How ZoomInfo's CEO Rewired a 3,500-Person Company to Be AI-First with Henry Schuck

0:00So how did Zoom Info CEO Henry Schuck rewire a 3 ,500-person company to be AI first? Stick around. He's about to tell us.

0:17All right, welcome humans to episode 10 of the Neuron AI Explained. I'm Corey Knowles, joined as always by our resident wordsmith and rabbit hole navigator extraordinaire, Grant Harvey. How are you today, Grant? Good. I'm diving into all the rabbit holes of all the rabbit conspiracies that we mentioned in one of our last podcasts for all the rabbit truthers. No, I'm good. How are you, Corey? I'm good, man. I'm good. I'm sure. Glad, excited about this one today because today we're tackling a question that is keeping teams and executives across the business world up at night. How do you lead an AI first team without burning mountains of cash or your people.

1:02To help us out, we've recruited Henry Shuck, founder and CEO of Zoom Info. Henry turned a scrappy contact data startup into a 3 ,500 person go-to-market intelligence machine powered by its own generative AI co-pilot. We'll break down the cultural shifts, the data hygiene, and the hard metrics that prove the tech is really working. They're doing some great things over there and I really think you'll be fascinated with it. But first, before we dig in, Grant, what would you say it means to be AI first? So this is an interesting one. Being AI first means that a company, product, or strategy is designed from the ground up with artificial intelligence as the core enabler.

1:48So rather than treating AI as an add-on or an enhancement, they're actually trying to build AI into the core mechanic, like basically into the core mechanism of how it works from the jump. As opposed to it being like, you know, the little deer antlers around Christmas you see on the side of a car. Instead of that, it's building it into the engine and making it important. Which is kind of how a lot of products have built AI into their, like, well, actually a lot of companies have built AI into their products at this point. It is. Where it's like, you're just kind of throwing it on top of what you already have and making a little chatbot.

2:25And a lot of people are like, this is kind of bad and not good. And it assumes this is as good as AI will ever be. It assumes that, oh, this is great. This is what it is. It doesn't assume that that little bolt-on is going to be irrelevant in three Thursdays. Whereas being AI first as a contrast is saying like, okay, we need to rethink our entire organization and our entire product. product and whatever you do from a standpoint of AI is here, let's build it into the core mechanism of it. Exactly. And I don't think there are many people more equipped to talk about going from being a traditional company to an AI-first company that's seeing huge results than Henry Shuck.

3:07So let's scoot on over to Henry here and let him talk to us about it. So what does it take to steer a 3 ,500-person company into the age of generative AI. Zoom Info founder and CEO Henry Shuck joins us today to unpack the company's journey from data powerhouse to AI-first GTM platform, the cultural shifts that enabled it, and the hard-won lessons any leader can borrow. Henry, it's exciting to have you on. How are you today?

3:35Henry Schuck:Great. Thank you for having me, Corey. Absolutely. Absolutely. So when did you first realize that AI had to be the core of the Zoom Info product roadmap? When was your like AI aha moment? Yeah, look, I think it actually happened in two ways. I think one was we always knew that we sat on this really proprietary data set. And we had data about 100 million companies and 500 million business professionals, all these unique business signals that were happening at those companies. And we constantly battled with the idea that our end user, in order to really get value out of all of that different data, they had to cross-reference this data with that data.

4:27Henry Schuck:They had to go look at intent data and then people who visited their websites and then scoops. And is this company in my total addressable market? Are they a company in my territory? Are they an assigned account? And so in order for you to really take advantage of all of the data inside of Zoom Info, you had to be like a power user. You couldn't just be like a regular user who came in and got advantage of all of this signal and all of this data. and endlessly I would talk to clients and they'd be like, oh, I didn't know you guys did that. Oh, I didn't know you guys did that. Oh, you guys do intent data?

5:02Henry Schuck:It's like we've done it for 10 years. Well, we didn't know you guys did that. And so I think the quick aha or the first real aha moment for us and for me especially was when you saw that one of the early things that we saw generative AI be really great at was taking a whole bunch of data, making sense of it and then giving you the most important pieces of it for your daily life. And so we realized, hey, if you could just take all of this data that we have on companies and people and signals happening at those companies, you can marry that up with the customer's first party data. So you know which accounts are theirs, which ones are in their territory, which accounts they care about, and then actually bring together that first party data underneath their emails they've had with those accounts, the engagements, the calls, the call transcripts, then that could much more easily triangulate which accounts you should be reaching out to and what you should be saying to them based on the signals and the first-party engagement.

6:06Henry Schuck:And you don't need to be a computer science PhD to pull that off. And then you don't need the world's greatest UI experts to create the perfect UI to do that. you really need that underlying LLM engine that can go triangulate that and deliver it to your end customer. I think when we first saw that, we realized, okay, this is going to help us solve a lot of really meaningful problems that our customers are having when they want to leverage the right data, the right signals to go to market. Wow. Yeah, that's super interesting. And when I think about that with software, one of the things that comes to mind is how often people underutilize the features that are there just because of how much there is to learn in every tool.

6:50How big of an undertaking with knowing that was it to get ZoomInfo AI ready?

6:56Henry Schuck:That sounds like it was a lot. Yeah, look, I think we benefited from a couple of things. One, we sit on this proprietary data asset. And so we didn't need to like fully pivot the business. We just needed to make it easier for our customers to get value out of that underlying data asset. And so that was one thing. But I think like the big thing was you had to we had to change the way we were thinking about building software for our customers, where a lot of that was focused on the application layer and how you improve the application layer. And we really had to shift people to start thinking about how do you improve that underlying data layer that drives insights up to the application layer.

7:37Henry Schuck:And so, you know, the platform itself, the ZoomInfo platform itself, when you log in, you know, we are gathering data on these 100 million companies, 500 million business professionals. We're gathering them from a multitude of different sources. We have hundreds of thousands of users who use our community edition, who get free access to ZoomInfo in exchange for their contacts and their email system. We have tens of thousands of SMB customers who integrate their CRM, marketing automation systems, their email systems, that we get data from those systems. We look at that data. We cleanse it. We validate it.

8:18Henry Schuck:We use that data to triangulate other data that we have. We go out and index the B2B web. And so press releases and announcements and case studies. We bring all that data together. and then you could see Cisco, the company, in 19 different places in one day. You see it in a press release, you see it in a customer CRM, you see it in a person's email contacts and how do you make sure that every time you see a Cisco that you actually roll it up into the right Cisco at the account level so you have one Cisco? Because when someone goes to look for Cisco, if you go look in your CRM today for Cisco, there are probably 17 instances of Cisco.

9:02Henry Schuck:There's an open opportunity, there's an old account, there's a new account, there's a new business account, there's a existing customer account. At ZoomInfo, we need one Cisco. We can only have one Cisco. And so if you think about that as like a master data management problem, the deployment of master data management to publish ZoomInfo's product is likely 50 times bigger than the largest Informatica MDM deployment in the world. And so we were able to bring that technology that we already had built and then make it available for our customers and place it in the platform so that when our customers integrate their first party data, their CRM data, their call data, their email data, that that same technology that takes the core Zoom info data and publishes it is now available to our customers to take all their data, enhance it, enrich it, normalize it, perfect it.

9:59Henry Schuck:And then that's the layer of data that we're using to build AI insights on top of. And so we were able to borrow from different technologies that we had built around the business to get a step ahead as it came to really driving an AI first mentality, not just for us, but for our customers as well. But largely, when we made this realization about, oh, the product can be so much more simple for our customers, they could actually get more value out of it. We did a pretty hard pivot behind AI products. And it was basically like you could think about kind of 80 % of our engineering teams then shifted focus to building AI first products for our customers.

10:44Wow. Wow. That's such a big shift. Well, and then, you know, I also understand And you all acquired Chorus AI last year.

10:53Henry Schuck:I say last year. 2021. 2021. Yeah. A ways back. My apologies. No problem. But how did that change your approach or direction? Has that been a key element? You know, it's so interesting. When we first acquired Chorus, I think AI felt more like something that people talked about, but you never saw well implemented in a company. these tended to be like before chorus all i ever saw inside of our business and i had invested a lot behind ai was a bunch of like academic-y projects people would go like do some data science-y projects almost nothing made it to production it was this incredibly frustrating experience where you put a lot of money behind ai but you never really saw it come to fruition in the platform.

11:42Henry Schuck:Then when we acquired Chorus, Chorus was way ahead from an AI perspective, and they had built a lot of AI technology. And so they kind of led the way or shined a light on the opportunity to leverage AI in the products and the platforms. And then over time, what we found is some of our best AI talent, my chief product officer, our chief strategy officer, they both came from Chorus and they are driving, both of them are driving internally with our chief strategy officer and externally with our chief product officer, all of our AI initiatives. And so you don't really appreciate that when you're making that acquisition.

12:24Henry Schuck:You're thinking more of the product, our ability to take it to market. And then tangentially, you're thinking about the talent that comes in with that acquisition as well. But in this case, the talent is running. The talent from Chorus is running our key AI initiatives in the business. Wow. That's really interesting. And I guess that's a good place to segue into, you know, what does an AI first team look like at ZoomInfo? And how much of it is new team members versus a shift in mindset for existing team? Yeah. So I think I don't think there's a one size fits all here, but I do think there are people within your organization that are well suited to be to become AI native.

13:15Henry Schuck:they're systems thinkers. Like if you think across your business and you think of who is using Zapier right now to automate a workflow inside of the company, that's probably a great person who's going to be great at thinking through how AI helps automate workflow and then how to use agents to automate that workflow even further. So there are people at the company who are well-suited for that. And then in those people, you need to like lift up and highlight. There are places in the business where somebody is getting some information from somebody, then translating that information and then handing it to somebody else who then takes that information and then delivers it out to some other constituency.

14:02Henry Schuck:I think product marketing is actually like a pretty good example of this, where product marketing goes to the product folks. they talk to the product people and they ask the product people tell them what they're building the product marketer goes okay i need to build content for the website based on that product i need to build content for release notes based on that product and what i've been told and then i need to go deliver also unique content to our sales team and our enablement team so the enablement team can then take that and deliver it to our sales folks so they know how to sell the product.

14:35Henry Schuck:And it's a lot of translation that has to happen. And so we thought, look, if you think about that pipeline from product manager to website content, to blog content, to enablement content, we can build agents for each part of that. And so instead of having 26 product managers, product marketing managers who are taking information from the product manager, or translating it in eight different ways. Let's rethink that whole workflow. And let's say product manager, you take all of the communications you've had about this product, every call you've had about this product, everything you've written about this product.

15:17Henry Schuck:We're gonna take that and we're gonna create multiple agents that take that content and translate it into website content, translate it into release notes, translate it into enablement content. And then we don't have to have a 26 person team. We can have two product marketing managers who are focused on automating and improving the agents along the way to get a better output. The closer you are to the raw data, the higher fidelity the output is going to be. And so what we've done is, you know, in the middle, when you write for the website, it's a different voice than when you write for a Gartner analyst report.

15:56Henry Schuck:Yes. Or when you write for enablement. And so we've created agents that we're constantly tuning to understand our tone, our voice, how we talk on the website, how we talk to our customers, how we talk in release notes, how we talk to a Gartner analyst. And so now when we get that content from the product manager, we're delivering better output faster to the end, to down the line constituencies. And we've taken that team from 26 to two. And I think there are probably other, I know that there are other opportunities across our business where that's happening as well. And as agent technology gets more and more advanced, you know, if I have one of my executives told me his team asked him this question and said, like, should I be concerned about my job?

16:44Henry Schuck:And he said, look, if ever there is a job that takes French fries from the fryer and lifts them up and put them over into another bin and sprinkle salt on them, I promise you Someone is trying to build a robotic arm to do that action. And so if you're in a position that's just moving information from one place to another place and sprinkling a little something on it, someone is going to try to replace that job and automate it. And I think there are a number of areas around every business that historically relied on people to move information from one repository to a dashboard somewhere else and click a bunch of buttons and it goes downstream.

17:28Henry Schuck:And that was very valuable to a business. And if you perfected the technology enablement along the way there, you could have a competitive advantage. That just is not a competitive advantage anymore. And those are areas in the business that to be competitive, we have to go use AI and leverage agents to do. And so I think there's a lot more of that coming for one. And then internally, we also focused a lot on how do we build the infrastructure, the data infrastructure for all of our employees to also take advantage of AI and its power and use it in their day to day. And so today we brought together our product data, Zoom Info's data, I'm sorry, product usage data, Zoom Info's product data, that company professional data asset, our financial metrics data, all of our calls with customers, all of our emails with customers, our calendar meetings, all across the business that's in one data asset that now our reps are able to go query and ask questions of.

18:37Henry Schuck:And they can say, hey, today I'm a mid-market rep. Which clients in my customer base should I be focused on today who show the most renewal risk and tell me the reasons why? And then that AI goes through and it says, these are the three, these are the reasons, this is what you should engage with them on. Here's a PDF of a deck that you should share with them. And so we're really driving efficiencies in the business. You know, one of the things I find myself saying constantly to people in the business today is, I don't ever want to ask you this question again, put it in an agent, and I'm going to ask the agent these questions in the future.

19:17Henry Schuck:So like, this is the last time you and I are going to engage on this topic. Like, look, I get a monthly report on sales efficiency or churn or winbacks and then I have, or headcount. And then I have questions. Is this person in this headcount number or that headcount number? How has it trended over the last six quarters? We moved these people to this department. Are they moved in there? Is there a clean compare? And then some analyst has to go look at all that information and get back to me. Like I don't want that anymore. Like I don't want to interact with an analyst who's just going and looking at the data to give me an answer.

19:55Henry Schuck:If I can interact with an agent who has access to that data in the future, it's cheaper. It's more efficient. It's faster. And then we can continue to focus on higher on tasks that are higher and higher up the value chain. And so like, I think my slacks, if I go look across them, like the new most common phrase is let's put that in an agent so I don't have to ask you these questions in the future anymore. That makes a lot of sense. And that's kind of a thing I'm looking forward to as well is really spinning up some of the more annoying, repetitive things I do all the time. Let's just make this easier and have it at my fingertips.

20:36So has this changed then? This leads me to wonder, this has changed how you hire now, like as far as your hard and soft skills that you're really looking for in a new team member? How is that different than it was before?

20:48Henry Schuck:I think about the most in hiring for AI talent today. I mean, there are all sorts of different things that are critically important. You want somebody who's curious, who has the ability to rethink workflows. But when it comes to that, I think the thing that I think about most is, are these people who are systems thinkers, do they think about when I look at an organization, do I step back and think about, okay, if I'm looking at a revenue organization, what is the system that generates the lead, that turns the lead into a demo, that turns the demo into an opportunity, that turns the opportunity into a sale, that then takes that sale and generates the DocuSign to get signed, that then gets reported into our financial systems, that gets rolled up into the dashboard.

21:42Henry Schuck:Am I somebody who can see the connective tissue through all of that? And if I can see the connective tissue through all of that, then I'm somebody and I'm curious and I'm leaned in from an AI perspective, then the very next question that I'm naturally asking is, can I plug an agent in there? Can I plug an agent in there? How do I make that more efficient with AI? How do I drive a better conversion rate over here with AI? I think about it a lot like when you set up like a home entertainment system and something breaks, does your brain work in a way that goes, okay, that's plugged into that and that's plugged into that and that's connected to that.

22:21Henry Schuck:And so I understand all the different break points and I can go figure out where that thing broke. And if I can think like that, then I have the right and I'm curious, then I have the right wrong ingredients to be great in an AI first world. Those are great call outs. You know, that curiosity, the ability to see that step-by-step really programmatic view of problem solving, I think, is very key. On a kind of unrelated note to that, do you have any advice on monetizing AI in the up market and down market in your customer base? You know, our customer base is interesting because we have 35 ,000 customers and those 35 ,000 customers, they range everything from the Fortune 10 to, you know, a small commercial cleaning business in Toronto and really everything in between.

23:15Henry Schuck:And so they all have like very different AI wants and needs. In the upmarket, those like Fortune 100, Fortune 500 customers, they want data. They want our data. They want our data ingested into whatever AI they're building. They want our technology that matches and merges data together. but they want to take all of that data and then they want to use it internally across a number of different AI applications. That's a really interesting business for us. It's actually the fastest growing business within ZoomInfo. It's growing 20 % year over year, more than 20 % year over year. It's our operations business.

23:58Henry Schuck:And it has this incredible tailwind because in the super enterprise, they're hungry for data to build into their internal AI applications. And so we monetize that way. In the down market, they're not building their own AI applications. They want to leverage AI because they recognize that it'll drive efficiencies in their business, but they want it out of the box. And so they want the ability to go pull something off the shelf, leverage that that drives their efficiency. And so we're kind of building solutions, not kind of, we're building solutions for both ends of the market. We're making it really easy to consume our data for the upmarket business.

24:38Henry Schuck:And then we're building out of the box solutions like Copilot and GoToMarket Studio for our downmarket clients as well. In all you've done over the last couple of years here, would you be willing to share maybe a failure story and how you pivoted along the way? Maybe there are two. I think one was, you know, pre us going all in on AI, we were really going all in on this idea of an integrated platform. So we thought like, hey, we have conversation intelligence, we have sales automation, we have the core data asset. Let's just build one platform that's an all-in-one platform that everybody can get.

25:16Henry Schuck:You could get everything you need from a go-to-market perspective out of this. And that integration was hard. We probably didn't have the right engineering or product talent at the time to pull that together. And so that project was like slow going and the pathway to delivering it was not obvious and didn't really leverage our key skill sets either. And so when we first saw the power of generative AI, we had to make a decision to go leave that vision behind and go drive towards a future vision. And I think like that's probably where most large organizations get stuck. there's this innovator's dilemma.

25:59Henry Schuck:Like this is the thing I'm doing. How do I abandon this whole thing and like chase after a new shiny object? I remember being on a trip with a friend of mine who runs a publicly traded software company. And I was telling him how like, I just turned 40. And I was like, you know, I'm 40 now. I started this business when I was 23. And when I was 23, like I was a digital native, I was an internet and web native. And so I understood the internet I was able to like leverage that ability and curiosity to start building a, you know, a data business that then turned into a software business. And I worry now I'm 40 and like, am I going to be able to drive that same level of innovation at 40 as I was able to drive at 23 when I was like deep into these things?

26:47Henry Schuck:And I don't even really know what the next thing is, what, what that thing would be. And he was like, oh, it's AI. It's 100 % AI and you should put all of your energy behind AI. And I was like, okay, I had been like, obviously AI had kind of like the generative stuff had just kind of come out. And I was like, he's right. Like that is it. And if we're not like every day waking up wondering about how AI is going to disrupt our business, then we're going to get disrupted in our space. And so we had to abandon a bunch of other projects that we were working on that we thought were the future of ZoomInfo to go all in on AI.