna be one of my next questions that I’m curious about is that between having the tool and effectively using the tool and what separates those firms from each other? 

[00:02:57] Kris Lengieza: Yeah. There’s a big difference between, Hey, [00:03:00] I stroked a check and I bought something.  

[00:03:02] Jessica Busch-Garrett: Yeah.  

[00:03:02] Kris Lengieza: That sits on a shelf. I gave a part one example of Microsoft teams.  

[00:03:06] Jessica Busch-Garrett: Yes.  

[00:03:06] Kris Lengieza: We were talking about that sat on a shelf for a while and nobody ever used it. That’s not highly adopted, right? 

[00:03:12] There is work that has to go into enabling your people, training your people, making sure that you have policies and procedures to follow, that there’s standardization. Those are the people who make those big steps all the way up to an optimized space. Now, I will say that I this stat we’ll have to double check after, but I believe it was still like 55 to 57% said that they were, gaining that benefit. It just goes, you can see the difference between 55% and 90%. It’s pretty significant when we talk about how they adopt. And so that is the big difference. It’s how do you implement it? How do you make sure that people are using it? It’s gotta be easy to use and it’s gotta be standardized because the data becomes extremely important as well and at the end of the day, you [00:04:00] want that consistency.  

[00:04:01] Dareen Salama: Yeah I think that basically the one, one important distinction and as we move forward in the adoption of AI, it’ll be there, is that somehow overnight all software in people’s mind became AI and no, that’s not the case, right? So, we have stats about digitization and tools, but we, I don’t think we have critical mass enough to have stats about AI, pure AI adoption.  

[00:04:28] What I have is more anecdotal, but I can say that there are certain functions that you can do and you can it would be an efficiency, save efficiency. So for example, if you have a document controls, pure document controls function, you can easily do that with 25% of the cost that you did before. 

[00:04:48] You can do it a lot faster than you did before. So, it is a significant improvement in certain functions and I’ll actually take us back to one thing we talked about of the job displacement.  

[00:04:59] Jessica Busch-Garrett: Yes.  

[00:05:00] Dareen Salama: It’s really critical that the people who know, I don’t know how else to say this, but the people who know what they’re doing, lead. 

[00:05:07] Kris Lengieza: Yes. 

[00:05:07] Dareen Salama: They know what they’re doing in the function. Like, how does this function work? How do I do, quality checks of the work. Not just procedures, but the people who have the experience, it’s very more critical than ever, so that AI adoption starts in the right way and uses the right data. I could use all the data, but if the data is wrong, all the output will not make any sense.  

[00:05:31] Jessica Busch-Garrett: How are you combating team members, companies, partners, those that have some level of, let’s call it resistance, how are companies overcoming that?  

[00:05:42] Chris Thompson: I think it has to do with something Dareen mentioned, which is, it’s not AI for AI’s sake. In fact, several of the core tools that we use only recently added at least mainstream AI functionality or enablement. Just, I think it’s [00:06:00] a bit of the RideAlong effect in that a lot of the attention on AI has also driven an overall, effort to improve process, whether that is with an AI native or AI enabled tool or not. There are some fantastic tools that we use as part of our ecosystem that don’t even have it at all.  

[00:06:20] Jessica Busch-Garrett: Yeah.  

[00:06:21] Chris Thompson: And so with that, I think clients see the importance of simply having that as part of the infrastructure and not necessarily just the technology in isolation.  

[00:06:33] Kris Lengieza: I think it’s critical to start with the problem. 

[00:06:38] What is it that you’re actually trying to solve? And then you have to go find the experts who know how to solve that problem, and then you have to scale it. No one has ever said, no, I don’t want to save time. Please, I’ll give you my cell phone number. Call me if you do. 

[00:06:54] But like everybody is trying to, has a problem that they’re trying to solve. Go find [00:07:00] the solutions to solve those problems, and some of them might use AI. Some of them might not. And they’ll only work if people do a significant job of actually using and adopting them. But people will use them if it does actually solve their problem. 

[00:07:15] And I think that’s a thing where we struggle sometimes today is there’s not enough education about what AI actually is and there’s not a base knowledge there. And so people go, oh, I can solve this problem with AI, but they don’t really truly understand how it works, the guardrails to put around it. 

[00:07:36] I’ll give you a perfect example of this. Policies and procedures. One of the most common things that people do right now with AI is they build a chat bot on top of their company’s policies and procedures. Everybody’s done it. It’s pretty easy to do. Then they learn pretty quickly that, the chat bot doesn’t understand versioning. It doesn’t necessarily understand specific context. It doesn’t [00:08:00] have the seven other documents that are linked in your policies and procedures, and you get these weird, erroneous answers and this is a real example from a customer of ours who was doing this and they said, oh, we had to actually start to think about how we structure the inputs and train our AI the way that we train our people. 

[00:08:19] We don’t just unleash them on a, the entire SharePoint, right? We feed them things slowly and test them and I think that’s a really important part right now that’ll help us with the adoption moving forward is education around what it can and can’t do. Mainly what it can’t do. And then the space and the freedom to test and iterate. That’s the other one. You gotta give people room to, to play.  

[00:08:42] Jessica Busch-Garrett: Can we talk about these certain tools from just a project lifecycle standpoint? Pre-construction, takeoffs, data integration, predictive insights. What tools are people using to go from okay to [00:09:00] exceptional outcomes, right now?  

[00:09:02] Chris Thompson: I think there, there has to be. A core tool that is your core collaboration platform and there are many of them out there now. We mentioned earlier, that’s one of the great things about being in 2025, almost 2026 or in 2026 by the time this airs.  

[00:09:18] Jessica Busch-Garrett: Yes.  

[00:09:18] Chris Thompson: That there are some really mature, great tools and there’s the ability to choose. 

[00:09:23] But, that I think is paramount and with that, not just the tool itself, not just the platform itself, but the SOPs to go along with it. The training, like Kris mentioned the mindset at, but before all that, the “why?” There are a hundred great ways or more to deliver a great outcome on a big program or project or anything in between, magnitude wise. 

[00:09:48] And we want to see how people can use those tools to take that process that they’re accustomed to and transform it a little bit at a time. But at that foundation, there has to be a core collaboration tool and a single point of truth. And then you can look at what are some of the specific solves that we need to have and again not solutions in search of a problem but something that actually adds value at that step in the workflow. We believe really strongly that the pre-construction phase, the lead in to construction is the most critical phase because that’s when all of those core decisions are being made and you’re setting up your project for success. 

[00:10:23] So, what do we need during the pre-construction phase for optionality? What do we need for collaboration? What do we need for digital twins, for for BIM, for actioning decisions, and also providing that realtime information to owners and then extending into the construction phase for monitoring progress, for being able to look at the model, for being able to solve change management when it when it’s needed, and so forth. 

[00:10:49] Dareen Salama: I, I think I’ll add a little bit to that. So, I think that there is definitely, I think at this point and both Chris’ mentioned that it’s almost [00:11:00] everyone now knows that they need a PMIS, right? And on multiple sides, right? So we as an industry, we have different stakeholders, so each stakeholder needs their own in their own way, right? 

[00:11:11] So, a PMIS is one, but I think it’s one of many and I think that more and more people today recognize that because in the past it was, do I only need that? And that will do everything? That will not do everything. You will always have a financial system. You need a financial system to do any number of things. 

[00:11:30] And specifically when we talk about owners. Owners, it’s not only about construction, right? They are a much larger organization than that. When you’re talking about a university, a public entity, a data centers and tech companies, right? They have a lot more going on than the construction department, which does a lot of work. 

[00:11:47] But still, so you have PMIS financials. Then you have a lot of others. Asset management is a very big one. For owners as well. Space management, there’s a lot of that. Field tools. And then you [00:12:00] make a lot of decisions for your contractors. What are they using? Are they using, scheduling tools? 

[00:12:05] Are they using, to your point, quantity takeoff tools, estimating tools. All bidding tools. There’s multiple, and then the question becomes where is your data? And I think that there are. In, in my mind, there are two schools of thought being formed. There is one that I need to centralize my data and I need a data layer, and I need a data platform that collects data from all these different places. Or there’s another school of thought that, I need it when I need it. I need access to it, but I need it when I need it. I don’t need to store it in multiple places. And I think that, I’m on the side of I need that data. I need to define what data I need and put it in a central location, but I don’t think that it’s any of the existing tools that I mentioned today. 

[00:12:51] I think that, and every owner right now is trying to do that in different flavors, whether they are trying to build their own or trying to buy something. I think that whole, that’s the movement of today that is formed not only in construction, but it’s being formed in a lot of other industries, and that’s being combined with the AI platform play that’s happening in the wider world right now.  

[00:13:14] Kris Lengieza: I’m putting my little separate spin on that, which is. You have to really, I talked about starting with the problem, you also have to think about the end user and there are a lot of tools out there. This reminds me a lot of 2017 and the explosion of technology in the construction space, and there was an app for everything. Now we’re, we’ve got an AI for everything. And I think you have to take a step back and go, okay, at the end of the day. What do I expect my people to use to get their job done? Am I asking them to go into 25 different things to get their job done, or am I asking them to go to four?  

[00:13:55] Jessica Busch-Garrett: We’re all nodding our head  

[00:13:56] Kris Lengieza: yes,  

[00:13:56] Jessica Busch-Garrett: we’re all living it. 

[00:13:57] Kris Lengieza: And by the way, this is not a problem that is [00:14:00] specific to construction. This is a problem for everywhere, right? So your point. You’re always gonna have an ERP. You’re always gonna have an HR system. You’re always gonna have a CRM. You’re always gonna have a PMIS, right? And then there are gonna be specific things that are gonna solve some very specific problems. Gosh darn it those things better integrate really well with one of those other systems and hopefully maybe even be able to be somewhat embedded in them.  

[00:14:27] We talk about, get a little nerdy for a second, like model context protocols, things that could talk between systems in the future, so that if I’m a project manager, I’m going to one system to do my job right. 

[00:14:42] I’m a pre-con manager. Maybe I’m going to one system to do my job. And I think that will actually drive more productivity in some cases than us solving all the individual problems with individual point solutions. And the other thing it will solve is this [00:15:00] question around the data, right? ’cause whether you pull the data out and you put it all in one place, or you pull it as you need it, the thing that is imperative. 

[00:15:12] Is that you understand the relationships between it, right? How data relates to each other becomes critical in how we will use it for predictive work in the future. How we will provide the insights that those individuals actually need. And so when we can say, Hey, the system I’m using for my PMIS. 

[00:15:35] Understands the context of the data that’s in my CRM, which understands the concept of my people, which is in my HR system.  

[00:15:43] And I can now go ask one question to one system. Maybe it’s an AI layer, maybe it’s in one of the platforms, and says, what’s the best team to put together on this project? 

[00:15:54] It has all the things that it needs. To make that decision for you. And that’s where I think we are heading in the future. And think about your end user experience as you’re selecting those tools, and you will find things along the entire life cycle that’ll solve individual points, but think about how they work in, in, in harmony. 

[00:16:12] Dareen Salama: And i’ll get nerdy with you for another second. There is that’s the rise of the knowledge graph.  

[00:16:16] Kris Lengieza: Yeah. Yes.  

[00:16:17] Dareen Salama: So, in multiple industries and it’s not knowledge graph is not a new concept. Knowledge graph has been there and people have tried, right? Either very big companies have built it or people have tried, but that’s where I not only need to collect my data, but I need to understand how this fits together. 

[00:16:36] Then how does this knowledge graph essentially understand the relationship between RFIs and change orders and invoice and people and co and companies, and what a contractor means versus an owner versus a sub versus a supplier, and what does that mean? When the same person works here and then goes and works here, is this the same person? 

[00:16:55] Is this different? What’s the relationship between these two companies? One [00:17:00] company bought another. What’s what? What does that look like now? So, I think that legal entities, all of these different relationships, that’s something that I think is still developing in the industry. It’s not a solved problem, but it is very much developing right now. 

[00:17:14] Jessica Busch-Garrett: So, I was gonna talk about those gaps, right? Developing kind of what gaps do we still need to fill? So, I guess it’s a two-prong question here. What are these gaps and what does it look like then the next year or two for our industry? Before I let you guys go.  

[00:17:31] Dareen Salama: You were about to, I didn’t wanna cut you off. 

[00:17:32] Kris Lengieza: Yeah, go. Go for it. Go for it. You go first.  

[00:17:34] Dareen Salama: So, I think that again we touched upon it a little bit. One is education, is you would be, in the yesterday alone, people stopped me to ask me, wait, what is an agent? Is that a person? Is that software? What are you talking about? One is education from multiple levels on what’s possible. 

[00:17:54] I think that, two is some sort of I, I do think that the industry now is in need of [00:18:00] a refresh of all the organizations of best practices that everyone is following. People are still following without naming any of these standards that everyone knows. But people are still following standards that are really old and they’re not in today’s age at all. 

[00:18:16] Not digital, not even ai. So I think the industry is in need of that a very big gap there. And I think that it’s always been there, but I think it’s easier now. You will still need to spend before you see outcomes.  

[00:18:29] Chris Thompson: Yeah.  

[00:18:30] Dareen Salama: So, that balance between that R and D budget has to get resolved. But, I think that is on its way because people are a lot more open now so that they can get returns on their investment. It’s not a year now, but it could really be within a month you start seeing returns. So I think there’s a bigger tendency to solve that gap. A bigger opportunity to solve that gap now.  

[00:18:54] Kris Lengieza: I would just make one tweak to the last thing I say, you have to invest. I think if we think of it as in spend, [00:19:00] then it’s hard to get people to understand that, hey, this is an investment that is going to pay off in a year or two. We’ve gotta train, we’ve gotta buy the solution. It’s not just write a check one time. You have to continue to invest in it.  

[00:19:12] Chris Thompson: I think, Jessica, to your question of what does it look like further down the road? Three years, five years. My question for the group is, do you think we will feel the moment either in that moment or in hindsight when we crossed the chasm or will it simply because change is very incremental. 

[00:19:27] It’s very gradual, and I think because of that, it’s really important to track those wins along the way and baseline at certain parts of that evolution and stop and look back. How did we really do this? Just. Because like you, everybody has said the pace is rapidly accelerating.  

[00:19:46] Until recent years, and even to this day to an extent, there’s a lot of things in our industry that we’re doing the same way we were 20 or 25 years ago or more. 

[00:19:57] And yet in the last 18, 24 months, [00:20:00] three years, some of those things have finally changed quite a bit and you just become used to it. And so I think it is really important to stop and measure what have we really done differently. That’s why that lessons learned, that continual improvement, that feedback loop is so very important because there is a lot of what we do that has a methodology and best practices that can then be fed back into a new process. And I think that’s really what one of the great opportunities is that no matter how great a lesson learned we do at the end of a program or at the end of a project now we actually have the ability to action that at a broader scale. 

[00:20:37] Dareen Salama: Yeah. I think we will. I’m a, I’m an optimist, so I think that we will, I think  

[00:20:43] Chris Thompson: everybody hear  

[00:20:43] Dareen Salama: Yeah we will see the moment where we cross, and I’ll tell you what the, my parallel is for that. So I think that again, when I joined the industry. I joined the industry in the rise of the promise, I’ll call it the promise of BIM. 

[00:20:58] And a lot of [00:21:00] people, individuals made their careers with that, right? And a lot of firms started by young people that are doing really well today through that kind of angle of this is what we can do and this is what we can do for a project, and this is how quickly we can understand the project and add value. 

[00:21:18] That happened. I’ll call it over a 10 year span. But if we measure what that would looked like, and again, I’m not not going in a, in an ageist direction here, but like the required experience for you to be managing an airport job was that you did, six airports before. 

[00:21:36] And how long does it take you to accumulate that experience? But today we have younger people managing jobs. Quicker with quicker experience. We have more smaller firms that are involved in big in big parts of big jobs. And I think you’re going to see that in the transformation of the landscape. And yes, in five years you’re going to see companies that are adopting technology growing much [00:22:00] faster than others and people wondering how is this happening? How is this company so efficient? How can this company do this? And the work is there. Data center work is increasing. There’s a lot of other types of industries that are increasing in volume and we have to keep up. 

[00:22:14] How are we going to keep up? These new firms are gonna appear people who are doing things differently and I think it’s going to be very clear. I wouldn’t go as far, I don’t wanna go as far as saying whoever is not doing that will go outta business, but there is a possibility that the costs will just not make sense if you’re not really utilizing the AI technology because it’s a, it is a game changer. 

[00:22:36] Kris Lengieza: Okay. You won’t say it, but I will. If you don’t change the way that you’re thinking about building now, you will not exist in 10 years. It’s, there are too many case studies right now that will show you that companies who basically started themselves in the last 10 years and took a different approach than companies that have been around from a hundred years [00:23:00] have scaled up to the size and scale of companies that have been around 9, 10, 20 times longer than them have. 

[00:23:07] Right? There is a moment of disruption. The technology is leveling the playing field and. The complexity and the demand right now is looking for people to innovate. We will have an Uber type moment with a construction company. It might be a new one, it might be an existing one. It might be an owner. 

[00:23:31] Katera was just probably ahead of their time, right? Something like that is going to happen in this industry in the next five years, and we will look back and be like, how did we not see that coming? Why didn’t we think of that? But there are really smart people in this industry, and I see some of the innovation that’s coming out of some of the contractors and some of the owners, the Compass data centers of the worlds, the Rogers O’Brien’s, like they’re. 

[00:23:54] Blazing trails with the technology that’s available today, and I am confident [00:24:00] we’re gonna see that.  

[00:24:02] Jessica Busch-Garrett: This has been an incredible conversation, so thank you all for joining us today. I think it’s clear that these companies that are taking it. Taking it seriously and knowing these aren’t just incremental improvements. 

[00:24:17] This is, we’re really in the middle of a complete shift in how we deliver these large capital construction projects. So thank you all for joining us on the Construction Insiders Podcast. We really appreciate you joining us today. Until next time, keep building the future. And thank you all for being here today. 

[00:24:34] Thank you.  

[00:24:35] Kris Lengieza: Thanks for having us. Thanks for having us.  

[00:24:37] Brad Ducey: Thank you for joining us for the Construction Insiders Podcast. You can continue the conversation by leaving a comment, asking a question, or participating in our poll. You can also visit us@cumminggroup.com for more great resources from the most trusted team in the built environment. 

[00:24:52] And don’t forget to subscribe to Stay up to date on our latest episodes.