This conversation at RSAC 2026 explores securing and scaling artificial intelligence in enterprise environments. Daniel Bernard of CrowdStrike and Mark Hughes of IBM join hosts Dave Vellante and Christophe Bertrand on theCUBE Research stage to discuss AI-enabled security operations center transformation, agent orchestration and the newly announced CrowdStrike–IBM collaboration. Bernard highlights CrowdStrike product and platform expertise around Charlotte AI and AgentWorks, and they describe how custom agents enable analysts to scale outcomes without simply hiring more staff. Hughes outlines IBM’s approach to autonomous security operations centers, identity-driven orchestration and operationalizing governance and fail-safe controls across complex legacy estates, and they explain how watsonx governance blueprints and Atom orchestration reduce total cost of ownership.
Key takeaways include accelerating platform adoption through agentic automation, prioritizing data and identity hygiene, and embedding governance and fail-safe controls to operationalize AI securely and at scale. The CrowdStrike–IBM collaboration focuses on integrating agent orchestration and governance to help enterprises implement autonomous SOC workflows and improve security operations efficiency.
Watch the full conversation for practical insights on AI governance, autonomous SOC design, identity-driven orchestration and agent strategy for modern cybersecurity programs.
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Daniel Bernard, Crowdstrike & Mark Hughes, IBM
This conversation at RSAC 2026 explores securing and scaling artificial intelligence in enterprise environments. Daniel Bernard of CrowdStrike and Mark Hughes of IBM join hosts Dave Vellante and Christophe Bertrand on theCUBE Research stage to discuss AI-enabled security operations center transformation, agent orchestration and the newly announced CrowdStrike–IBM collaboration. Bernard highlights CrowdStrike product and platform expertise around Charlotte AI and AgentWorks, and they describe how custom agents enable analysts to scale outcomes without simply hiring more staff. Hughes outlines IBM’s approach to autonomous security operations centers, identity-driven orchestration and operationalizing governance and fail-safe controls across complex legacy estates, and they explain how watsonx governance blueprints and Atom orchestration reduce total cost of ownership.
Key takeaways include accelerating platform adoption through agentic automation, prioritizing data and identity hygiene, and embedding governance and fail-safe controls to operationalize AI securely and at scale. The CrowdStrike–IBM collaboration focuses on integrating agent orchestration and governance to help enterprises implement autonomous SOC workflows and improve security operations efficiency.
Watch the full conversation for practical insights on AI governance, autonomous SOC design, identity-driven orchestration and agent strategy for modern cybersecurity programs.
play_circle_outlineCrowdStrike and IBM partnership to build autonomous, AI-driven SOCs
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play_circle_outlineCharlotte AI and AgentWorks: Agent-Based Orchestration, Digital Twins for Analysts, and IBM–CrowdStrike Consultancy for Autonomous Endpoint Security
In this interview from RSAC 2026, Daniel Bernard, chief business officer of CrowdStrike, joins Mark Hughes, global managing partner of cybersecurity services at IBM, to talk with theCUBE's Dave Vellante about how the two companies are transforming the security operations center for the agentic AI era. Bernard and Hughes detail a joint initiative to remap today's SOC into an autonomous, AI-driven operation — combining CrowdStrike's Charlotte AI and Falcon platform with IBM's orchestration expertise and Atom platform. Bernard explains how agentic AI has evolved...Read more
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How will the partnership between IBM and CrowdStrike—combining IBM’s Atom platform with CrowdStrike’s AI-powered technologies (including Charlotte AI and the CrowdStrike product family)—change how Security Operations Centers (SOCs) operate, particularly around detection, alerting, orchestration, and remediation?add
How is AI accelerating platform adoption, and how do agents (like Charlotte) and tools such as AgentWorks enable orchestration of Falcon’s modules and scaling of capabilities (for example, SOC detection and response) without hiring additional staff?add
How are orchestration tools and agent-based automation (for example CrowdStrike) transforming the security operations center, analyst roles, and broader security workflows (including identity and cloud security)?add
What is the number-one challenge your customers are asking you to solve (for each company represented)?add
What should organizations focus on when deploying agent-based AI systems across the enterprise?add
>> Hi, everybody. Welcome back to RSAC 2026, theCUBE's live coverage here at Moscone West. We're winding down. The crowd is filtering in, filtering out. My name's Dave Vellante. Daniel Bernard is here. He's the Chief Business Officer at CrowdStrike. Great to see you DB. Thanks for making some time. It's-
Daniel Bernard
>> Great to be here....
Dave Vellante
>> it's kind of becoming a tradition, isn't it?
Daniel Bernard
>> It is.
Dave Vellante
>> And Mark Hughes from IBM, we just saw you at=
Mark Hughes
>> ....
Dave Vellante
>> MWC. We had a great conversation.
Mark Hughes
>> Great to be back.
Dave Vellante
>> From Barcelona to San Francisco, welcome.
Mark Hughes
>> Thank you.
Dave Vellante
>> You guys made some news-
Daniel Bernard
>> We did.
Mark Hughes
>> Yeah....
Dave Vellante
>> today.
Mark Hughes
>> We did.
Dave Vellante
>> It's awesome. Let's get the hard news out of the way and then we'll get into some of the trends in-
Daniel Bernard
>> Sure....
Dave Vellante
>> business.
Daniel Bernard
>> Well, we're really excited to be working with the folks over at IBM and going and actually remapping the SOCs of today to something autonomous and ready for tomorrow. IBM is a great platform. The Atom platform, we'll talk more about it, but what we see happening in the market is a broader need to revolutionize how the SOC operates. And together we're delivering that, our technology, their expertise, and also their technology, too, on top of it, so we can make these SOCs ready for the agentic era.
Mark Hughes
>> Yeah. And Dave, what we're saying is that the CrowdStrike technology is one which is incredibly mature, especially with now Charlotte AI and the AI that's built natively into the platform. And so not just the next-gen SIEM, but all of the CrowdStrike family of products. And being able to now use that in a way in which we can really drive better outcomes when you can orchestrate that power into complex enterprise environments where they really struggle to detect and do the alerting and beyond, but then actually take that and actually find the way in which they can remediate that across their enterprise. So it's that really being able to bring and marry those two things together that is incredibly powerful. We're super excited about it.
Dave Vellante
>> Yeah. The AI SOC is kind of a big topic here. I remember, I think it was three years ago, Daniel, when you guys introduced Charlotte-
Daniel Bernard
>> Yeah....
Dave Vellante
>> at Fal.Con.
Daniel Bernard
>> Right.
Dave Vellante
>> And I went, "Okay, this is a sign of things to come."
Daniel Bernard
>> Yeah.
Dave Vellante
>> It was early days and it's now maturing. What impacts are you seeing AI have on SOC analysts, on the SOC experience?
Daniel Bernard
>> Sure. Two dimensions. The first is platform adoption overall. AI is a platform adoption accelerant because you look at Charlotte and Charlotte becomes the orchestrator of using a lot of other capabilities that Falcon has to offer, over 35 different modules. The front door of modules is becoming agents. And Charlotte's not alone. We have over 10 other agents live on the platform. And we debuted AgentWorks that was in beta and now that is something that our customers and partners are using where you can use NVIDIA technology in the platform and create your own agent. So it puts Mark his team in the driver's seat to say, "Hey, this team over here, this customer, they need more detection response capabilities in their SOC." You don't actually need to hire more people for that. You take the people that are there and you pair them up with their digital twins with agents. And you can create a custom agent for every client. Or you can use Charlotte, who's this orchestrator of the whole Falcon platform. And you can do that all under the auspices of IBM mapping, not only the strategy, but executing on that strategy.
Dave Vellante
>> Are agents an endpoint?
Daniel Bernard
>> Well, it's interesting that you asked that because every agent needs protection. So if you look at our TAM, it's just growing exponentially right now because there's all this new... It's not like we got to go to a agent and say, "Stop using your legacy security technology, put this new technology." It's all green space. It's all a big opportunity, but agent lifecycle management is such an important part of security. We're talking about agents specifically designed to operate security and deliver outcomes for customers. So there's a lot. We could talk about agents for a long time.
Mark Hughes
>> We certainly can. And I just want to pick up, Dave, on that point about the SOC and what we're seeing and the operation there. So we really see that absolutely the SOC is transforming in a way in which we've now really seen that happening. We have that orchestration tool with the likes of CrowdStrike deployed into many, many clients now, over a hundred, in fact. And what we see there is a lot of the traditional jobs that were being done by humans, Layer 1 analysts, Layer 2 analysts even in many of those environments is now being completely overtaken by what those digital workers. As DB just said, those digital twins that come in that actually now really take the role of where the person used to do that work of the analysis and looking at alerts. All that now is done by the agents that kind of orchestrate that into the broader response that's required across the enterprise. So that's one area. And we have a whole number of orchestration agents that we've put in place now that are built on that, working with CrowdStrike, and some others as well, and also where there are some pieces of legacy technologies in organizations where they don't have native agents enabled. So again, there's an agent build function that we can drop in there that allows that to be built as well. But then you then begin to expand that, which is really where CrowdStrike is doing that as well, where we're looking at how that now works in the identity space, for example. And where you now take this to is you can now see a world where we have those agents orchestrating, not just in what was the traditional security operation center environment, but also now in the identity space, in the cloud security space. So you now begin to see how they work together and create almost an autonomous workflow of security in a very different way from how we've seen before.
Dave Vellante
>> We've got a product company, you guys are a product company and, obviously, a consultancy and world class. I'm going to ask you each question. What's the number one challenge and problem that your customers at IBM are asking you to solve? And then same question for you, DB.
Daniel Bernard
>> Sure.
Mark Hughes
>> First and foremost, it's about they've got a massive sprawl of tools, a lot of legacy in their environment, and how do they actually get visibility across all of that? And most importantly, how do they get to contextualization where we can now deploy Charlotte AI in conjunction with AI tools like Atom, for example, and our autonomous SOC in an environment where they can actually get that contextualization? So the number one problem they have is how do they now expand that, especially as they're now deploying agents themselves, as DB was saying, into that environment where they need to get the visibility across all of those different assets, agents, and traditional legacy environments to then actually work out because the threat actors are being able to pick off where they can look between the ability for the AI to find and find the weaknesses and where things are, but also how we now orchestrate the response. The AI, the threat actors are using AI themselves to be able to do that. So it's that ability to find and see the whole enterprise and be able to orchestrate outcomes across that. That's the number one problem that most of our clients are facing.
Dave Vellante
>> What's the Venn look like, DB, with regard to what Mark just said? Like what are the similarities and what other things-
Daniel Bernard
>> Sure....
Dave Vellante
>> are you being pushed through?
Daniel Bernard
>> So the question we get, to answer your first one-
Dave Vellante
>> Yes, please....
Daniel Bernard
>> and then I'll come back to that, is how do I secure AI? And what is veiled in there is how cab I as a security professional be an AI accelerant in my organization? Nobody wants to be on the wrong side of history. The CEO, the board is saying, "Go use more AI faster because we want to see productivity rise in costs flat line, decline, some variation of thereof." So security can actually be, in this transformation, an accelerant. The biggest question that the customer's asking is it's changing by the hour, if not the week. Last year, we were talking about GenAI and GenAI is still great, and the year before that, we had just realized what ChatGPT was. What's an LLM? And now we're talking about OpenClaw, Claude Code, NemoClaw. And what's so exciting is now we're actually getting to agentic outcomes really for the first time where you can say, "I have an idea," and it'll turn your idea into an outcome. Before it was like it was a better version of a search engine. Now, it's like I have an idea and it can build something around it and it can iterate on it. But the security around that whole process is still not understood, and that's where we get into everything Mark talked about, which is, how do I rethink my entire security stack, my people, my process, my technology to be ready for the next decade in cybersecurity?"
And that's where, by the way, most companies, they don't know what to do, where to start. It's like, "How do you untie this thing?" It's where IBM comes into play. Not only will they help do it, they'll write the strategy, they'll operate it. They'll be the guide and give industry benchmarks on what they need to do, present that lower total cost of ownership, and use the best-of-breed technologies to bring it to bear, which is how we and why we work together and in such a complementary way.
Dave Vellante
>> So Mark, security, compliance, governance, the nirvana has always been to make those an accelerant. Are we finally at a point... I mean, you're still seeing a lot of Shadow AI, which is scaring a lot of people, so something bad is going to happen there, but my sense is that organizations that have strong governance are saying, "We want to make security an accelerant and we'll do so by making sure that you're not bolting it on, it's designed in. And by doing that and having that as part of the workflow, we're going to get products to market faster." Is that a pipe dream by me or is it actually happening?
Mark Hughes
>> No, that's actually now happening. And I really do see that happening. As long as clients and large enterprises can really embrace not just the underlying technology, for example, from CrowdStrike and others, which they may already have in their environment, but they can then bring and orchestrate that with agents to now reimagine a lot of the workflows that they've traditionally been operating at. Because the thing is that is now all too slow, not just to deal with some of the threats they have, but also to deal with the pace of introduction of some of the agents and AI that they want to do to improve their business processes. So think about the fact that the traditional life cycle of developing new software, deploying it into an organization, of testing it, and of bringing that into prod. All of those things now, we have developed agents and IBM that can do that job and do that job with guardrails and with blueprints, for example, of the right levels of access that can then obviously then monitor what levels of access they have. And as DB was saying earlier on, all of that learning that those agents are doing as well is constantly changing that. So we're now in a situation where get that right, then that massively accelerates what organizations can do. And I do see that those organizations that haven't got that thinking right with the right tools in place to be able to do that are going to be held back. But I can definitely tell you that those that have got that right, have thought that through, have deployed the tools in the right way, are now absolutely in a position where they can make that life cycle much more effective for them to deploy their game-changing AI that benefits their clients, changes their workflow, increases their profit and their top line by really making sure that they can bring that in quickly.
Dave Vellante
>> And does that start with sort of a culture of governance? And DB, I'm wondering-
Daniel Bernard
>> Sure....
Dave Vellante
>> if when you see a culture of governance, can you actually make security an accelerant? And is it very difficult to do when there's not a culture of governance?
Daniel Bernard
>> Well, organizations fall into one of two buckets today. People are saying, "Go adopt everything," or people saying, "Don't adopt anything." And the reality is you kind of need to be more the first, but you need to do it the right way. I mean, you don't want to be a Luddite, you don't want to be on the wrong side of history.
Dave Vellante
>> You're going to be out of business.
Daniel Bernard
>> You're going to be out of business. Every business is going to be an AI business. It's going to be powered by, using with, but the first part is we need to set the search party free to see where the hell the AI is in the company. People are bringing things to work. It's the Wild West of AI, and here's one observation. Feel free to comment on. What I've noticed so far is you look at people that are using AI tools. It's an amplification factor. Here's what it is. People that are using AI that are smart and productive are now like 10 to a hundred times more productive and smart. An inquisitive, smart person is going to know how to prompt, is going to be inquisitive and use the technologies and theoretically use them in the right way. But then there's a whole nother set of people, the idiots, the people that are bad are now 10 times worse than they were before because they're using AI, too, and the AI slop bucket is overfilling with junk. It's like, "Wait, this guy or gal doesn't know what he's doing, or what she's doing, and all of a sudden I got 10 times more emails from this person and they're still bad." So I think right now we're seeing the productivity gains, but it's also this interesting adolescence period of people are using and tinkering with AI, but we don't know where it is, we don't know who's using it. We don't know what tools are being used, and there's no real governance standards yet to even do the governance correctly. So that's kind of like where the market is today. It's like, "What the heck is going on in the digital Wild West of AI?"
Mark Hughes
>> Yeah, yeah.
Dave Vellante
>> Somebody wrote a blog, Don't Let AI Make You Dumber.
Mark Hughes
>> Yeah. Yeah-
Daniel Bernard
>> ....
Mark Hughes
>> that's a good point, Dave. And so being able to orchestrate that with the right guardrails, and here at IBM, we developed a bunch of tools natively like watsonx.governance that actually creates the blueprints and says that, "Yeah. No, you can bring this stuff in. You can bring it in quickly and get it into product. Get it into your environment in a safe way, but having those guardrails around it and so that you can really understand the various factors that need to be put in place for that to happen is absolutely essential, which really is the big unlock which turns it from just random adoption, productivity gains, absolutely. But the real power that we see in enterprises is where they're designing AI to reimagine their business processes, which fundamentally changes how they serve their customers, serve their markets. And that's where you've got this sort of almost dichotomy of productivity tooling which is very good, but you've also got that underlying enterprise adoption, which is becoming much more prevalent now. And that's where we see the big shift, and that's where there's real opportunity to make sure that that becomes the way in which you accelerate that.
Dave Vellante
>> I want to circle back, Daniel, to your two buckets. I like how you make things really easy to understand. And you're right, you've got the Luddites and you've got the people who are leaning in, and you want to be in that category. John Furrier loves to invoke Andy Grove, let chaos reign, and then reign the chaos in.
Daniel Bernard
>> Yes.
Dave Vellante
>> So I want to be in that category. However, I'm nervous about it. So can you give me a sandbox? When we first started on this recent AI journey, it was, "Okay, we get a million ideas for use cases, let's prioritize them, and let's focus on the ones that are going to make a big difference." I feel like we're back in that cycle again now with everybody playing with OpenClaw and Perplexity Computer. We're dramatically opening up the reservoir of people who can really get interesting things done with AI, but I'm nervous and I want to give them a sandbox to play with-
Mark Hughes
>> Certainly....
Dave Vellante
>> that we can then reprioritize. How do I do that?
Mark Hughes
>> Well, you start with basically data sits underneath it all. So we've got to get busy on data and we've got to understand what we're ingesting and pulling into models and what we're using in the enterprise in a way in which perhaps we haven't really had to think about that hard for some time yet. And of course, then identity plays a huge thing. Each of the agents have identities, they have privileges. You want them to start working together in agentic way, which we have now in IBM across not just security space, but in many other areas as well. And then you want them to start determining how they work together as well. So all of those things are not new to us. We know how to do those things, but we now just have to do that in a much faster, much more focused way. And of course, we're using AI to do that. So we can get AI to create those blueprints, to create those deterministic effectively identities and how that they should behave and when they're out of band in terms of their behavior. And a lot of that comes from the wealth of expertise we have here at the show to be able to now incorporate that in so that we can really orch
Dave Vellante
>> Yeah.
Daniel Bernard
>> Correct, correct. I mean, this is fundamentally a detection-and-response problem all over again. It's just a whole new attack service. So you need to be able to see what the heck is going on, govern it, and respond. And if you can do that at a much faster speed than you were able to before, because agents can proliferate and pop up and be created instantly, they can also be rather ephemeral, like in the good old days of VMware where we used to see each other and talk there, like spin up an instance. It's a new world, and in this world, you can spin up a digital workforce, a digital security team overnight, and you can shut it down in an instant, too, but you need to have the button. You need to know what's going on. You need to have a human somewhere in the loop so that it can be governed appropriately, and you need to have a fail-safe switch to be able to shut all this stuff down. And I think if you have those things, you can at least put your head on the pillow at night and know that, "Okay, these are the fundamentals to start really seeing the outcomes in a way that is secure."
Dave Vellante
>> So Mark, you and I talked about this, I think, in Barcelona. And Daniel, based on what you just said, I think it's relevant because there were a lot of people early on in this journey that were thinking, "Wow, we've really got to get our data act in order before we do anything with AI." And rather you want to get your data infrastructure, your ability to observe what's happening and then go for it. Then, let AI help cleanse the data.
Mark Hughes
>> Absolutely. Absolutely.
Dave Vellante
>> Get on that curve-
Mark Hughes
>> Yeah, yeah....
Dave Vellante
>> because as Jassy says, there's no compression algorithm for experience.
Daniel Bernard
>> Yeah, right.
Dave Vellante
>> You want that experience because your competitors are on that curve. Is that what you're seeing now that-
Daniel Bernard
>> Yeah, but-...
Dave Vellante
>> that that's the learning? Or-...
Daniel Bernard
>> the learning is also manifesting in the form of people's use of new technologies for the first time. So the learning is you might be multi-model from an LLM perspective. You're going to be multi-cloud. Now, there's all these neoclouds as well. So I think you have like multiple axes and dimensions of learning and experimenting. It's sort of a renaissance of the stack right now, which is really, really exciting. Again, we just talked about how you don't take the learnings that you have and throw them out the window. You apply the principles and the knowledge and the experience in to where it's relevant, but you're doing it on new attack surfaces and new places with new geopolitical concerns. And maybe you're thinking about data sovereignty in new ways that you weren't thinking about that before. And that's why the space is really fun. Half the companies that you... You go to NVIDIA GTC, half these companies, they didn't exist three to five years ago. And they're not just going and closing anecdotal little deals. They're closing multi-billion dollar deals. People are doing inference there. There's a whole new subset of chips that are coming out. There's these AI factories that are being built. It's a whole new world, and that's where the experience matters in the past, but getting the game-time film on these different technologies and these different places is super critical to being effective.
Dave Vellante
>> Well, and this is where security is so important because you mentioned GTC. The most important chart that Jensen threw up on his keynote was that XY axis and the Paretos of all the future of systems that are coming out, but on the horizontal axis was the new business model. So the vertical axis was training and your hyperscaler, great. You get a new set of chips and it's going to be cheaper to train, wonderful. You'll eventually get your CapEx return. That horizontal axis was the most interesting. That's the inference access. That's the customer experience access. It was a freemium model and then a lightweight 20 bucks a month, $200 a month, and then really heavy, expensive, but worth it on the right-hand side.
Mark Hughes
>> Exactly.
Dave Vellante
>> And that's a new revenue model that security enables. Without security, you're not going to be able to-
Mark Hughes
>> You're not going to be able to-...
Dave Vellante
>> to-...
Mark Hughes
>> unlock that....
Dave Vellante
>> to... and you're going to be tapping intelligence, manufacture that AI factory through APIs, accessing tokens in the form of intelligence, and that's going to be your new business model.
Mark Hughes
>> Exactly. And what we see there is just the complete reimagining of a lot of the workflows. I've been speaking with a lot of clients recently where we're orchestrating the various AI that we have now in the security space, and they're saying to me, "Well, where is this part of the process?" And I'm saying, "That doesn't exist anymore because the agents are now doing that job. It's not replicating what we've done in the past." We have to reimagine that. And it's that unlock that we now are seeing happening in many organizations. As DB just said, we can spin up security processes autonomously with agents managing that. We are reimagining really how all of that actually works and happens. So we see at IBM now, we talk about the autonomous security program. So the idea that, be it identity, be it in the SOC, or be it in other areas, that we can orchestrate all of those things together to provide the outcomes that are going to be appropriate for the organization. Very different from what we have today and what we've had for the last few years. Really exciting. Still bounded on the same principles and found on the same principles we've been working with, but now completely reimagining that workflow in a way in which actually makes it less of a thing, less of a separate thing, but powered by really foundationally strong tools that can actually do that job.
Dave Vellante
>> Well, guys, congratulations on the partnership. DB, you're like the ecosystem alpha. I mean, I've been watching the CrowdStrike network grow and go and grow. And I know you've been a big part of it and you've got a great team behind you. So thanks you guys for coming in.
Daniel Bernard
>> The Falcon flies all around, and we're so excited for the market-
Mark Hughes
>> ....
Daniel Bernard
>> to know the great things that we're doing together.
Mark Hughes
>> Thanks, DB. Thanks, Dave. Good to see you.
Dave Vellante
>> All right. We'll see you tomorrow and we'll maybe-
Daniel Bernard
>> Perfect....
Dave Vellante
>> see you tonight. Thanks so much.
Mark Hughes
>> See you around.
Daniel Bernard
>> Thanks so much, Dave.
Dave Vellante
>> Thanks for watching. This wraps up day three at RSAC 2026. We'll be back tomorrow first thing, let's see, 9:30 AM Pacific Time. Dave Vellante for Christophe Bertrand. Watch theCUBE. We'll see you tomorrow.
Dave Vellante