Name: Tom Eggemeier | Cube Conversation
Uploaded: 2026-02-10T18:00:00.000Z
Duration: 26 min 27 s

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Tom Eggemeier | Cube Conversation

John Furrier

>> Hello, I'm John Furrier with theCube here in our Palo Alto studios, here for an exclusive cube conversation with Tom Eggemeier, who's the CEO of Zendesk. Cube alumni, recently came on at AWS Reinvent where AI was really ramping up. You're starting to see the AI infrastructure plays really pan out. Tom, great to have you back on here in our Palo Alto studios.

Tom Eggemeier

>> Great to be here, John.

John Furrier

>> So the AI infrastructure is a booming category. You got MWC right around the corner and the theme is quantum and intelligent infrastructure. You guys are playing in the agent, I call it the agent layer, big time. Take us through what's on your agenda this year, because this is now a whole nother level of, got to have the right data, it's got to be in the right format. You got to have the demand. What's the update?

Tom Eggemeier

>> We're seeing the demand, and I know the MIT study that was largely quoted in 2025 said 95% of C-suite are not getting the value from AI. We're seeing the opposite from our customers, is they're getting a lot of value. And people and our competitors are giving that value as well. But they want to go adopt it even further. They want to go get even more accuracy, more quality, more personalization and more adoption with their customers. And so we're seeing 2026 is really the year of adoption, and their year to take those, accuracy up, quality up, and to take automated resolutions, solving customers' problems.

John Furrier

>> I'm really glad you brought the MIT study up because I've been really poo-pooing it. I've been poo-pooing it from day one, but there's a lot of experimentation going on. So there will be, not failures, but misfires.

Tom Eggemeier

>> Totally.

John Furrier

>> And we just covered NRF, which is the retail show in New York. There were specific examples of companies hitting record revenue because they got in agents early. Take us through your thoughts on this, and how in the customer service scale and that data, it's not just a cost center problem. It's a revenue generating problem. And I think if you look at the successes of the ones who did the right selection of pilots, went into production, record revenues, that's a number.

Tom Eggemeier

>> Yeah. We really have talked to a lot of customers and they're not seeing it. Some customers are definitely doing cost-cutting from customer service and AI. A lot are saying, "I can go solve a lot of my easy to medium complexity problems, and take that as a service dividend to go drive revenue, to go drive loyalty with my customers through personalization." I was just on the phone a couple of hours ago with a Zoom call actually with the CEO of a two-sided marketplace. And she was, "I want to go save money here to go reinvest into service, so I can drive my buyers and my sellers to have better personalized, more human empathy experience by getting rid of all the easy stuff or the low friction stuff." And I think that's what a lot of CEOs are seeing right now with AI.

John Furrier

>> The strategy has been clear. Infuse AI in your business. So I think there's not a strategy problem. There's more of an execution, project selection, which workflows. Take us through how you see that, because now you're looking at certainly changing the workflows, but also the business benefits that are going to come out on the other side.

Tom Eggemeier

>> Totally. I think you're right on, John. For Zendesk, for instance, we always had a value proposition of easy to implement, easy to use. You do not need services. You have to have the best product and the best platform in AI, but you also have to have the best partners and the best services. Because number one, it's a change management journey, where people are used to doing workflows. They're used to doing tasks a certain way, interacting with their customers. You need to go turn that on their head and reinvent workflows, do things in a different way. So it's change management, it's workflow re-engineering, it's root cause analysis. It's using your data for post-training of models. All these things are new and they require a lot of services. So it's no longer press one button and everything's beautiful. You really need to go to work to get the automation you want.

John Furrier

>> I really like about Zendesk because you guys always had a great product. There's huge need for it in the digital business, even pre-AI. But now that you have AI, you have a lot of data. You're in the data business, basically. You have a lot of things to work on and there's new data coming in. Talk about how you guys see the platform, and your customers adopting that value. Because you have a historical perspective, enterprise has a high bar of failure. You can't hallucinate in the enterprise. If I hallucinate on Chat GPT or Gemini, I just type for another prompt. You can't really do that in the enterprise, you got to get the accuracy. So that's a high bar. But you got the data. Talk about that relationship and what customers are doing right now.

Tom Eggemeier

>> Yeah. Well, there's really two things we're seeing. First, conversational, just answering questions. The data and the context is really important. And to be able to go take that data, like you said, scrub it, making sure that it's giving the right accurate answers important. And then Agentic's a buzzword, but actually making it actionable. So have the conversation with the customer, but action into back office systems is really important. And where we see the data is we've called something a learning loop, that sometimes you're going to have AI agents solve a problem and you want to put that into the system on how they're solving it. Sometimes a human agent is going to solve the problem and you want the AI to learn from that. And we think really having an end-to-end platform to use the data, to keep getting accuracy better, to keep getting empathy better, to keep getting personalization better is really a differentiation. So we think data is important. We have over 18 billion interactions now in our database, with either a thumbs up or thumbs down. Did it go well or did it go poorly? And we're informing our models based upon that data.

John Furrier

>> I love the whole data piece, but you mentioned earlier a service dividend. Explain what that is, because I think that's a clever way of saying you get a dividend from what you are doing, which is revenue. It's a benefit. Talk about what that means and what does that look like in practice?

Tom Eggemeier

>> We've seen most companies when they interact with their customers, whether it's business customers or consumers, they're spending 50 to 75% of their interactions on low to medium complexity things that quite frankly, you should be able to automate. They're simple things that you should be able to automate. A lot of companies have asked, "What do I do with that savings once I automate those?" And what we've advised customers is you probably have a list of 100 things that you've always wanted to do to get closer to your customer, to increase the loyalty loop, to drive more revenue. And you can go start tackling those things in an intelligent way now, because of the service dividend. That you've saved so much money from going on these basic things that you should have been able to automate in the past, but we haven't been able to until Agentic and large language models came to be.

John Furrier

>> Yeah. And that's a great benefit because reinvest back into the team, understanding where the technology's going. That brings up the tech speed velocity. So you got a lot of velocity on the technology side. You mentioned change management earlier. What's the, I won't say gap or what's the... Is there a lag on change management or how are you guys seeing customers keep pace of the technology with the change management, not only for the people in the company, but also their products?

Tom Eggemeier

>> I think it's really hard. It's even hard for me who we're transforming our company from a SaaS company to a AI company, and to keep up every week or every two weeks. I know we were talking a little beforehand, just the rate of change is amazing. And so we think the technology is there. It's more about a change management, and it's more about making sure that we're experts in service and we can deliver that to our customers. Because our customers are not going to be able to be experts in AI service, AI sales, AI marketing, AEO, all these new things that are coming out. So we need to be not only product experts, but also service experts. How you do the change management, and how you can get the benefit of this technology with your company.

John Furrier

>> We've heard that on theCube interviews that the change management, also the people side of it is a bottleneck. Used to be people, process technology, now it's the AI agents are coming in. But the change management's the bottleneck. What mistakes do you see companies make that kick in? And what should they avoid?

Tom Eggemeier

>> So first of all, I think they should give their vision, because a lot of companies want to do this service dividend. And so I think employees are worried, is AI going to take my job? In some companies, it is. And I think people should be realistic and tell them about that. But if it's not, they should give them the vision that we are going to have this service dividend. Your nature of work might change. You might be an editor instead of a doer. You might be working on workflows and getting data from AI, how to solve root cause. But you need to lay that up front, because that is the number one thing on an employee's mind. Is this going to impact, am I working myself out of a job by helping the change management in AI? And I think you need to be upfront on that.

John Furrier

>> You mentioned working yourself. What's the job security angle? Because the metrics stay the same in your business. Resolution, service, there's outcomes that are well-defined, but how does that change the job security piece? How do people think about that?

Tom Eggemeier

>> I think it's tough. I've got a 23-year-old daughter and a 20-year-old son, and they are asking me like, what should their career be? And 10 years ago, the easy was learn to code, right?

John Furrier

>> Yeah.

Tom Eggemeier

>> Learn to code and you're going to have a job for the next 50 years. I keep telling people, and I tell our employees, learn how to prompt. You need to be a good prompt engineer no matter what job you are, learn how to speak and write well, learn how to analyze things. And if you have those skill sets, you're going to be fine. Because I really do think the nature of work is going to go change over the next three, five, 10 years. And it's all going to be about skillset. I'm a big liberal arts person. And so I think having a liberal arts background, along with an engineering background, can really prepare you for how the nature of work is going to change.

John Furrier

>> It's a good point about the liberal arts, but I think the holistic thinking that most people say, "Okay, what's the skill?" Understand the big picture. In tech, it's a systems game. You're seeing order of magnitudes, also collateral effects when you make decisions. So thinking holistically is huge. That ties to on the human in the loop piece, but also the system side of it. When I want to deploy a workflow, I got to know how it works end to end. So you're in a unique position with Zendesk. You got the workflows, but also you've got this human piece, which is, "Okay, I can curate, I know the domain." Explain the difference between the domain expertise, workflow, and the human role.

Tom Eggemeier

>> Yeah. We think it's going to become more and more verticalized over time, where you're not going to just have an AI agent or understand the platform and the system. You're going to have to understand it for E-commerce, or you're going to have to understand it for government, or you're going to have to understand it for any other industry, transportation or whatever. So we think it's going to first, that system is going to be more verticalized, more industry-specific knowledge. Second, you're going to have to understand how systems work together. I was with a customer in the UK last week, and a lot of our discussion was, how they can change the workflows and integrate into 40 different systems to actually go from conversations, to actions or agentic. And so that systems level thinking and really understanding the whole system, as you said, John, is just increasingly becoming important, because you're not going to get the value of AI unless you interconnect it with a lot of different things.

John Furrier

>> Yeah. Look, this question just comes up a lot with agentic infrastructure and data that you're living in right now, that's scale. Talk about the impact of scale to a company. We see a lot of demos, vibe coding, they're getting better. Now you get a lot more code assistant, still the humans in the loop, but the scale is pretty significant. You've got billions and billions of data. Customers are dealing with a lot of data. So agents will be there in your world. You're going to have to be very agentic.

Tom Eggemeier

>> Right.

John Furrier

>> How does scale change things, competitive strategy, product strategy, customer benefit?

Tom Eggemeier

>> Well, I just think scale is really interesting. And a lot of times in the past, you wanted to be just an enormous company to have enormous scale. I worry those companies aren't being nimble enough because AI is changing every couple of weeks. On the other hand, you've got startups who don't have the experience and scale on advising customers how they go through the change management. So we think a sweet spot is companies that are big enough, that have enough data. For instance, last year we processed over 800 billion API requests and we'll do over a trillion this year, just to give you an idea of scale. But we're taking that, we're small enough that we can take that information and really personalize it, make sure that our customers are using those requests. The API request for me is a good indicator of actions on the backend, that they're actually taking actions. And so I think we're getting to this world where in the past, just a couple hyper big scalers were the winners. I don't think that's going to be the case because I wonder if they're going to move quick enough.

John Furrier

>> Yeah. Talk about some real world examples too, that you're seeing. That's billions of transactions. What are some real world examples that you're seeing benefits now that people are doing?

Tom Eggemeier

>> First of all, I'm seeing a lot of our customers pass the more than 50% threshold of getting automated resolutions. And so what I'm seeing is customers are able to go solve their customers problems with their business or consumers, and they're getting higher customer satisfaction. One of our customers, a retail company called Motel Rocks. They just passed the 50%. They're more about 60% automated resolutions, and their CSAT, their customer satisfaction went up about 10%. I think it was like nine point something percent. And so I'm seeing this right now with the service dividend. You're automating, you're making it quicker for your customers. I know for a lot of my interactions, I just want it done quickly and effectively, and that gets me high customer satisfaction. So I think companies are able to really do that effectively right now.

John Furrier

>> We were talking about the hype side before we came on camera here, but also we've been seeing some examples out there. How is the hype impacting the business? And because there's not yet a playbook. Can you share some playbooks or best practices you see, and how does that differ from the hype?

Tom Eggemeier

>> Yeah. So first of all, I think the hype, boards and CEOs are expecting that they can press two buttons and they will just get massive benefit from AI. And I think we're crossing that right now where people, to our earlier conversation, are understanding they really got to work at it and they really got to do service. And so we've spent a lot of time the last year taking off camera conversation, failures. Things that didn't go as well when we tried things, and successes to try to go replicate that with a playbook for specific verticals with our customers. And I think that's what's happening right now and that's why it's the year of adoption. People are finding those good lessons and bad lessons. All lessons are good, on how to go do that change management, how to go structure data better, when to go use AI, when to go to a human, when to go to an AI agent versus you can do a plain old generative search on a knowledge base, frequently ask questions. When to go use all these tools to get the customer the best answer possible.

John Furrier

>> I think the accuracy is clearly one. We just talked about that. You mentioned AI native. What does success look like from an AI native perspective? A lot of people are hand waving. We're AI native. They've written wrappers into Chat GPT. That's clearly what they're doing, other methods, but you start to see more deeper startups come out. But how does the customer determine like, "Wow, this is an AI native company and this is the real deal." So how do you determine what does that mean, AI native? Can you give some examples? And how do customers do the smell test?

Tom Eggemeier

>> I think it's tough for customers right now because it's the early, I'll use an American metaphor, the early innings, the early, the first 30 minutes of the soccer game. To really understand what matters the most. We tell our customers, worry about the platform, meaning you need to go solve your customer's interactions no matter how they come in. And if you're just solving one part of it, so think holistically, think how you can use the data from a learning loop. We say, are people investing enough in AI? And I can tell you right now, we announced a couple of weeks ago on LinkedIn, we passed $200 million of AI ARR last year, and we want to go double that again this year. And we're putting a ton of research and development into this. And so I think there is a bar on you get benefit from scale, you get benefit from data, whether you're AI-native or not. But if the company doesn't believe, if they're a SaaS company, and they don't believe they're going to have to be an AI company in three to five years and totally change their model. I have a question whether first they're going to be viable and second, whether they're really the company you want to listen to from an AI perspective.

John Furrier

>> It's almost two sides of the street here. There's the right side of history and the wrong side.

Tom Eggemeier

>> Right.

John Furrier

>> People do have the fear of missing out and also the fear of getting screwed over. No one wants to... This is a fatal flaw if people don't adopt and the business side don't get AI right. You're starting to see people understand this, but then have to ask, okay, this is the year of execution, this is the year of proof, this is the year of ROI. A lot more ROI conversations in this world we're in now it's like, okay, love agents, I can see the benefit. Oh yeah, there's some technical things going on, MCP servers, all this stuff, but at the end of the day it's like, did it work?

Tom Eggemeier

>> Totally. I think the last couple of years we had a lot of proof of concepts, a lot of trials competing against other competition. When I talk to C-suite and other people, now it's like, how do I go from 40 to 70% resolutions now? How do I go get more use cases, and how do I plug into other systems and get truly agentic? People want to experiment still, but they want hard results. And the metrics they care about are those resolutions because they think that, and we agree, that's going to impact customer satisfaction, going to drive revenue, going to drive loyalty. And so last year and the year before, I think we're a little more of the, let's try it out, let's experiment. I'm hearing a lot more now from the C-suite, let's drive business results this year.

John Furrier

>> I want to ask your thoughts on cloud. I know we talked a little bit about Reinvent. The IT service management has the word IT in it, so it implies on-prem. Certainly the cloud game powered in SaaS. So the first generation was print, paper, internet, mobile cloud, that was a great run. Now we're in transformers AI, that's through that. Now we're agents to fully autonomous systems. That's going to be, could be a five year if you accelerate down, call it 10, five, 20, 10. Huge generational shift in how business gets done, human work you mentioned. What is the impact of this idea of cloud, scale? How are companies thinking about that piece of history? Because if you have autonomous, that's going to be a generation run. So people are not scared, but they want to make good calls. I'm seeing AI infrastructure decisions being made because of Agentic. How do you see your business evolving in that world?

Tom Eggemeier

>> Well, I think you nailed it. If you think some big changes in the last 25 years, you had internet, then you had mobile, then you had prem to cloud, but prem to cloud, it's still going on. There's a lot of premise software out there. So this has been a, I remember ASPs, that was the first thing in the 2000s, Application Service Providers. And so this has been a 25-year change in prem to cloud. What we tell our customers is this is going to be a three, five, max 10-year change where companies are going to go from using SaaS applications to be using AI applications. And they still probably have a year or two to experiment and to get it right, but they're going to be making some big decisions on how you go use your data, whether that's Snowflake, or that's Databricks, for instance, what service providers are you going to use for your employee and customer service? And so I think there's a lot of experimentation, a lot of good decision making about prem to cloud, but this is going to be quicker decision making. And so I think it's to your point earlier, like it's hard to cut through, who is really investing, who has a good demo versus who's going to help you drive value?

John Furrier

>> I love not a demo, it's real value. I talked to a lot of people who are in the service, catalog, service, ticketing, the business that you're in, which is a lot bigger now than that. And the general comment has been, I've been with the same company that locked in." And they say that privately, locked in, because they have software agreements. And so you had that IT stickiness that went away with cloud, but okay, I just lifted and shifted. I didn't really do anything re-imagining it. We're seeing now with AI native re-imagining those workflows. If you got the data like you have, you understand the workflows, there's now opportunities to take share for Zendesk, a AI-native startup could come out of the woodwork. So there's opportunity to disrupt and accelerate this area that you're in. What's your thoughts on that? What's your reaction?

Tom Eggemeier

>> Yeah. So we tell our employees, I tell my fellow Zendeskians, this is an existential crisis, but most importantly, it's an existential opportunity for Zendesk and our customers, and our potential customers. We saw about an over 30% uptick in new customers in the second half of last year versus the first half of last year. And I think that is a lot of customers that are thinking, "If I'm going to go invest in AI in this big change management, I should go look at my whole service platform and what is going to get me for the next five or 10 years." And so we see it as an opportunity. We think we gained share in the second half of last year by really having a nice uptick in new customers. But I do agree with your premise. This is a unprecedented opportunity where customers are in the driver's seat. The switching costs are probably lower right now, but the impact is higher than ever on getting it right on the right service platform and the right AI platform.

John Furrier

>> I was just watching a couple of videos around management tech and AI error. One, acceleration is so fast now, so you can actually, with all the coding assistance, you can be more nimble. And then more thinking around reverse benchmarking and other tactics where it's like, wow, I want to take share. I don't necessarily have to copy someone else. I can just do what they don't do better. Zendesk is in a good position. You guys have a lot of opportunity. You have the install base, you've got data, you got the workflows. How do you feel about that opportunity and competing on that value?

Tom Eggemeier

>> So the opportunity is great and we think we've got a really, really clear strategy. And when we talk about a strategy with our customers and internally, it's AI, AI, AI. Those are our top three priorities. It's all about execution right now. We've got 80,000 customers, like we talked, 18 billion interactions that we have rated, good or bad. We've got the right products with AI agents, Copilot, our AI QA, in free products like our AI generative search on knowledge. It's all about execution. And execution is not just selling a customer doing a proof of concept like we talked about. This is the year about making sure that our customers get the promise of AI, get those adoption rates. Our best customers right now, get the adoption rates, get the ROI, are driving the service dividend, but it's not enough. We need to drive all of our current customers and potential customers to go get that value this year.

John Furrier

>> I love that we'll show you the proof, but also your product gets better too. You have opportunities to increase product velocity for the customer.

Tom Eggemeier

>> Totally. We try to measure, and it's always tough to measure on product velocity, how you measure it, but we think our organization is doing somewhere between two and 3X what it was from three to five years ago. Part of that is AI. Part of that is a great management team that we have running our product and engineering team. But the velocity of change is really high in products. And I know our customers was always like, "We didn't know you had that." And so this is part of the change management. With the velocity going up, we need to make sure that our customers and our potential customers know about all the great innovations.

John Furrier

>> And you got to market the value. And that's one of the things that what you have now is a great benefit. Final question, more personal, not personal, but a curious question. You just had your sale and company kickoff, you're visiting some customers outside the United States. What's the vibe? What's the sentiment from the troops? What's the reaction about, one, where Zendesk is, where they are and what the value is?

Tom Eggemeier

>> So I think the team is really, really excited. They say they haven't seen this kind of opportunity in 10 years to go make a difference with our customers and our partners. And so really excited about that. They do have a question, how can I keep up with not just our organic change, but also what's going on with the AI industry? So you're a person. I always use Malta as an example because it's usually non-confrontational. The person in Malta, the Zendesk employee, how do they keep up with what's going on in AI, and what's going on at Zendesk and what's going on with their customers? And so excited, want to go drive with the year of adoption with value to our customers, a little scared that the pace of change that's going on at Zendesk, in the industry at large. But I really think they see the value that we drove from our customers and they're excited about it.

John Furrier

>> Well, you're in the sweet spot because it's a board level mandate and the ROI shows up where you are.

Tom Eggemeier

>> Yeah. I think other places are having a more difficult time showing the ROI, but I think with software coding, with the large language models themselves, and then employing customer services are really clear ROI, whether you take things to the bottom line, whether you go with more customer satisfaction or you do a service dividend, really, really clear differentiation.

John Furrier

>> Well, Tom, great to have you on. Continue the conversation. Final question is, what's up for this year? What's on your agenda? What are you optimizing for? What's the focus?

Tom Eggemeier

>> The focus is making sure that we have an impact with our customers. Every morning we're reviewing what resolutions our customers, how much automation that they were to get, whether that's through the human agents or their AI agents. We look at those statistics every day and like, how can we go do that? And then from a leadership perspective, we want to make sure that the world knows that we are an AI native now and that we're delivering so much value for our customers. And then for our employees, we think this is just an unprecedented opportunity for them. I tell them, you're going to have once or twice in your lifetime that you're going to be able to write the playbook that everyone's going to use, to how you go reinvent yourself from a SaaS company to an AI company. Every SaaS company is going to do this the next 10 to 20 years. You have an unprecedented opportunity at Zendesk to be one of the first companies to go do that.

John Furrier

>> And you're touching the most critical piece, which is the end user piece. That's the edge of the network that's going to be more wearables, robotics. There's so much going on at the edge, connectivity's there, the data's coming in, just a lot of headroom.

Tom Eggemeier

>> A lot of headroom. And you're going to see really cool things, John. I think people are starting to experiment more. We talked about it 12 months ago, but you're going to have your own bot, where you're going to be telling your bot to do things and not just conversational, but actually agentic, actually do the action. Where that wasn't possible. So you're going to start to have even more bot-to-bot conversations with the edge.

John Furrier

>> Well, Tom, I'll have my agent call your agent for the next interview.

Tom Eggemeier

>> That's perfect, John.

John Furrier

>> Came in for theCube. Thanks for coming in. Appreciate it.

Tom Eggemeier

>> Thanks for having me.

John Furrier

>> All right. I'm John Furrier with theCube. Exclusive Cube conversation here in Palo Alto. Thanks for watching.

Tom Eggemeier | Cube Conversation

John Furrier

Tom Eggemeier

>> Great to be here, John.

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>> Totally.

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Tom Eggemeier

>> I think it's tough. I've got a 23-year-old daughter and a 20-year-old son, and they are asking me like, what should their career be? And 10 years ago, the easy was learn to code, right?

John Furrier

>> Yeah.

Tom Eggemeier

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Tom Eggemeier

>> Right.

John Furrier

>> How does scale change things, competitive strategy, product strategy, customer benefit?

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John Furrier

>> Yeah. Talk about some real world examples too, that you're seeing. That's billions of transactions. What are some real world examples that you're seeing benefits now that people are doing?

Tom Eggemeier

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John Furrier

>> It's almost two sides of the street here. There's the right side of history and the wrong side.

Tom Eggemeier

>> Right.

John Furrier

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John Furrier

>> I love that we'll show you the proof, but also your product gets better too. You have opportunities to increase product velocity for the customer.

Tom Eggemeier

John Furrier

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John Furrier

>> Well, you're in the sweet spot because it's a board level mandate and the ROI shows up where you are.

Tom Eggemeier

John Furrier

>> Well, Tom, great to have you on. Continue the conversation. Final question is, what's up for this year? What's on your agenda? What are you optimizing for? What's the focus?

Tom Eggemeier

John Furrier

Tom Eggemeier

John Furrier

>> Well, Tom, I'll have my agent call your agent for the next interview.

Tom Eggemeier

>> That's perfect, John.

John Furrier

>> Came in for theCube. Thanks for coming in. Appreciate it.

Tom Eggemeier

>> Thanks for having me.

John Furrier

>> All right. I'm John Furrier with theCube. Exclusive Cube conversation here in Palo Alto. Thanks for watching.