The rapid evolution of artificial intelligence is transforming cybersecurity. AI offers unprecedented opportunities to defend against increasingly complex and automated threats. It is emerging as a central pillar of modern security strategies.
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AI enables defenders to detect anomalies and automate threat responses. It allows security teams to act faster, scale their operations, and outpace attackers. However, significant challenges remain, from adversarial AI to the cultural inertia of legacy systems.
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“It’s very early days for AI in security,” says Richard Stiennon, a cybersecurity expert.
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“I have found 84 startups with various AI agents or which hope to deploy guardrails to protect companies from mishandling of data by users of AI. It’s way too early to say that any of them are having an impact on the ecosystem.
That said, the future is clear. AI will be part of every cyber defense position.”
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Tomer Weingarten, CEO of SentinelOne, echoes this sentiment. He notes that AI’s role is rapidly expanding but far from mature.
AI’s journey in cybersecurity began with basic machine learning. It evolved into predictive AI, which identifies patterns and anticipates threats based on historical data. Today, AI has moved into the generative phase, opening up new possibilities for threat detection and response.
Weingarten points to the rise of specialized AI models as a key differentiator in the future of cybersecurity. Unlike general-purpose large language models trained on text, specialized security models are built on security-specific datasets. “Instead of training a language model on books and speeches, we’re training security models on devices, logs, and behavioral patterns,” says Weingarten.
“This allows AI to detect subtle anomalies that general-purpose models might miss.”
The next leap forward is AI-driven automation—specifically, autonomous security operations. With automation, AI won’t just identify threats; it will also execute actions to respond and remediate incidents in real-time. This evolution has the potential to dramatically scale cybersecurity operations.
“The volume of work that’s happening can now become two, five, or even ten times more efficient,” Weingarten explains. “AI allows security teams to prompt machines to handle tasks autonomously, freeing up humans for strategic initiatives.”
Despite AI’s promise, it is still in its early stages of adoption. Stiennon’s observation highlights the fragmented nature of the current landscape, with dozens of startups exploring AI-driven cybersecurity tools but few having a meaningful impact yet.
The growing use of AI by attackers further complicates the landscape. Hackers are leveraging AI to automate exploits, evade detection, and identify vulnerabilities at an unprecedented pace.
Ai-driven security transformation begins
“Attackers think the same way we do,” Weingarten observes. “They look for weaknesses and ask themselves: what isn’t being protected?”
This adversarial use of AI creates an arms race where defenders must adopt AI not just to respond to threats but to anticipate and preemptively block them. Generative AI also faces inherent limitations.
While tools like large language models can assist with identifying known vulnerabilities or automating workflows, they lack creative reasoning. “Generative AI can only surface what it already knows,” Weingarten explains. “It cannot yet think outside the box to anticipate novel attack vectors.”
While AI automates repetitive tasks and scales security operations, it cannot fully replace human expertise.
Organizations must strike a balance between automation and oversight, ensuring that humans remain involved in interpreting complex scenarios and guiding AI-driven systems. The role of AI in cybersecurity is like a doctor who is a general practitioner in the healthcare system. Generative AI is like a primary care physician—it knows a little about a lot of things.
But for specialized issues, you need experts. In cybersecurity, specialized AI models can act as those experts to find patterns and anomalies that general AI might overlook. This analogy highlights the importance of collaboration between humans and AI.
As AI systems grow more sophisticated, security professionals will play a critical role in refining models, interpreting findings, and making decisions in scenarios where AI lacks context or creativity. While it is still early days for AI in cybersecurity, both Weingarten and Stiennon agree that AI will soon become a foundational element of every cyber defense strategy. Specialized models will continue to evolve, enabling autonomous security systems capable of identifying and responding to threats faster than humans ever could.
Weingarten foresees a future where AI not only secures systems but transforms how software is developed and deployed. AI-driven secure coding practices will allow developers to preemptively identify vulnerabilities, reducing risks at the source. “The entire code-to-cloud process will be automated and secured by AI,” he predicts.
At the same time, organizations must prepare for the challenges ahead—adversarial AI, fragmented tools, and the limitations of early-stage models. By focusing on innovation, collaboration, and real-world value, the cybersecurity industry can harness AI’s potential to build stronger, faster, and more resilient defenses. AI is transforming cybersecurity, but we are still at the starting line.
The AI ecosystem remains fragmented, with many AI tools still proving their worth. Yet the future is clear: AI will be integral to every aspect of cyber defense. For leaders like Tomer Weingarten, the focus must remain on solving real-world problems and anticipating the challenges of tomorrow.
“You can’t just think about solving one piece of the puzzle,” he says. “AI is the glue that brings everything together.”
By combining AI-driven innovation with human expertise, the industry has an opportunity to stay ahead of attackers and build the foundation for a more secure digital future. The revolution is underway—now it’s up to defenders to seize the moment.
