The CISO’s Strategy for Staying Ahead in the Age of AI

The cat and mouse game between security teams and threat actors is nothing new. But artificial intelligence (AI) has changed the pace. While AI is helping organizations innovate faster, it’s also enabling cybercriminals to scale their efforts, adapt in real time, and strike with greater precision. The rules haven’t changed, but the speed and complexity have.

Security leaders are now operating in an environment that’s more distributed, more dynamic, and harder to control. AI workloads are fueling a surge in network traffic, with 1 in 3 organizations reporting that data volumes have more than doubled in the past two years. At the same time, breach rates continue to rise, exposing cracks in legacy defenses.

I took a deep dive into the insights of 211 CISOs from our global 2025 Hybrid Cloud Security Survey to understand how today’s security leaders are responding. One thing is clear: this new reality demands a different approach. Static controls and siloed visibility no longer cut it.

To stay ahead, CISOs are going on the offense, reassessing the risks tied to public cloud, rethinking how and where AI is deployed, and putting visibility at the center of everything they do.

Rethinking the Role of Public Cloud

The role of public cloud is being re-evaluated. Once viewed as the fast lane to digital transformation, it’s now under sharper scrutiny from security leaders. In 2025, 75 percent of CISOs say public cloud presents a greater security risk than any other environment, reflecting a growing concern around the infrastructure supporting AI workloads and the exposure they introduce.

Nearly three-quarters (73 percent) of CISOs are now considering repatriating data from public to private cloud. But the goal isn’t to reverse innovation, it’s to regain control. With sensitive workloads at stake, many are prioritizing environments where visibility, governance, and access control can be more tightly enforced.

The challenge itself isn’t new, but the urgency is. Protecting sensitive data has always been fundamental to security. What’s changed is how that data is accessed, processed, and exposed through AI systems. Internal Large Language Models (LLMs) often pull from high-value datasets that, if compromised, could expose intellectual property and damage years of innovation.

More executive teams are waking up to this reality. Conversations are shifting from how to use AI to what happens if it’s breached. Questions about exposure, data leakage, and the potential loss of intellectual property are now driving security decisions at the top level.

And the concern is well-founded, as 47 percent of organizations claim to have seen a rise in attacks targeting their LLMs. These systems are valuable, vulnerable, and increasingly under pressure. Public cloud still has its place, but it’s no longer a default decision. Security teams are approaching it with more caution, making calculated choices based on risk, not just convenience.

Balancing Innovation and Risk

As concerns grow around where AI lives and how it’s accessed, CISOs are being pulled in multiple directions. Securing public cloud workloads is only part of the challenge. The real complexity lies in managing how AI is deployed internally, how sensitive data is being used, and how security operations can keep pace.

This pressure is showing up in three key areas. First, there’s AI for security operations efficiency. Security teams are expected to move faster while dealing with more data, more alerts, and a wider surface area. AI is helping bridge the gap. By automating triage, escalation and ticketing, teams are cutting through noise and focusing on what matters. In some organizations, automated playbooks are already replacing the need for six to eight analysts, freeing up staff to focus on engineering and program development.

Second, internal AI models require secure architecture. That includes strict access controls, identity frameworks, and real-time oversight. For many organizations, this is the first time they’re working with something of this scale. That unfamiliarity often brings uncertainty and blind spots, especially when it comes to safeguarding the data being used to train and run these models.

Third, AI must be deployed in ways that support meaningful business outcomes. It must improve products, enhance operations and drive efficiency, without introducing new risk. That balance is now part of the CISO’s core responsibility.

To manage this, organizations are putting clear guardrails in place. Some are restricting the use of public AI platforms, disallowing file uploads, and blocking copy-paste features to prevent the accidental exposure of proprietary information.

The truth is that organizations that don’t adopt AI will struggle to keep up. But moving too fast without understanding how to secure these technologies can create even bigger problems. The key for CISOs is finding a balance that enables innovation without opening the door to avoidable threats.

Staying On the Offense With Visibility

As CISOs work to find that delicate balance, one theme keeps coming up: you can’t secure what you can’t see. AI is generating more traffic and more complexity, which makes visibility the baseline for staying in control.

The ability to see all data in motion is more critical than ever. As a result, 86 percent of CISOs say deep observability—the combination of log data and network telemetry—is essential to securing hybrid cloud environments. Yet nearly half still lack full insight into East-West traffic, where many of today’s most dangerous threats can go undetected as they move laterally within the network.

Every CISO should be asking: Do I have complete visibility into all data in motion across my environment? If the answer isn’t a confident yes, then it’s time to figure out how to get there. Without complete visibility, it’s impossible to play offense. It’s impossible to move ahead of the threat. Because in a landscape shaped by AI, the advantage always belongs to those who can see clearly, act quickly, and stay one step ahead.

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