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How do you move AI from a cost center to a growth engine? Most enterprises are stuck in pilot purgatory, but Rubrik has found a way through. In the latest episode of AI Impact, Ajay Sabhlok, CIO and Chief Data Officer at Rubrik, joins Larridin co-founder and CEO Russ Fradin. Ajay explains why the secret to AI maturity isn't having the latest models; it's the philosophy of doing more with less. He walks through the framework Rubrik uses to move past AI risk to a point where internal demand for AI outpaces the company's capacity to deliver it.
Ajay came up as a hardcore developer before becoming a CIO, and it shows: his approach is hands-on, structured, and focused on measurable results. Several key points emerged.
Russ opens by noting that CIO is a job people talk about constantly without knowing what it involves. Ajay's answer: the CIO is the business catalyst, the connective tissue that keeps the company running efficiently while offering insight into how the business performs. Done well, the role becomes that of a trusted advisor, with marketing and sales leaders bringing ideas to IT rather than dreading the conversation. That partnership extends to HR. With the entire knowledge workforce being retrained at once, Ajay says CIOs and HR leaders need to set shared objectives, explain to employees what the future looks like, and make AI easy to try. At Rubrik, giving people agents they could simply ask questions built comfort quickly, and soon employees were coming to IT with ideas of their own.
To manage the flood of AI tools, Rubrik set up an internal council: the CFO, the co-founder and head of engineering, the general counsel, and Ajay. Every tool request comes to the council, which looks at the use case and sets the criteria for measuring success before anything is bought. InfoSec and Legal review each request, and Legal publishes a list of conditions with every approval, based on data sensitivity. The requester is accountable for meeting those conditions, and new tools typically start with a one-year subscription: try before you commit. Rubrik then enforces the conditions on its AI agents with its own product, Rubrik Agent Cloud, which can block an agent that steps outside its approved limits. With those safeguards in place, Ajay says he's willing to let people try more tools, not fewer.
AI tools are expensive, and Russ puts the stakes plainly: companies will sell more, hire fewer people, or accept lower gross margins forever, and the last option isn't going to happen. Ajay agrees that measuring AI productivity is essential. Some of Rubrik's use cases have already shown that the company can do more with less. In Ajay's view, that means slower headcount growth rather than headcount cuts; Russ adds that for fast-growing companies, the bigger prize is turning a two-year roadmap into a three-month one. Because tools change so fast (Russ describes developer tools going from Cursor to Google to Anthropic within months), Ajay avoids multi-year contracts and would welcome vendors willing to offer pay-as-you-go terms. As he puts it, if something better comes along, the only thing tying him to a tool is the agreement.
Ajay is more excited about AI now than he was two years ago. Models have become far more reliable, and once Rubrik had its framework and safeguards in place, he stopped worrying about risk and started focusing on use cases. The new bottleneck is capacity: employees now arrive with long lists of use cases and want results. But he's clear about what has to come first. Data quality has to be great no matter what, and Rubrik started its own data quality effort more than seven years ago. CIOs also need governance over critical and sensitive data, visibility into what data their agents access and where it goes, and a way to recover if an agent goes rogue. Asked what will join coding and call centers as the next big AI productivity win, Ajay doesn't hesitate: sales and marketing, where Rubrik's own account-research agent has changed how its salespeople work.
See the full episode on the AI Impact Podcast playlist on the Larridin YouTube channel. To get a demo of Larridin, contact us.
Russ had questions; Ajay had answers.
Q: How do you define the actual role of a CIO? Forget where it reports. What's the job?
A: I look at CIOs as being the business catalyst. It's the engine that helps enable, power, and ensure that the business keeps running efficiently all across the board. ... It's a combination of making sure that you are the connective tissue that's gluing everybody together, and ensuring that the business continues to operate in a healthy, scalable, efficient manner. ... We are the fuel that powers this company.
Q: Are you more excited today about the promise of AI than you were two years ago? Is it underhyped or overhyped?
A: I think I'm more excited today than I was. ... Being CIOs, we have a tendency to always look at risk and safety. ... The rapid pace of evolution has definitely answered a lot of questions. Models have become a lot more reliable. ... When you glue it all together, and you have a framework, and we put safeguards in place, then, at least for me, I'm not thinking about risk anymore.
Q: Coding and call centers are the top one or two. If we're sitting here a year or two from today, what will be number three?
A: Sales and marketing. Unbelievably massive opportunity there. ... We put out a bespoke agent for account research. It's produced amazing results, and it has changed the lives of our salespeople.
Key topics in this episode include:
Russ: I'm here with Ajay Sabhlok, CIO and Chief Data Officer from Rubrik. CIO is one of these jobs that people talk about all the time, and they don't really know what it does. What is the actual role of the CIO?
Ajay: I look at CIOs as being the business catalyst. It's the engine that helps enable, power, and ensure that the business keeps running efficiently all across the board.
Russ: What's your advice to CIOs on the right way to think about data?
Ajay: I think the most important question is, how are you going to leverage your data in the context of AI? AI is going to make all of us highly productive. Data quality has to be great no matter what. The question is, can AI help you improve data quality faster?
Russ: How do you think about the ideal relationship between the CIO and the head of HR? What's your mental model for what's worth experimenting with, and what's not? If we're sitting here a year or two from today, what will be the obvious top three? Coding, call centers, and what?
Russ: Welcome back to AI Impact. I'm Russ Fradin. Thank you for joining me. I'm here with Ajay Sabhlok from Rubrik, CIO and Chief Data Officer. Really appreciate you making the time.
Ajay: Yeah, happy to be here.
Russ: So, a question I always want to start with before we talk about AI. There's lots to talk about with AI, but I feel like CIO is one of these jobs that people talk about all the time, and they don't really know what it does. How do you define the actual role of a CIO? Forget where it reports or anything like that. What's the job?
Ajay: I agree with you. The simple answer is that the CIO is expected to kind of run the company, but I look at CIOs as being the business catalyst. It's the engine that helps enable, power, and ensure that the business keeps running efficiently all across the board. But in addition to that, CIOs are also looking at how the business performs, so they can help with insights and intelligence. So I think it's a combination of making sure that you are the connective tissue that's gluing everybody together, and ensuring that the business continues to operate in a healthy, scalable, efficient manner. At the same time, CIOs can also become consultants and advisors on a variety of processes that companies pretty much have to run to run their business. So I think they're part of the entire DNA of a company in terms of what we do and how we operate. We are the fuel that powers this company.
Russ: It's always interesting to me. I've spent my whole career as an entrepreneur selling things into companies, and generally, when you're selling into departments, you'll hear a lot of, "Oh, we've got to go to IT. Oh, we've got to go to our CIO." And you heard a lot of almost regret there, or apprehension. But it feels like the best CIOs are partnering with all of the various executives. And frankly, in a world where technology impacts every department, I'm not sure how you can succeed as an executive today without a good relationship with the underlying technology that powers your business.
Ajay: I agree with you. There are different ideas and thoughts about how companies should consume technology and how they should go on a transformation journey across all facets of the company. But if you have a trusted partner you can rely upon, a catalyst, somebody who understands that the business needs 10 different things to grow, to thrive, to do things well, then how do you make the connection between all these needs? There may be dependencies. There might be overlaps. And then it all comes back to tools and technologies and data at the same time. So I think reliability is the key. If people feel that they don't enjoy going to IT to ask for help with certain things, that's a partnership that needs to be improved. Something's failing; something's not happening really well. But once you build that great partnership and gain credibility, you become that trusted advisor to everyone, and people actually start gravitating toward you. They use you as a sounding board: "I have this great process automation idea in marketing or sales. What do you think?" For example, I have product managers in IT, and they deeply engage with their business partners and are always available to answer these questions. And sometimes I have leaders, like the CMO, come to me and say, "This is my website idea. What do you think? And how fast can I get there?" So we're there to answer all types of questions. It's not just about enabling the process in a better way. It's also, how do I get it done faster, and is there technology that can help me get it done in a meaningful way, with good user experience or good customer experience? So all those aspects.
Russ: Yeah. If you think about the CIOs you respect the most, or have seen the most across your network, obviously there are a million ways, but what's the right career path? CIOs need such a diverse skill set. It's one part relationships and one part very technical, and procurement. There are so many parts to it. It's a little bit like a CFO, who will come up through either accounting or FP&A. What have you seen as you think about the CIO of the future?
Ajay: I've seen successful CIOs come from different places. I think it's really about the person and the kind of exposure you've had in your past. I've seen great CIOs come up as I did. I was a hardcore developer, and I grew through the ranks and had exposure to all the business processes, tools, technologies, the data portfolio, etc. So I'd seen it all. I've seen CIOs come out of infrastructure, where they're just running infrastructure for a company, but then they grow into this role. We don't think we're experts in everything, sure, but we learn quickly, because we develop a mindset, an attitude, toward understanding all aspects of technology, process and data. When you understand all those dimensions well, I think you're qualified. Then it matters how exactly you go about this journey: what kind of policies you set, what kind of mentality you have toward business velocity, acceleration, and quality of services. That's why I think it comes down to the person, the personality, and of course the exposure they've had. And I don't think there's any wrong background for this candidate. People even from product engineering have done well in this role. But of course, if you come up through the ranks, you've had exposure to everything, and I think you'll be a lot more comfortable becoming much more engaged and hands-on. That's what helped me. When I started at Rubrik, I had good exposure and understanding, to the point where I could even be hands-on for a few months. I just didn't think I needed a lot of people, and I knew exactly where to put resources. It also depends on where the company is. At a scale company, maybe a lot of candidates could succeed based on their personality. At a startup, I increasingly see people look for CIOs who are deeply engaged, a little more hands-on, who can guide people on all topics, including technology and architecture and the best way to design processes or automate things. And then slowly you can build up from there.
Russ: So I'm curious about relationships in an organization, and then I'll ask you questions on AI projects. Given the fact that we're effectively trying, probably for the first time ever, to retrain the entire global knowledge worker workforce at the same time, right now. It's never happened before. Tech has always started somewhere. Maybe it started in Silicon Valley, and it was just for technology companies, and it was just in America. It took a while to get to Europe, a little longer to get to Asia; it started in automotive, whatever it was. Now we're doing a thing where every knowledge worker is trying to get retrained in real time. How do you think about the ideal relationship between the CIO and the head of HR? My customers at Larridin are always CIOs, but the thing we hear from heads of HR is that there's so much angst in the 40- and 50-year-old employee base at traditional companies. It's probably not as true at Rubrik, and I'm not asking about Rubrik specifically, but there's so much angst. How do you think about the ideal relationship between CIOs and heads of HR in this time of tremendous technology change?
Ajay: I hear you. It's a concern every head of HR is going to have: how do I help my employees transform, get trained, get comfortable? Because it's a big change for people, and some people actually have concerns about adopting this and what it means for their jobs. So I definitely feel that this is again a partnership, because we have the ideas, the means, and the resources to enable a transformation of this nature. That partnership needs to have conversations about what we're really trying to achieve. Let's set our objectives. And it has to involve communicating with our employees: what's the future going to look like, and why do we want to empower you and help you train yourself to adapt to this new paradigm? It's a huge shift. We just want to make you more productive. We want to help you self-serve, because now it's actually possible. Before, you were completely reliant on IT or technology, but that's no longer the case. So this partnership has to talk about all the benefits. Then there's definitely communication that needs to occur, and we have to enable a very easy-to-consume way for people to come in. We started doing that at Rubrik. We said, okay, how do you allow the entire workforce to get comfortable with it? So you put out a few things where the knowledge workers say, "Oh wow, okay, I can actually start to ask this agent questions about anything: what I do, how I do it, how to do it more efficiently. It can actually become my copilot in certain cases." And they develop that level of comfort just by experimentally trying a few things. At the same time, you give them exposure to how things work and what it all means for their future growth. And I do see people start to get a lot more comfortable. We followed a similar journey, and we definitely saw people come aboard, to the point where they were reaching out with a lot more ideas and questions, asking for help to enable them quicker. So I think it can absolutely go viral in a company, but the partnership is key. We definitely talked about the different types of people in a workforce. They do different things, they have different needs, and even their consumption abilities are different. Tailoring your strategies to make every group comfortable is a great way to make progress. So I feel this is an important partnership. It should occur, and companies will definitely make quicker progress when employees come aboard, get comfortable with this new world, and actually start leveraging it for their own productivity gains.
Russ: As you think about this explosion of tools in the AI world, we've obviously seen spend from CIOs growing probably faster than it's ever grown.
Ajay: True.
Russ: What's your rubric? What's your mental model for what's worth experimenting with and what's not, in terms of vendors that have been around versus newer companies? How do you think about that in a world where people are obviously spending money on pilots very quickly?
Ajay: You're absolutely right. There's a plethora of AI tools now available. They do everything from being a platform where you can consume and build things quickly, to automate, build agents, build AI workflows and AI assistants, to doing one thing specifically. They're an app, and they do something like help you generate code, or they can do RFPs. I think it's important to understand why we want to go and transform a certain area. We had this notion of the level of productivity gain you can expect from transforming a specific process or a specific area: taking a use case and asking, what can I do with this? Do I need an agent? We've seen a lot of interesting tools, but I think this connection is important.
Ajay: We're on a similar journey ourselves, where we said, on one side, I need to consume AI tools that can do and automate things. Great. At the same time, I want to do it safely and securely. How do I bring the two together? So we set up our own council inside Rubrik, and it comprises our CFO, our co-founder and head of engineering, myself, and our general counsel. We're all in there. All tool requests come to us. We look at the use case and say, okay, interesting, what are we trying to solve? And we set up the criteria for measuring success ahead of time.
Ajay: Plus, we route it to InfoSec and Legal to look at the safety considerations. And Legal is actually publishing a list of conditions when they approve a tool. They say, okay, you can use it, but here are my conditions. They look at data sensitivity. We took that list, and it goes back to the requester, and we say, you're accountable now. Please ensure that these conditions are met. At the same time, go ahead and subscribe, maybe for a year, so at least we can see how well it works. It's try before you completely commit for the long term.
Ajay: And then, on the question of safety, we started to say, okay, how do I ensure that when I implement something, it can be governed? We have our own product, and I was fortunate enough to start my journey on Rubrik Agent Cloud. And I said, okay, it can actually monitor all the legal conditions. It's very specific. It's like saying, for this app, any agent related to this app should not do anything outside of these exceptions. If they try to do something, it can be blocked. Once I have the safeguards in place, I'm actually willing to allow people to try out more tools as soon as we see that the use cases are interesting. We've seen a lot of interesting use cases, and we felt there's a level of productivity gain possible from this, or a huge revenue uplift.
Ajay: So we're also looking at build versus buy. It's not just about the tools. The buy part is a ready tool, but the build part is, I'm still going to leverage a platform. It could be any one of the three, four or five popular platforms that help me build agents quickly. But then I'll put out some bespoke agents of my own and also try to achieve some automation through there.
Russ: Have you tended to prefer working with a smaller number of vendors? I won't ask whether it's Google or Microsoft. Or have you tended toward, I kind of don't care, as long as they operate and the business gets what it needs? I imagine that for some people in a role like yours, it makes life much more efficient if you do as much as possible with Microsoft, or with Google, or with OpenAI. How do you think about those trade-offs?
Ajay: I think it's less about the vendor and more about the effectiveness of platforms. Like I said, there are many platforms available out there. Google has one, Microsoft, Amazon. There's a big platform play out there. Anthropic announced a whole bunch of things. OpenAI announced...
Russ: OpenAI, literally today: the coworker for your enterprise.
Ajay: There you go. Very similar to what Anthropic did. So a lot of companies are definitely making robust platforms available that can honestly help you enable a lot of things with less effort. We're comparing and contrasting. We're going through a lot of POCs when it comes to platform selection. At the same time, we've built some things of our own to learn through that journey: what works well, how do you deploy agents, how do you support and maintain agents, what kind of teams do we need? I built my own AI engineering team that rolls up to me, and we're looking at use cases across the board. In many cases, we say, this tool is great; it'll solve the use case effectively. But for this enterprise use case, I don't think there's any tool, so let me use a platform and build an agent and put it out there. Or we can use a combination of things, and we have many use cases we've pursued in this manner. We still haven't made our final selection on platforms, but we're already on that journey of trying all of them and comparing them, and then we'll converge on one and say, okay, let's roll this out widely for self-service, whether it's an AI assistant platform. So we'll tell people, go ahead, see how much productivity you can gain in your day-to-day activities, while we keep putting out other tools and bespoke agents.
Ajay: In combination, I think we feel we can start to measure our journey now and ask, how is it working? You mentioned performance and productivity measurement. That's absolutely the right question to ask. When you put all of these things out there, how well are they working?
Russ: By the way, these tools are expensive. As I say to people, we're either going to have a world where you're going to sell more, you're going to hire fewer people, or everyone's just going to have a lower gross margin forever because the tools are fun. And that's not going to happen.
Ajay: That's not going to happen. We definitely have to start measuring productivity, because you're right. As soon as you see a boost in productivity, and some of our use cases have seen that on this journey, we know that we can do more with less. And at some point, you're not talking about headcount reduction. You're just talking about slower headcount growth.
Russ: Well, also, for companies like mine or yours, I think it's very different than if you're a mature, slow-growth company, maybe owned by PE. For companies like mine or yours, there's so much opportunity in taking what was your two-year roadmap and making it your three-month roadmap. You see that all across Silicon Valley, and by Silicon Valley I mean the idea, not necessarily companies based here. I don't think any of those companies are thinking about cutting headcount. They're saying, what would have taken 18 months, we can do in three months, so let's hire more. Look at all the stuff we can build for our customers. I assume Rubrik thinks about it that way. I think it's very different if you're a 5% growth business owned by private equity that's really going to think, look, we're not going to grow revenue faster, so we have to...
Ajay: Yeah, I think that's true. And I know every business is different. There are so many different functions within a business. But the underlying philosophy is that AI is going to make all of us highly productive. In many cases, you'll have digital agents that automate processes, and they become copilots, etc., with a human in the loop. So there will be an opportunity to contain headcount. It's not like you just do away with headcount. I don't think that's the right philosophy, at least not in the foreseeable future, and we'll see how this journey evolves. But at this time, that makes the most logical sense. You're not talking about headcount reduction. You're saying, let's get highly productive. And yes, you can actually churn out much more, whether that means you're churning out products faster, features faster, or, depending on the industry you're in, you're improving your services or doing things in a much more effective way. But yes, in many areas you'll find that you don't have to grow headcount in that traditional scale model.
Russ: Sure. So the traditional scale models are going to get challenged first. No one's hiring the 200 SDRs they used to.
Ajay: Because agents can... But if we have X number of SDRs, they'll start to become much more productive, 100%. They'll also become the human in the loop for a lot of decisions they have to help digital agents make. That's a great way to see this: you can do a lot more; you can accelerate your business.
Russ: Ten years ago, when I was building a startup, if you were building a SaaS company, and I'm sure Rubrik did the same, it's frankly why you saw so many people hiring SDRs in Denver, I think Snowflake was in Denver. We did it in Sacramento. People did it in Nashville, because you literally couldn't hire enough SDRs in Silicon Valley given the amount you'd pay. It was just impossible. And the truth is, the people you have now have just gotten more efficient. So I wanted to ask you how you think about centralizing on platforms versus the constant... We've never seen tool evolution at this speed. Let me set it up this way, and you might challenge it. Please do. I'll pick one category: developer productivity. Nine months ago, if you talked to any Silicon Valley founder, they'd say Cursor, Cursor, Cursor. Five months ago, if you talked to any Silicon Valley founder, nothing against Cursor, they'd say the Google model, which is slipping my mind. And two months ago, absolutely something changed with Claude, where it's Anthropic, Anthropic, Anthropic.
Ajay: I agree.
Russ: And the rumor is that what comes out in a month or two from OpenAI will be even better. Let's just say that's true, and without getting into it, I'm sure if Cursor and Claude and Google were here, they'd take issue. But on the one hand, you have that dynamic. We've never seen the pace of innovation at this rate, ever.
Ajay: Yeah, absolutely.
Russ: On the other hand, though, eventually you do have to choose a platform. There are all of these business efficiencies in choosing a platform. How do you think about that dynamic? Because you can't have a world where every Rubrik engineer changes the way they write code every three months. It doesn't work at your scale, and it certainly doesn't work at Honeywell's scale.
Ajay: I agree with you. Because the world's changing so rapidly, I think the first thing that happens is that people are not comfortable getting into multi-year agreements. That's the first thing you change: saying, I really have to understand how this evolution is happening, but let me try something out. Also, a lot of these tools and this technology are not legacy in any shape or form. It's not something that's hard to replace. It does something efficiently, but if I see something else that can do it better, all that binds me to it is this agreement.
Russ: You don't have the issue of, all of my content is in SharePoint, so I'm not going to move.
Ajay: Yeah. It's cost and contract. I'm asking, what are my constraints here?
Russ: So would pay-as-you-go models become more popular?
Ajay: Probably. I might actually be attracted to you if you give me that flexibility, with the promise that you'll keep innovating at the same pace as everybody else. Pay as you go, and see if you want to challenge us that way. I would love companies who put themselves out there and challenge the status quo.
Russ: Because this is not like switching off Workday or switching off Oracle Financials, where, in all honesty, people talk about this, but if you choose Oracle Financials, you're using that till you go out of business.
Ajay: Yeah, but I think there will be two types of apps. You brought up the code generators, and I absolutely think they can't be sticky. But I believe the entire SaaS world is getting challenged. We'll have new form factors, new kinds of AI tools that completely change the experience, whether it's CRM or configure-price-quote or ERP. People are generally thinking, how can AI help transform these areas? There's this notion of a data store. You still need a system of record, a source of truth. That data isn't just disappearing. You need reliable data. You have compliance requirements like SOX to maintain. So I think there will be tools coming in the near future that are very AI-driven but do have a data store, and I think they'll be stickier than the AI tools where, right now, the use cases I see don't have that level of stickiness. Eventually, I'm looking forward to some of these apps where my entire data is in there, my entire metadata is in there. I'd still love more flexibility, because you're right, I can't put all my eggs in one basket. I don't do that with SaaS either, but it's harder. With SaaS, we have to plan a year or two in advance and then churn out, and we've done these things before. But with AI, you'd hope you can do things faster, and maybe AI itself can help you go from one tool or technology to another, or one platform to another, because at the foundational level it's a very similar approach. You have models, different kinds of models helping power this thing, and then you have the platform, and then you have the actual tool. So how easy is it for me to move data stores from here to there? Because I'm not customizing, I'm not configuring. I'm just giving you a BRD, and you're doing the rest. But I can take all the same BRDs and give them to another tool. So I think the entire development cycle might change. I haven't seen platforms emerge that can do all of these things, but I'm very optimistic it's coming, because we're entering into some design partnerships ourselves with that same idea, with some vendors, and saying, okay, let's challenge the status quo in some of these areas.
Russ: So, two years ago, let's say two and a half years ago, ChatGPT comes out, and there's this perspective that we're just going to go away. There are going to be agents; we're not even going to have jobs; global IT spend is going to go from $1 trillion to $10 trillion; a lot of that ridiculousness. But ignoring that, if you can remember yourself two years ago, are you more excited about the next two years, given the reality of what you've actually seen delivered in the last two years? Are you more excited today about the promise of AI than you were two years ago, or less? Is it underhyped, overhyped? How do you think about it? Forget the bubble; the bubble is just people making money and losing money.
Ajay: Well, I think I'm more excited today than I was. Two years ago, we were all trying to grapple with a lot of different things about AI. Being CIOs, we have a tendency to always look at risk and safety. It's baked into our nature.
Russ: Right there in the other part of your title.
Ajay: I think so. I just cannot do things that could jeopardize the business. So we all started asking the same question: how safe is this? Because you hear about hallucinations, and autonomous models that can actually make a mistake. Then you hear about databases getting deleted with Replit. I was like, "Oh my gosh." So for the last two years, we've all been debating, and the rapid pace of evolution has definitely answered a lot of questions. Models have become a lot more reliable. They don't hallucinate a whole lot. Yes, there are areas where you can push them into it. But have they evolved to a level where I can 100% trust them? Well, we're trying conversational analytics across Rubrik in a big way, and yes, we're seeing levels of accuracy that are improving. But we have to work with these tools we're leveraging. It's not just plug and play. And that's fine. As long as we understand how this landscape and ecosystem work, I'm willing to make investments. As long as I can get automation, massive productivity gains, people can self-serve, knowledge becomes freely available, I think it's worth the investment.
Russ: That's why the excitement's increasing. Because you're seeing that a decent percentage of the things you've piloted, with your steering committee, are impacting your business. Real, on-the-ground value.
Ajay: Yeah. When you glue it all together, and you have a framework, and we put safeguards in place, then, at least for me, I'm not thinking about risk anymore. I'm like, "I think I have the right tools to take care of my risk now. Now I need to focus on use cases and rapid consumption." How can I convert these use cases into actual solutions so the entire workforce benefits in different ways? And that's the excitement. Then it's like, oh my God, we're on this amazing journey; look at the possibilities now.
Russ: Well, look, here's my theory, and tell me if you disagree. For a long time, being CIO was something where other departments wanted to fight with you a little bit. Now, because AI is so exciting, I can't imagine there's been a time when being the CIO was more popular with your co-workers. To me, this is such an exciting time, when people want to experiment with so much stuff. I imagine it's easier for the average CIO to build relationships with peers today. Maybe not you at Rubrik, but I imagine now is an amazing time to be a CIO. Just super exciting.
Ajay: Absolutely. This is a common plane that resonates so well with all the business leaders. There's no one who doesn't recognize that there's a massive opportunity for them to transform, and they just need a partner. People try to just consume tools, and that's where I said, can this journey be chaotic? Oh my God. Absolutely.
Russ: I'm sure you've had projects not work.
Ajay: Of course. Yeah. If you let it loose and let it run by itself, people are just going to start consuming any kind of tool. The question is, then they're not measuring. They don't know what went wrong. They might hit a wall. But if you do it in a more disciplined manner, with the right council framework, I think it can go a long way, and people are satisfied. Now our major challenge is capacity bottlenecks. The first bottleneck I hit was not that people weren't coming to the table. It was my own capacity. Too many requests coming from all over. I said, okay, this is a great problem to solve, because it means we've educated the workforce to the point where they're all excited about this journey. They're not concerned anymore; now they want results. They're like, "I have these 10 use cases. When do they see the light of day?" So it's go, go, go. Great. I said, that's my problem to solve. I know exactly how to increase capacity. No worries. I've already started building partnerships, and we'll absolutely increase capacity and beat the demand, partnering with people in every which way and getting the right tools in play. So I think the journey definitely becomes very structured, and we'll see a lot more gains, because now everybody's on the same page, and we have this common council looking at all the gains and saying, we're still going in the right direction.
Russ: What's your advice to CIOs on the right way to think about data in this world of brand-new tools, from startups no one ever heard of, that didn't exist two years ago, with access to lots of data? Not that you assume bad intentions, but what's your mental model for how CIOs should think about data?
Ajay: I think the most important asset you have for your company is data. Data is the fuel that drives your business. So the question is, how are you going to leverage your data in the context of AI? Because yes, AI is data-hungry. To get the best answers for a lot of business use cases, you'll need AI to look at your own data.
Russ: Yep.
Ajay: And that's where you have to think data quality first, and ask, am I going to have quality data? Because I'm depending on my digital agents to leverage it, derive insights from it, and advise me on it. So how good is the quality of the data? Because that could skew the results. Hopefully you've embarked on a data quality improvement journey. We did, seven, seven and a half years ago, and to me that was foundational. Data quality has to be great no matter what. It's not about AI. Data quality had to be great back then. Now the question is, can AI help you improve data quality faster? Yes, there are absolutely ways to improve your master data quality, etc. You can leverage those techniques if you haven't already put these processes in place. But yes, the data foundation is important. Whether you build a lakehouse, however you build your strategy... We in fact have tools with data connectors that go into all the data sources, and different ways of consuming data, but the quality needs to be certified. So we said, we can certify data quality in many different sources. Next is governance. Where is your critical data, your sensitive data? What data privacy rules should you maintain? All these things have to be taken care of as part of the foundation. And then, and only then, do you get to play in this. Then you can get much more comfortable about enabling use cases. So all CIOs absolutely have to make sure that, if this was never a priority, it becomes the top priority immediately, because everybody's going to come at your data in every which way. And absolutely measure what agents do: what data sources are being accessed, and who the data is going out to, because a lot of this will be autonomous. Humans may or may not be in the loop. So how are you going to safeguard yourself? I think that's become an imperative. Make sure that if there's corruption, you can get the data back. Assume that an agent goes rogue: what are you going to do next? We've been worrying about this; we were obsessing about it. And there are tools available now to solve that. Rubrik has its own tools, and there are many different ways to secure data. All these elements will really help you ensure that you can more confidently allow people to consume their use cases, because you've put all these monitors in place.
Russ: Thank you so much. I really appreciate you taking the time. I have one final question. Tell me if you disagree with this framing. We know for sure we've seen amazing productivity gains with coding. We know for sure we've seen amazing productivity gains in call centers. I think it's pretty undebatable that those are the top one or two. What do you think is number three? If we're sitting here a year or two from today, what will be the obvious top three? Coding, call centers, and what?
Ajay: Sales and marketing. Unbelievably massive opportunity there. We got so excited about this third dimension. In fact, we put out a bespoke agent for account research. It's produced amazing results, and it has changed the lives of our salespeople.
Russ: I assume, as someone people try to sell to, you get a much higher volume of much higher-quality email.
Ajay: I think it's a reciprocal thing, because when we built that, we're now helping our prospects fully understand where their challenges are and how we can help them. Before, it was a more difficult thing to articulate. But this research really puts the entire thing together, and with that, gosh, we can give you so much more information about what you should or shouldn't do. I think it's amazing. That's what got us excited, and we said, this is where that entire transformation is going to occur. The third area.
Russ: Excellent. Thank you so much for taking the time. I appreciate it.
Ajay: Absolutely. It was great talking to you.
This transcript was prepared by AI and may contain mistakes.