78. Every AI Strategy Needs a Data Protection Strategy with Commvault

Every company lives in fear of a ransomware attack, whether they've suffered one or not. And this is even more critical in the era of ai. This episode of the Tech Field Day podcast looks forward to Commvault Shift in November with a discussion of the importance of data protection to AI applications with Tim Zonca from Commvault and Frequent Field Day delegate Gina Rosenthal.

Listen in and learn about the connection between data, data protection, and ai. Welcome to the Tech Field Day podcast, where we bring together a group of IT technical experts to discuss a single idea about key concepts in the industry. This podcast features a variety of perspectives from members of the Tech Field Day delegate community, and is often recorded in association with one of our events.

This episode in particular, is recorded in association with Commvault Shift, which we will be attending in just a few weeks. Tech Field Day is part of the Futurum Group, and this podcast is published on our sister company site, text Strong tv. This episode we're looking forward to Commvault Shift, which is November 19th, and we're talking about the importance of data protection to ai.

Yes, ai, it's 2025. Everything is about ai, but we've found that there's an interesting connection between AI strategies and data protection strategies. Before we get started with that conversation though, let's meet who's on the panel today.

Hi, I'm Gina Rosenthal. I am a fractional product marketing manager. I help lots of companies including data protection companies with their, um, private marketing.

And I'm Tim Zaka. I'm the Vice President of Portfolio Marketing here at Commvault, and glad to be here with you today, Steven. Thanks for having me.

Yeah, it's great to have you. Uh, as you mentioned, I'm Steven. Uh, I am the, uh, halftime host of the Tech Field Day podcast, and, uh, have been running tech field day events for 15 years.

Over that time, I've actually attended quite a few Commvault, uh, events, and we've had Commvault join us as well at our tech field day events. And one of the things that comes across whenever we talk to folks from Commvault is the importance of data protection. I guess surprise, you know, I mean, that's, you know, what you do, but it's also something I think that is really, uh, in your hearts because you're a company that spends your time talking to companies who either fear data loss or have suffered data loss, and you're trying to help them avoid that catastrophe now that it's 2025 and AI is on everyone's lips and everyone is trying to figure out how to roll out a successful AI strategy.

Tim, I wonder if you can start off by just sort of drawing the connection between AI applications and data protection needs. I actually think you just nailed a, a big part of that connection, Steven, is you had said something along the lines of e everyone, you know, focused on kinda ransomware, staying resilient, uh, kind of frankly like the hygiene of what great looks like to just maintain a continuous business and fight through an attack. Now, while organizations are doing that and putting these best practices in place, they still most still have a long way to go.

And you have this meteor of AI coming crashing into that set of projects, practices, and initiatives. So I think one big connection point is as organizations are trying to improve their resilience, their recovery practices to fight through just kind of maybe good old, uh, cyber crimes now, it's just gotten that much more daunting as AI stacks look different, as AI data is distributed everywhere, as there's questions of accountability and ownership, and now add just attacks that could, uh, in the threat surface that's widened and different through ai. And I think that's the big connection point because the so what across all of it, it doesn't matter if it's a, you know, maybe a more traditional looking attack or something that's come through ai, you know, poisoning or even just, frankly, an outage due to the newness of it, the business needs to be back up and running.

And so having a resilient, strong resilience practice is I think the, the connection point between the two. I love that word resilience because I think that's really true. A a couple of things that really stuck with me is it's definitely, you know, AI introduces all of this new ways to attack organizations.

I think one of the most interesting ones is that the people sending the ransomware out are using AI to create their, their campaigns. So one of the things we've lost is the, the as just users, individuals that, you know, on the, on taking all the training and looking out for the phishing, you've lost the ability of saying, oh, that's definitely not proper English, that I don't think this is really from that person. You've now got the ability, the, the, the people have the ability to, to train on an individual's voice and how they write and how they talk and send you a phishing email that looks super, super, um, real hard to explain.

And then I love that point about resilience, because you're gonna make mistakes because this is all new to everybody. So you're gonna lose data, you're gonna dump something you should, and you need to be able to roll back. So it's, it's really important to think about that.

Yeah, and I think you, you mentioned a good point, Gina, which is, it's, I think maybe it's just like we as technologists, it's easy to geek out on the more sophisticated attacks or, or maybe newer ones, you know, prompt injection or just adversarial attacks where maybe it's, uh, where the bad guys are using AI to do, you know, polymorphic attacks where the signature's changing. It's hard to detect, but I think like just making spam that much or, or phishing rather, you know, that much better. Um, it's super dangerous.

And, and I think that, you know, when you can have these attacks that are just actually logins, not, not these really like well-crafted, uh, uh, you know, initial kind of entry points, um, yeah, that, that's, I think that's really dangerous. Yeah, we've been seeing that here, um, where the, I don't wanna say sophistication because that's really not the right word. 'cause it's not any more sophisticated than it used to be.

It's just, as Gina said, it's more convincing. And so we're starting to get, uh, well, I mean, we, we're all businesses, we all get ransomware, uh, attacks or at least openings, uh, you know, phishing and, um, social engineering openings all the time. But I've noticed that they really have changed.

Uh, they used to be pretty clunky. They used to have poor English, poor integration, you know, sometimes it was like, dear, you know, last name, you know, that kind of thing. Now it's really not like that, and it's pretty obvious to me that, that it's generative ai, especially with, you know, text chatbots that's enabling, uh, customization and personalization at scale, at least to some extent.

Now, obviously, as, as Gina points out, sometimes they're still a little nonsensical, but, um, it takes a human to recognize that. And I'm concerned that these, um, you know, the AI technology, on the one hand, it opens, uh, doors to creating more, uh, credible attacks. But on the other hand, of course, we also have to think about the ways that agentic AI applications are opening the doors for those attacks to be more successful.

So maybe we can get to that second point a little bit later. But I mean, first, um, you know, has the prevalence of ransomware increased or does it just seem like it has because it, it seems like we're hearing about it constantly and is it the fault of AI that these things are, are more credible and that's what makes people, uh, uh, more susceptible to them? I mean, I, I think at least what I see as I, as I talk with, with our customers around the world, I think I, I've seen, I would say most data at least suggests yes, ransomware is becoming more prevalent.

I've seen enough to say, well, you know, it's about the same or even, you know, a slight decline. But I think the punchline is, um, that it's gotten that much more effective and, and, and common, and I think dangerous. I think it's in, in this, it's talking to the two of you.

This is cliche to say like, it's become such a massive business that I don't really, I think it's a distraction to think about, like, has it gotten, you know, more prevalent or the same or less, like it's a, or a just a staggering, uh, danger and, and a costly one. I mean, it, it, it, you know, it impacts business from a cost perspective. You know, we've all read, uh, you know, or, or even some of us, like work directly with, you know, healthcare organizations where, you know, it's patients that, that they're, they're working with it's government institutions trying to serve their citizens that are impacted by this sort of thing.

So it's, it's, it's like a massive business. And I think to me, that's the, the biggest one. So regardless, like what the trend is, it's, there's no future where it's going away or, or, you know, diminishing to any kind of significant degree.

And I think, Steven, you're right, it's just, it's, it's getting smarter, I think the iterations with which, um, kind of adversarial, uh, or, or just kind of either hackers or usually it's, you know, organizations can just put out a text like it's a business. Um, I think that's the part that is the most just daunting and challenging. It's just moving so fast.

And I think AI allows them to do it that much more adeptly. And I think you can have people who are, you know, even organizations that are pretty good, all of a sudden get really great and they tend to be able to move faster anyway. And so to now have a set of tools that allows them to, um, you know, often outpace the people that they're trying to, um, get leverage against and, and hold for ransom.

I I think that's the daunting, the, the most daunting thing. I think that's the way to look at it too. This is not like the hackers and the hoodies, like the whole crazy way they display hackers, it's businesses, it's, it's a business and it's nation states doing it as well.

So the, the, the money that they can't get other ways, they're able to get it from ransom. So they're definitely using every tool they can to number one, build the tools. And they're using, they're using generative AI to write the code, and they're using, they're using it to market.

They're using all the tools we use to make sure people hear about the products. They're like, we're gonna make our product really awesome, and we're gonna make sure you hear about it and use it whether you like it or not. So it, it's not, you know, like script kitties, like we used to always think this is literally well organized businesses that want to be well funded, and it's really easy for them to get funded because of the nature of ransomware if they don't have protection.

Yeah, that's, that's a really interesting point. Like Tim said, I mean, this is, these, these are basically businesses now, uh, they're illegal businesses, but they're businesses. And so by, uh, whether they're funded by nation states or funded by ransomware payments, they have a huge amount of power, a huge amount of money.

Um, they've got this incredible technology in their hands. I mean, Jeannie, you, you know, as you say, a lot of them are using, uh, generative AI to write code as well as to, to write text. Um, you know, we have a whole new world now of, uh, very, very convincing generated video and audio.

Uh, I know that we've all heard, uh, stories of, you know, ransomware attacks that, uh, appear to be legitimate employees on a zoom call and things like that. I mean, this stuff is just wild. And, and I think that basically, you know, we have to move on from this idea that somehow we're gonna squash this before it happens, and we have to move to the idea of what do we do when it happens?

Because I just don't think we can stuff this genie into the bottle. There's too much money at stake. It's not going back.

You have to protect yourself and have a, a way to recover. You have to, it's gonna happen. Yeah.

And I think the whole notion of yeah, like stuffing the genie in the bottle, I, I think the thing that, kind of back to your, one of your original questions, Steven, is just, you know, that the connection of AI and the impact that it's having on, on resilience is not only like, we can't stuff the genie in the back, in the bottle, but the, the pace of change that AI is bringing is so dramatic. I at least it's the fastest and most impactful thing I've seen in, in my tech career. I mean, there's, there are analogs to I think the cloud world.

I, I see things like, you know, remember in the early days before, like the, um, kinda shared responsibility model was really something that was wholeheartedly, you know, articulated, understood, practiced, and it's kind of who owns which piece of it. I mean, I think it's a similar thing here in this, this AI world, and it's, it's moving so fast that as org every organization that I've talked to recently is doing something there, and many of 'em are doing real stuff, but they're like, Hey, look, I was talking to a CISO the other day. He is like, we use Zendesk for these sorts of things, and, you know, we understand how to make that resilient, but they're using, you know, what about the supply chain of what they're using?

Where does our accountability go? How far does it reach into the LLMs and the, the way that they're, they're training stuff, and where does that line stop? And I think there's a, a whole set of questions around those kinds of practices that are being entertained now, don't have clear answers, and the pace is moving so fast that it's, you know, I think, you know, people are, are trying to keep up, but it, I think that's the part that's, that's not, it's like the genius outta the bottle and watch out because, you know, it's coming really quickly at you.

I think that's a really interesting point too, because, um, PE businesses want to move ahead and it's obvious that AI is the next round of, of innovation for computer science. So they want to move ahead, but everything's coming so fast. Everything all at once, right?

How do you, can you, you still have to maintain that data center hygiene and keep everything protected and, and do that side of the business and, and how do you do that protection and, and how do you know where to go? Where do you put your funds to actually do more than what you've been doing and, and, and use AI to get you to the next level? Yeah.

And I think to me, that I, that's the biggest tension that I see with the customers that, that I'm working with in that kir, to your point, Gina, that some of the, the practices that they're putting in place to protect their data, um, even basic ones, things like, you know, air gapping with immutable and indelible copies of your, of your critical data. Things like, um, some sort of practices, processes, technology for identifying clean points to, you know, to recover too. You know, Steven, as we were kind of prepping for this, you know, just talking about like, Hey, how far do you, you roll back certain sets of data?

Like, so having a process around what that looks like. Things like, are you class, you know, discovering and classifying your data? You can't do rag if you don't what your, what your data is where, you know, like, you know, and, and, um, and, and I think basics like that are still being implemented, let alone more advanced technologies or, or capabilities like, Hey, I wanna use the cloud to burst into isolated clean rooms for forensics or something like that.

Just the basics are still being put in place, at least broadly. And, and now just this rapid progression of ai. The, the, to me, the heartening thing though is the organizations that I am, I am, that I'm, that I've been working with, is just, they're, um, kind of delightfully a a bit more progressive than I would've thought on, you know, who's involved or how many applic, you know, kind of AI driven applications they have in production.

And even when they're, they're moving forward with almost like this blind urgency, uh, and kind of prioritizing learning and, and growth over kind of the guardrails. They, uh, I feel like at least some of the proper guardrails are starting to get it put in place. And the ones that aren't, they know what they are.

Like Gina, to your point, they're like, yeah, we know that the right hygiene looks like this for our established workloads and, you know, but we're three months out on that for this project, or six months out. So, uh, maybe it's the e eternal optimist in me, but I, I at least feel like people know what they should be doing soon for those workloads. Yeah.

It's not all doom and gloom too, that's the thing. So, I mean, AI is also a very powerful tool for data classification and for, you know, detecting, uh, attacks as well. And I think that that's all something I th that, that gets lost sometimes.

'cause we are very scared of ransomware attacks. I mean, I, I am, you know, as a business person, uh, I am as a professional worried about what the impact of these things are. But there is some reason to be optimistic that companies are, you know, kind of getting their act together in terms of data classification, in terms of implementing, uh, good strategies around data protection and that that the tools are advancing as well.

I mean, one of the coolest things out there, and, and it's funny because it's not really a new idea, but it found new impetus, is this idea that you can have, uh, almost real time data protection. And you have that kind of virtual dial where you can sort of go back and say, well, the ransom attack happened here, so I want my data set to go back to right before that. And there again, I don't want it to sound too much like an ad for Commvault products, 'cause I know that you guys have stuff that does that, but you know, that's a pretty powerful tool and something that has finally found some currency in here.

And the same is true as you point out of tools that allow you to, um, organize and classify and categorize data to replicate data to different locations, to burst between locations. A lot of this has been something that we in the industry have been building to for a long time, but here it is, and it's actually important, more important than ever when you're talking about these data-driven applications. Yeah, I I think you bring up like a, one of the kind of current hot topics, I'd say in a lot of discussions with our customers at least, that are, that kind of are, uh, running their applications regardless if they're like AI driven or not, but on the AI sort of like maybe typical underpinning, so some of the larger, you know, uh, like data structures like, uh, you know, S3 or, or something like that in that, um, there's this combination that I think technology has gotten great at helping provide, which is not only being able to recover at just ridiculously massive scale and doing it really fast, but then Steven, you kind of suggest these, like what we, we call like micro recoveries.

It's just these like kind of near real time. They're, you know, they push out, especially in cloud native apps, they're, you know, as, as, as updates are being pushed out and all of a sudden something gets corrupted or, or clobbered to being able to just have these kind of micro recoveries. I think spanning that gamut is, is I think, a key new requirement for resilience.

And so, you know, you, uh, I appreciate you kind of given a nod to us, but you know, I'm biased kinda working for Commvault. You're right. Like we have some of our, our capabilities that we have there are just really well suited to cover that, that broad swath of recovery from just the super massive, you know, billions of objects in, you know, record time to these kind of micro recoveries where you're just kind of backtracking to some subset of your, your data state to, to a form important time and again, in close to real time.

To me, it seems like this, this whole period seems more to me, like when Linux came out, that's, that's when I experienced this much disruption. So with you saying that, Tim, one of the things, we're talking a lot about the production applications, but when things are in development, it seems like having that resilience to roll back exactly where you need is important too. Especially with ai, when you've got so much time that you're spending on, um, doing some of, especially the inference training or, or whatever you may be doing in your organization, and having several people going at copies of the same data at one time, it seems like there's a great need to, um, to have a place to roll back to.

So those experiments don't take longer than they need to. I think that's a good per like, kinda a good parallel, or like the, you know, the, the way you mentioned Linux, I think the trend that, that I see is that, I know I don't wanna diminish the importance of kind of on-prem disaster recovery or like, you know, kind of disaster recovery with traditional or operational recovery with traditional packaged applications applications. But it's largely a solved problem, like in, in an on-prem world, you know, most, most customers I talk to, like, if it's not, I mean, it's pretty much real time or near, like they're flipping over from one site to another.

Like they just got that lick, they, they're doing testing. It's, it's a really rigorous, well established process that's not true in the cloud. This operational outages are still an unsolved problem.

Um, so, you know, they have cyber and operational recoveries to kind of deal with, and I think you're spot on is that this, this notion of, you know, in development, like, whoa, we just, we just updated a whole bunch of stuff. You know, it, it might be they're pushing out a, you know, new build of, some of the services might even just be new, you know, or infrastructure updates. And like, we need, we need to rewind that part.

Like something didn't go right there and it, and it's not a, an attack necessarily, it's, it's just a, some, you know, something doesn't match what they expected. And that's, I think that's a still like a largely unsolved problem in the cloud. And I think that comes back to, I keep, I always just have been using, like this meteor analogy is as people get that hygiene in place, you know, then like, here comes AI to just, you know, put the additional pressure on.

And I think that's the, just the massive strain that, that I see within the conversations we have with our customer base. Yeah. I'm interested in hearing more about sort of what the real world looks like out there.

I know that you guys are talking to customers all the time. I've run into those customers, uh, you know, at events, um, certainly at Commvault shift. Um, what are they saying is the real world of that sort of interplay between AI and data protection?

I think there's a couple things. I think, um, on the fir like it's, it's almost like two sides of a coin is where I spend most of my time talking with our customers. On the one side of it is, how do we make, you know, these new AI stacks, the new data, you know, formats and things like that, how do we make that resilient?

And so this may be things like, you know, it's iceberg or, you know, S3 tables or, you know, Postgres with vector support, you know, so they, they wanna make sure that the, the, um, kind of data stores are something that they can protect in it and have adhere to their, the policies that they have in place for governance, resilience for all their established workloads. So I think that's one of the places where AI intersects and it's where they look to Commvault to help them protect that data that's ma being made ready for ai. And then the AI generated data.

That's, that's kind of coming out of that. The other side of the coin is how do I use AI to be better at the resilience practices that I put in place? And Steven, you already kind of alluded to some of this, which is, you know, using ai, I mean, it's great at pattern recognition, right?

So like, uh, what about things like anomalies and, you know, detecting those and threat hunting and, you know, helping people find, um, we use it as part of our platform for our customers to, to help identify these clean points, to recover to, or to help, uh, see malicious activities that are otherwise really hard to detect if you're, you know, a human trying to, to compare this sort of stuff. For sure. So I think the, you know, on the one side it's, um, making your data and your, especially your ai, you know, ready data resilient, and then the auto or, you know, the AI generated data making that resilient.

And then the other side is just using AI to improve your, um, efficacy of your resilience practices. How does that strike you, Gina? Again, you're kind of coming from the, uh, customer perspective as well, and from the, the world of, of, of, I guess, uh, tech skepticism generally.

Um, does this, does this ring a bell for you? No, I think it's, I think it's been happening for a long time though, um, within, uh, I think you guys have had some machine learning, right? For a long time and, you know, and so, uh, that's helped that this is not, it's not a new practice, you know, and it's not something new to people have been thinking about.

They've been trying to figure out, okay, this seems like if we use machine learning on this, we could get it to go really fast. Um, and I think it is very true. I think the other thing is you, the people that are doing security and people that are doing, um, the operational piece, which is usually data protection, I think those teams are probably melting into each other a little bit.

And I think there's not a lot of people doing it for the amount of a meteor coming at them and smashing them with AI driven ransomware. So, um, you know, we already know that knocking on the door and getting in is the har is one of the hardest things for the ransomware companies. I'm just gonna call 'em that they're using AI to get better at it, but once they get in, it's really, really hard to detect it unless you've got these tools set up watching for it, even if you're been in the business 30 years.

Because I mean, I remember being assistant man and having little scripts that I would run every morning just to see, and I'd have things set up and we could sue when things were happening, but I, you know, it's a horrible feeling to know somebody's dropped a root kit on your, one of your systems and you've been wa watching for it for, you know, years. So, um, yeah, you have to have, you have to fight fire with fire. And it's not like, you know, it's not like it was 20 years ago.

It's, it's, it's all evolved and it's very, you've got companies trying to infect you and hold your, your data for ransom. So, and they're using AI to get there, so you've got to use fire with fire, I think. Yep.

Well said. And I think that that's exactly what we're hearing from some of these leading companies. I mean, when we are at events, uh, with Tech Field Day, um, one of the things that I'm always listening for when companies start talking about, oh, AI is in our product, you know, the thing I'm always listening for is what are you actually doing with it that's productive?

And I love it when I hear companies talk about how they're using, you know, generative AI to monitor, um, you know, massive quantities of data to find anomalies and patterns in that data when they're using AI to, uh, classify and organize and tag data when they're using AI to, as Gina is saying, fight fire with fire. Um, I think that that's great. Um, if, if their answer is, yeah, we've got a little, uh, chat bot down on the corner that can talk to you, well, that's, uh, I don't wanna say it's bad, but it's a little less great use of this technology because, you know, it has a lot of potential and it has a lot of use cases.

And, um, we can have, you know, small specific models that do specific things. And of course, we also have to think about this rise of agentic AI and giving AI applications autonomy and a chain of thought process. Uh, by the way, quick plug, that's what we're talking about on this season of utilizing Tech, which, uh, will have just launched.

Uh, that's our, our other tech field, a podcast. Uh, we're talking about agent ai and, um, I think that that really is going to be opening up a whole other can of worms, uh, good worms and bad worms. So I, I guess to, to sum up Tim, um, tell us a little bit more about the state of the industry and the state of Commvault and what we could expect at Commvault shift here, uh, in November.

So I think, uh, I think it'll come back to some of the points we talked, uh, about earlier, which is I think from a, the state of the industry perspective is the impact that AI is having on, you know, the market. And surely our customer base is not only massive, just, but moving at an unprecedented rate. And so, um, what you should expect it shift is, um, uh, a, a a broad set of, um, you know, presentations, topics, discussions, demonstrations.

We have a, a great both, um, for those who are joining in person in New York, um, November, um, uh, uh, 11th through 13th is we have a set of, you know, breakout sessions. Um, all will have, you know, demonstrations of some of these technologies. And then we have a virtual track, and the topics are going to be around as organizations, um, scale their success with ai, how does Commvault help them bring those workloads, kind of protect those with the sorts of governance, uh, control policy monitoring and enforcement that they have, uh, come to get great at, uh, for the all their established workloads.

And then on the other side, how does Commvault help them use AI to be great at their resilience operations? I think that sounds really exciting. I think it's a really important message and, um, I know with the demos and stuff, you're gonna show people how to do it, so that's always the best.

Yeah, Gina, absolutely. I'm, I'm with you. I can't wait to see what, uh, Convault has in store at shift.

And, um, definitely we'll be continuing to follow this here on the tech field, a podcast as well as on our utilizing Tech podcast. So thank you both for joining us for this episode of the Tech Field Day podcast, focused on the connection and interplay between AI and data protection. Before we go, uh, where can we continue this conversation?

Uh, Gina, Uh, the best place for me is probably LinkedIn. Um, and you can search for Gina Rosenthal and you'll find me. I'd love to talk to you.

Excellent. And, uh, Tim, uh, where can we continue this conversation with you? Same thing.

I'm Tim Zonca, uh, on LinkedIn. You could find me there if you wanted to DM me, but also, uh, for those of us that wanna hear more, uh, get some hands on experience, see some of what we talked about live, either join us in New York City, November 11th through 13th at our shift event, or do it online. And you can, uh, join straight from your desk with good cup of coffee and see the same sorts of things.

So thanks Steven, and good to get, get a chance to talk to you, Gina. Yeah, absolutely. And we'll be, uh, covering shift on the tech field day channels, uh, YouTube, our social media, and of course on LinkedIn, where you'll find me as Steven FoST.

Also, as I mentioned, uh, we have just launched our next season of utilizing Tech, which is focused on Agen AI and features, uh, friend of the podcast, Frederick Van Herrin and Guy Courier as co-hosts. We've also just launched another podcast that's gonna be relevant to this audience, uh, security Boulevard, which is in concert with our sister website, security Boulevard. Uh, there you'll find, uh, familiar faces, Tom Hollingsworth, uh, Mitch Ashley, along with, uh, folks, uh, like, uh, Fernando Montenegro and Alan Shimmel talking, uh, data security.

So check those out in your favorite podcast feed. Thank you very much for listening to this episode of the Tech Field Day podcast. If you enjoyed this discussion, please do subscribe.

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