All right. I think we're ready to kick it off. Day two of the Communacopia + Technology Conference. My name is Joe Ritchie. I cover the multi-industry sector at Goldman Sachs, also co-head our U.S. Industrials and Materials Research. Really happy today to have Roper Technologies with us today. We have Neil Hunn, President and CEO, as well as Jason Conley, CFO. Thank you guys for joining us today.
Yeah, thanks for having us.
Great to be here.
Neil, year three at the Communacopia + Technology Conference. At this point, you would think that folks would be pretty familiar with the Roper Technologies story, but for those that aren't, maybe just provide a little overview on your value creation framework, and we'll take it from there.
Yeah. Just real briefly, think of us as a durable, steady, low range of outcomes, cash flow per share compounder. That's the mindset of the organization. In terms of the profile of the assets and the business, about $8.5 billion of revenue, 40% EBITDA margins, low 30% free cash flow margins. Perhaps interesting for investors is the portfolio of businesses are hard for investors to own individually because they're small. They're tiny businesses that are leaders in small markets. So we're the leader in a small TAM. So we have the scale advantage locally, but we compete on intimacy with customers. We have strong product-market fit, strong gross retention, and collectively, the cash flow generative capacity of the enterprise is quite compelling. Standalone, each business would not be particularly uniquely productive in how to deploy the cash flow they generate to their own individual purpose.
Therefore, we take all the cash flow up to the center, the free cash flow, excess free cash flow, and deploy it to what is, we think, the next best opportunity, whether it's a new platform, a tuck-in acquisition, a buyback at the enterprise. When you put that together, the cash flow compounding per share capacity is in the mid-teens, and we go to work every day trying to find a way to get that to the high teens, so the rate of double goes from every four years. Excuse me, every five years to every four years. So low range of outcome, durable cash flow per share compounder, one of the largest, if not the largest, vertical market software businesses that's publicly traded, that's a collection of 29 businesses underneath the hood. But I'll stop there. We can take where you want to go, too.
Yeah. Super helpful. Before we get into the whole AI discussion, which I'm sure will dominate a lot of this discussion, we've talked historically about being very focused niche markets, vertical software. Why is the disruption risk low when you think about the horizontal players that are out there potentially coming into your markets? How do you think about the defensibility of the businesses that you're in?
Yeah, I think there's several defensive aspects to it. The first, and this is proving to be the case even in the AI era, is the size of the prize is quite small. When I say our TAMs are small, our largest singular TAM for one of our business. Our biggest TAM is about $4 billion a year. This is pre-AI. Most of our TAMs are $1 billion or less. So the size of the prize is just quite small. It's already very well-vended, particularly by us, and a very small number of competitors we have in each one of our verticals. So that is the case. I think 18 of our 21 software businesses work in a regulated end market. Oftentimes, the regulatory regime is why you need very specialized software in a vertical, whether it's education or insurance or government contracting or whatever it may be.
Healthcare.
Healthcare, for sure. In that specialized end market, there's something unique about the way that end market operates that isn't suited particularly well for horizontal software. Every one of our businesses were created sort of in the nooks and crannies of the horizontal. From the day that they were born, the businesses were born, they had to create differential value from the generic application of horizontal software. Those are some of the reasons why it's historically durable. Going forward on an AI front, if you think about, in our opinion, what are the attributes for an AI winner? First you have to be able to take this probabilistic outcome to deterministic. That's largely done with the context and data knowledge graphs that we have across all of our businesses.
Then you have to apply that in a workflow with potentially no latency, and you have to have the customer trust to be able to do the first one of those. It's the aggregation of those that is, I believe, an incumbent advantage in AI, which I'm sure we'll get into as we get further into the questions today.
Yeah. Let's start. Since last year, you have given a ton of examples on earnings calls, in particular, about how AI adoption is accelerating across the portfolio. Maybe just level set us on what parts of the portfolio are already monetizing AI and bookings or retention ratios and how you're monitoring it.
Yeah. Just to step back and a little bit of context. When the AI gun went off a couple of years ago, our decision at the enterprise level was we want to take all of this goodness of these tools and drive into the product stacks to drive customer value, to drive growth, and play offense. From the very beginning, that's been the mantra and the mindset. Not how can we do what we do substantially more cost effectively and take it to margin. We're playing sort of a growth game knowing that over time we'll get the productivity and maybe there's some marginal benefits, but we want to take all the productivity gains and go play offense.
What that manifested is all of last year into this year, it has been how do we develop these agentic SKUs that are doing these task replacement sort of things across a large swath of our portfolio, not domiciled in one or two of our businesses, but essentially all 21 of our software businesses. That has been largely successful in the first wave, and now we are in the commercialization sort of learning phase of that, broadly across the portfolio. When you have a portfolio of our size, you definitely have companies that lead the pack and ones that lag. Your question, like on the early adopters and where we have had real success in autism therapy, legal, increasing success in some of our other healthcare IT franchises, early success in insurance, early success in pharmacy automation, just to name a few. I call it early.
We have got to scale this. It has got to get scaled across a dozen plus of our software businesses, not just the product releases, but the commercialization, the retention. Signs are encouraging early, but it is too early to call the trajectory of that.
Maybe, you have a disparate group of 21 software companies, right? What is it about the ones where you have had early success versus maybe more kind of like, you think the adoption is going to be a little bit more gradual? What are some of the reasons why these companies, whether it is CentralReach or Aderant, is having a little bit more success than others?
I will start, and Jason can add some color. I will paint two distinct points on this map, and then I think most of our adoption will live in the middle. In autism therapy, there is a huge demand for the service in the U.S. There is something like 800 million therapy hours that are demanded every year. There is 300 million therapy hours supplied. There is a line outside the door of every autism therapy clinic for families that need these services. Our three categories of agentic SKUs basically allow the therapist to have more hands-on physical therapy time with the learners. Instead of 15% administrative time, it goes down to 5%. They see more learners, the line gets shorter, more families receive the care, the practice makes more revenue. It is a win-win-win. It is just a win all the way around.
That's been a very fast adoption, faster adoption pace for us. It has been. On the other side of the coin, same conceptual setup. In freight matching in the spot market, we own the business that organizes a spot freight market in North America. It's called DAT. Roughly 750,000 unique loads are advertised on our network every day between freight brokers and carriers. The capability that we bought and built now can automate entirely the matching process of a freight broker to the carrier. Today, it costs between $100 and $200 of manual labor to do that. There's about 10 phone calls that happen in each one of those matches. "Are you available on Thursday? Can you do it for $3,000? Can you drop it off on Friday by 3:00?" This happens back and forth.
I need your insurance." We collapse all of that into an automated charge, $40- $50 to do it. That rate of adoption's been slower because the person pressing the magic button's like, "That's my job." There's human adoption that has to go through. The unit economics are so compelling, it will happen, but the rate of adoption is going to be a little bit slower. I think the reality for most of our agentic tasks are going to live in between those two. Because in the case of DAT, it's not entirely replacing a freight broker's job, but a big swath of it is.
Most of what we're doing, and whether it's pharmacy automation or insurance automation, we're replacing and augmenting individual tasks. I think the propensity to, "Yeah, I don't like doing this reconciliation task," or, "Of course, I don't like to have confirm every script, every day for four or five hours of my day. If the software can do that, I'll let it do it," so the people can go do higher value-added tasks. I'd expect the rate of adoption for the bulk of what we're doing to be between the two, not super fast, not super slow.
The only thing I'd add is, we are in small markets, and so what we've seen at least on cloud adoption as an example, I'll pick on legal. We thought it was going to be the slowest to adopt cloud, and then when COVID hit, you had this tipping point, and then when law firms knew that others were implementing it, you had an acceleration. I do see parallels here, where you're going to come back a year from now at these user conferences, you're going to have reference customers, and they're going to show the benefits of it from a productivity standpoint and say, "I got to get." There's a lot of conversations that happen within the industries, and so I think we just need to seed enough of those to get that tipping point.
That's right.
Super helpful example. Thank you for that. Last year, at this conference, I asked you about disruption risk. You mentioned Foundry as a potential portfolio company that could be disrupted maybe sometime down the road. Then this year, Foundry returned to growth. You launched more AI tools. Has anything changed about the long-term risks of Foundry? As you think about the broader portfolio, any further thoughts on whether there are other parts of the portfolio that could be disrupted?
On Foundry specific, the context here, just so everybody has it, Foundry's less than 1% of our revenue. If we're wrong in this statement, it's not hugely impactful to Roper. What Foundry does, by the way, is it has a very clear market leadership position in post-production, high dollar per minute Netflix streaming, theatrical releases. It takes the live action and the computer-generated graphics and composites that into a single frame. Think the "Game of Thrones" dragon and the humans, putting it into a single screen. It all happens in post-production called compositing, and we have a very strong market position there. If you believe that all high-dollar content is going to be completely generative, then there's not a post-production step to do. That's like the existential threat for that business. The current course of speed is that is not what's going to happen.
AI is being used to generate more CG, and more CG means more compositing. What Foundry's doing is making the compositing step even more automated. In the intermediate term, multi-year term, it feels like there's wind at the back of Foundry, but we can all draw individual conclusions on where the future, 10, 15, 20 years of high-end, like million-dollar plus per minute sort of releases will be in terms of content creation. That's sort of the framing of the existential risk. For the broader portfolio, we feel very comfortable. We think that's ultimately with Foundry, is like, does the end customer exist? Yes or no? Does the compositor exist? For the other 20 software businesses, we feel very convicted that the end customer exists. There's going to be an autism therapist. People are going to go to church.
Insurance is going to continue to be sold for complex business insurance. The customer exists, and it's then our job to automate as much of that customer's activity to service that end market as possible. We feel very comfortable with that opportunity. But it tilts very in favor of growth versus contraction.
Very helpful. Maybe talk a little bit about the pricing models that exist. Because I'm sure they're disparate across the different portfolio companies.
Mm-hmm. Yeah. No, and it is disparate. Some of that is inherent with whatever the business model was before. We have a couple of businesses, like parts of DAT, where it's automated already. It's based on per transaction, or at SoftWriters, it's based on per script. The agentic charge meter is going to be similar to that, and the customers are used to that consumption. But that's more of an exception. I think what is starting to be apparent, and I think everyone's heard this, is that as a CFO, especially, I want to have certainty on my budget. Something like a credit system is what we think is going to be probably the preponderance of what's going to be out there. It's something that Vertafore put in place in the market.
Essentially, if you're a customer, you can draw down credits based on the task that whatever agent you want to choose, there's different meters based on different tasks. That's good because it's a use-it-or-lose-it type policy. We get recurring revenue out of that. It's more certainty to the customer, and so that's where we see things headed.
Got it. Okay, great. We talked a little bit about some of these efficiency gains. You talked about DAT and maybe some of the slower adoption. One of the things that we've talked about historically has been that AI could reduce some seat in some of the workflows. Have you seen any kind of seat compression today across your portfolio or no?
We've not. Gross retention continues to be very strong, mid-90s at the enterprise level is the number we sort of talk about earnings calls. We obviously monitor that. We also just inventoried the pricing model. This goes back a year and a half, two years ago. There's only three of our businesses that have a pricing meter that we might potentially have to adjust the meter over the medium arc. Nothing we have to do, like, we'd change it in a nanosecond. The reason there's only three, think like healthcare IT, to the extent we have seats, it's like the total number of healthcare workers. So we don't need to change that. In insurance is the one that we have a very clear line of sight, property and casualty insurance, on how we need to modify the pricing meter. We have the plans in place.
We have the telemetry that's being built. The first wave that'll go out in the first part of next year. It completely aligns with the customer. We're not trying to price grab or change total price. We're just changing the underlying meter from a seat to something that's more indicative of the growth and unit economics of the insurance agency itself. So that's the one that is sort of front and center. The next one would be our legal business, which we charge on the number of fee earners. This is not. Once you hit a fee tier, then you basically can't drop down. So we might introduce a secondary pricing meter with that. We may or may not.
Those are the two that we have to work on in, I'll call it, the shorter term, and possibly over a multi-year period of time, maybe modify what we do with Deltek, but not something in the short term.
Got it. Is your customer changing who you are actually targeting within each organization?
Interesting on this is it is hard to generalize across all 21 software businesses, but I will take a stab at it.
Yeah, please.
Our customer profile is typically a medium-sized business. Think a three-facility daycare center, or a four-facility closed-door pharmacy, or a 500-person insurance agency. We certainly sell to large enterprises in our government contracting business, and there are some very large insurance companies, for sure. But the preponderance of the number of customers that we deal with, we are the IT budget. They do not have Salesforce administrators. They do not have big IT departments. We are the IT department, if you will.
In that regard, the customer is not really changing because we're generally selling to the principal or a very close proxy to the principal. Maybe the CFO of a large insurance agency, maybe not the owner or the CEO. In that regard, no, it doesn't change that much. At the enterprise level, we do sell to larger customers. I would say that we have typically sold. That's where it might change a little bit more to the end user than the IT department, where we're sort of selling a tool to make the user more efficient, then they have to take it and work with the IT department. But that's a minority of the sales motion that we have.
That's helpful. You mentioned earlier, Neil, that you're trying to take all your productivity gains to play offense.
Right? Maybe discuss where you're seeing the biggest kind of efficiency gains within your own portfolio.
Yeah. Okay. As I said earlier, a couple of years ago, when the gun went off, it was like, how do we go drive in product velocity and play offense and get first products to market and accrue the AI agentic learnings at accelerated pace and compound that? Without question, where we've seen the most productivity in the organization is where the emphasis has been in the software development life cycle. It's direct. It's straight up offense. As we have more product velocity, and this is not just using the models to code faster. There's a whole workflow. Coding is but a small portion of the software development life cycle.
It's the whole software development life cycle that we've got a very clear model on what it looks like, the way you organize your people, smaller teams closer to customers solve problems or build features to drive product velocity. And we've seen really encouraging, super encouraging results in pockets from enterprise and are on track to be fully agentic SDLC across all 21 software businesses by the end of this year. So not 30%- 50% improvement, but multiple-fold, like 3- 5X product velocity releases. That's great. We just now have the organizational mandate to get other functions together to share best practices about what they're doing on the AI productivity. Finance teams, sales teams, support teams, services teams, implementation teams.
There's pockets of real goodness because the incentive is like, "Hey, if you can drive productivity to go put more and to go to market a product," then every company's incentive to do that. It's just how do we get the competitive juices flowing inside the portfolio? Like, "Oh, that company's doing it. I want to do it better. I want to at least adopt what they're doing." And we're just literally this month getting the other functions together to tap into that.
That's great. I'm going to ask one more question and then I'll turn it over to the audience before we move beyond this topic. Just in terms of contribution, right? So I think you said AI is not going to be a material revenue contributor this year. You're going to see it flow into bookings first and then into some of your recurring revenue streams. How are you thinking about potentially the 2027 contribution, and when would you expect it to really kind of influx for you?
Well, I think the second half will be telling in terms of the early signs of bookings, and then from there, I think it's just adoption. So I think adoption is the ultimate question. I think we're getting signals from customers like, "Wow, this is really going to kind of revolutionize what I'm doing," or I think that the signal's really strong, but in terms of when it's actually going to materialize is the $100 billion question, and we're just not there yet.
Okay. Fair enough. I am going to turn it to the audience, see if there is any questions before we move on.
In terms of the value proposition
Keith, just give me one second for the mic to come. Thank you.
Thank you. So in terms of the value proposition of playing offense by increasing productivity in AI, maybe how much growth do you think you can get by executing this strategy and changing your trajectory from now on?
Again, that goes to the same question. What we know is, we know TAM expanding. We went from theory to real. I think that is clear and obvious for us in our portfolio. What is less clear and obvious is the ultimate magnitude of growth and then the pace to get there. We are a sort of a 5%-7%, 6%-8% sort of organic growth business. I think this is hundreds of basis points, but it is not a doubling of the growth rate of the enterprise. I think we can say that just to put big parameters around it. Again, we are going to be very cautious on what the ultimate destination is and the pace to get there until we have more, like we see it in the trailing numbers, because we are speculating on two different parts of a trajectory that we do not quite know yet.
Question right here.
Do you feel now is a good time for shopping for more M&A targets, given like everyone else is quite depressed?
Jason, you want to start?
Yeah. The question was what's the M&A environment? I think it is a great time to shop. We just need more products on the shelf. I think there's lots of conversations about products that are going to be on the shelf, but they're not there yet. What I mean by that is, we still have this kind of bid-ask spread between where the public markets are trading and sort of where private equity thinks their assets should trade. There's a lot of, I think, tailwinds for us in terms of LPs need liquidity. There's some credit cliffs coming in the next couple of years, what we've seen in the public markets.
I think all those things, and we've been having very constructive conversations with sponsors over the last, boy, really two years, but I think they've gotten increasingly more constructive, like really wanting to transact. We do think, though, that because there's been so much volatility in the public markets, they're probably going to try to wait this out as long as possible, and it's probably going to be more of a 2027 where we'll see kind of meaningful platform-sized deals that'll come to market.
But also just look at the decision, like the actions we took in the last earnings call. From November to June, we bought 8% of the company back in eight months, essentially. Then we said we're going to prepare the balance sheet and build M&A capacity on the prospect that what Jason just said is going to happen. The early signal that there's some beginning stages of seller capitulation in the private markets appear real. It takes more than a month or two to prepare the balance sheet, but the returns that we could potentially drive to the enterprise and the cash flow compounding that could accelerate to the extent we can buy the businesses we bought 18 months ago for 30%, 40%, 25% lower prices are quite compelling. The option value for that is worth exercising. Yes, sir.
Following up on the M&A question, how does a rising rate impact your M&A decision, and at what point does it become prohibitive for you?
Yeah. Cost of capital factors heavily, and it goes to ultimately the underwrite case. What we try to do in the underwrites is we know that in the cash flow compounding, what we need in terms of capital deployment to drive the cash flow per share compounding we need, we need to underwrite somewhere in the 10x year 5 EBITDA as a baseline. Tax effect that, inverse that formula, you sort of get year 5 ROIC. That is what we underwrote to a year and a half ago. With the asset prices coming down perspectively, that will help sort of underwrite substantially below 10x . But then cost of capital will push that up a little bit. It all goes into the math equation, of where it is best to deploy the capital.
Certainly, increasing cost of capital will put some deflationary pressure on the asset prices for sure.
That impacts sponsors more than it does us.
That is right.
They can't put as much debt on the assets. Mezzanine capital is not available. That should drive down prices.
Any other questions from the audience? Just continuing along with the M&A side for a second. In the pipeline that you see today, are you seeing more opportunities in earlier stage, faster growing companies, or are you seeing it in more mature platforms and bolt-ons?
Just to reground everybody, in the 2022 timeframe, we made a modification to our capital deployment framing, which is more value to be created, more long-term compounding for the shareholders instead of buying a nearly perfected asset. Buying it from being the last owner of a long string from venture to mid-market to sort of scaled private equity to us, we essentially want to buy the same asset, a leader in a small market, high gross retention, strong product market fit, but being an owner or two earlier. We buy more from mid-market. We're catching businesses as they're still growing a little bit faster, still have margin opportunity to improvement opportunity. So more value for us to go execute to grab for our shareholders. That is still the archetype that we lean.
The businesses in the portfolio definitely lean more growthy relative to the pre-2022 time. Now, whether or not, I wouldn't distinguish too much if they're 10% or 20% growth, but they're not like mid-single digit growers, because we're just not tuned in that part of the portfolio. The other is to do, if we could deploy all of our capital in tuck-ins, it would be a great outcome. Just the time and motion study of that doesn't allow us to do it. We don't have a portfolio that's large enough, and the tuck-ins are small dollars. We'd love for that to be a quarter to a third of the capital deployment over a long arc of time. That's always the first call of capital for us is the tuck-ins. The portfolio is always a good mix.
Janet and her team do a great job of looking at every portfolio of every sponsor, meeting with all the companies, having them in various sort of quality quadrants, high business quality, attractive end markets, spend more time obviously in the box that is attractive and attractive. Cultivating the relationships, understanding the timing of those. That has substantially improved over the last 3 or 4 years in terms of understanding the actionability and sort of having us be attractive owner of those businesses.
Yeah. You have had some great outcomes so far with CentralReach and Subsplash. Maybe a less favorable outcome thus far with Procare Solutions. I guess when you think about this shift, what has been the hardest thing to underwrite? Is it the management capability? Is it go to market, like scaling? What has been difficult?
Thinking about this, we had to almost like do process elimination, like what is easiest, what is hardest. What we have been able to prove, and this is a learning sort of process. We are always learning, by the way. So we are never perfect in any deal. We are always trying to learn what we did well, what we did not do well. So we apply that to the next one, both internally and externally. We game film everything. Every deal of every size goes to our board for a postmortem after the first full year. If it is not good, it goes to a second year. So there is discipline around this. I would say the easier parts for us to diligence is sort of market attractiveness, competitive intensity, market growth rates, generally. That, we generally do a pretty good job with.
On the business specific things, we have done a pretty good job on the tech stack, understanding if it is a hornet's nest, understanding the scalability, sensibility of the tech stacks. Obviously, the product market fit, the right to win, the customer attribution of why they buy and why they do not. So almost by process elimination, like what is left is like the go to market, and generally the commercial function, and this has like been the most difficult, challenging part of Procare Solutions. I think the hardest part is like, what is driving the historical success? Is it like a cult of personality of a leader that is driving it? Is it like real process repeatability? Sometimes those things in the diligence process can be masked a little bit where you cannot get to the real root of that.
You can see the pipeline, you can sort of vet the pipeline, but how did the pipeline get built? That's been almost by definition of what's left over has been the commercial parts.
Yeah. That makes a ton of sense. Jason, maybe turning to you talked about maybe the opportunities being more kind of like 2027. But your leverage right now is about 3.4x net levered. You guys have talked about having $5 billion of annualized capital deployment capacity. What would you be willing to lever up to in this current environment?
Yeah. Look, over the past 10 or 15 years, we've levered up a couple of times for some larger assets, and we've always delevered after that. We generate a lot of cash flow, so obviously, we're mindful of the environment, but back to the point of shopping, if there's just some very unique opportunities to compound free cash flow per share, then we're going to do it. But we're also committed to delevering shortly thereafter. So we want to stay investment grade, of course. That's a table stakes for us.
Neil, you mentioned buying back 8% of your shares this year. How are you thinking about that decision, whether to continue to buy them back, where your shares are today versus deploying capital through M&A?
Right, wrong, or different, we think about the capital allocation as just math. There's no emotion attached to it. It's just math. Our math is, what's better on a cash flow for share compounding basis, 5 and 7 years in the future, not like in the next 12 months?
We're constantly evaluating, is it better to buy our stock back? Is it better to do capital allocation M&A, this bolt-on? That's the way we think about it. Mathematically, as we all know in the room, the numerator compounds faster than the denominator. Mathematically, M&A has an advantage as it compounds faster. That's how we think about it. It's just a capital allocation trade-off. Put in perspective, what we did a year and a half ago, the CentralReach and Subsplash deals, those were, as I mentioned, they're like 22x NTM. Obviously, a different valuation era than we are in today. We underwrote those like 9 or 10x year five, as I talked about earlier. At the time, we could have bought our stock back at roughly 15x year fie. So there's like a 50% risk premium-
which I think is extraordinary. That's extraordinary risk premium. We don't need that 50% risk premium. We just bought our stock back at 9 or 10 times or something.
Call it 10. Round to 10x , something like that.
Yeah.
That's where we can buy our stock back, ish today.
We need to underwrite to a risk premium that's 20%-30% better than that. We need to underwrite to six, seven, eight times EBITDA to year five to make the math work on a risk-adjusted basis. That's like in today's valuation environment. This is very dynamic.
Yeah
Because where we can buy our stock back and versus at private prices, it's a teeter-totter balancing equation of capital allocation math.
Makes a ton of sense. You talked earlier about your organic growth framework and, today it's kind of like been single digit plus, but we've talked in the past, it's something closer to high single digits. Clearly, this whole discussion around AI is going to be an enhancer over time. You're buying businesses right now that are growing faster than the portfolio. Is there potentially more addition by subtraction in the portfolio today? Then how are you thinking about the other pieces to get to that high single digit longer term growth profile?
On the portfolio construct, we have been pretty aggressive over the last five or six years on the portfolio. We sold 40% of our revenue in 2021, 2022.
Yeah.
Basically exiting our industrial and project-based businesses. We are certainly not afraid to do something if there is value to be unlocked for a shareholder. The math, though, is we are not a public private equity firm. We own things on the Roper balance sheet. From a tax perspective, there is leakage when things exit the portfolio. But under certain circumstances, if there is a buyer to pay X for a price, we have the tax leakage, we can redeploy it and put the shareholder back in a better position than we started, we would consider that. It is a math exercise like I went to before. Unfortunately, that math is quite hard.
It just does not pencil out that frequently. Basically, it never is penciled out. But conceptually, it could. On the growth side, I would say it is interesting that I am simultaneously encouraged and frustrated on organic growth. We have the potential, very clear potential pre-AI to be a high single digit consistent organic growth business. It has been frustratingly difficult to get our chin on that. We are doing all the right things in the portfolio. The leadership teams, the leadership CEOs, the teams themselves, the product velocity, the go-to-market commercial execution, is all sort of seeming in the right direction. AI is going to be on top of that. We just have to demonstrate that across a broad swath in a portfolio.
Last year was frustrating because 17 or 25 of the businesses did what they needed to do, and then three or four of the larger ones had market sort of challenges. It looks like there is a macro thing, when underneath the hood, there is a lot of good stuff happening. I feel very comfortable with the lever of the organic growth. It is just taken us a little bit longer to get there than we wanted to get there.
Got it.
It's every about systematic structural repeatability, not just flashing the fan growth.
We're bumping up on time. Assuming we're here a year from now, what are you hoping to be able to say to us a year from now based on where you see the business trending over the next 12 months?
I think it'd be fantastic if we could say, to answer the question the gentleman asked in the audience, what is the rate of growth acceleration going to be on organic growth because of AI? If we can be, "Hey, we got these 18 or these 12 businesses that are doing this, which adds up to that, which means there's X basis points of growth on the fleet enterprise growth rate," it'd be great to be able to say that in a year.
Hope you can.
Yeah.
All right. Good to see you guys.
Appreciate it.
Thanks for coming.