This article is part of VentureBeat’s special issue, “The cyber resilience playbook: Navigating the new era of threats.” Read more from this special issue here.
Enterprises run the very real risk of losing the AI arms race to adversaries who weaponize large language models (LLMs) and create fraudulent bots to automate attacks.
Trading on the trust of legitimate tools, adversaries are using generative AI to create malware that doesn’t create a unique signature but instead relies on fileless execution, making the attacks often undetectable. Gen AI is extensively being used to create large-scale automated phishing campaigns and automate social engineering, with attackers looking to exploit human vulnerabilities at scale.
Gartner points out in its latest Magic Quadrant for Endpoint Protection Platforms that “leaders in the endpoint protection market are prioritizing integrated security solutions that unify endpoint detection and response (EDR), extended detection and response (XDR) and identity protection into a single platform. This shift enables security teams to reduce complexity while improving threat visibility.”
The result? A more complex threat landscape moving at machine speed while enterprise defenders rely on outdated tools and technologies designed for a different era.
The scale of these attacks is staggering. Zscaler’s ThreatLabz indicated a nearly 60% year-over-year increase in global phishing attacks, and attributes this rise in part to the proliferation of gen AI-driven schemes. Likewise, Ivanti’s 2024 State of Cybersecurity Report found that 74% of businesses are already seeing the impact of AI-powered threats. And, nine in 10 executives said they believe that AI-powered threats are just getting started.
“If you’ve got adversaries breaking out in two minutes, and it takes you a day to ingest data and another day to run a search, how can you possibly hope to keep up?” Elia Zaitsev, CTO of CrowdStrike noted in a recent interview with VentureBeat.
The new cyber arms race: Adversarial AI vs. defensive AI on the endpoint
Adversaries, especially cybercrime syndicates and nation-state actors, are refining their tradecraft with AI, adding to their arsenals faster than any enterprise can keep up. Gen AI has democratized how adversaries, from rogue attackers to large-scale cyberwar operations, can create new weapons.
“Even if you’re not an expert, gen AI can create scripts or phishing emails on your behalf,” George Kurtz, CrowdStrike CEO and founder at the recent World Economic Forum, said in an interview with CNBC. “It’s never been easier for adversaries. But the good news is, if we properly harness AI on the defensive side, we have a massive opportunity to stay ahead.”
As Gartner advises: “AI-enhanced security tools should be viewed as force multipliers rather than standalone replacements for traditional security measures. Organizations must ensure that AI-driven solutions integrate effectively with human decision-making to mitigate risks.”
Etay Maor, chief security strategist at Cato Networks, told VentureBeat that “adversaries are not just using AI to automate attacks — they’re using it to blend into normal network traffic, making them harder to detect. The real challenge is that AI-powered attacks are not a single event; they’re a continuous process of reconnaissance, evasion and adaptation.”
Cato outlined in its 2024 business highlights how it expanded its secure access service edge (SASE) cloud platform five times in the last year, introducing Cato XDR, Cato endpoint protection platform (EPP), Cato managed SASE, Cato digital experience monitoring (DEM) and Cato IoT/OT Security, all of which aim to streamline and unify security capabilities under one platform. “We’re not just taking share,” said Shlomo Kramer, Cato co-founder and CEO. “We’re redefining how organizations connect and secure their operations, as AI and cloud transform the security landscape.”
Unifying endpoints and identities is the future of zero trust. Adversaries are quick to capitalize on unchecked agent sprawl, which is made more unreliable due to a surge in dozens of identities’ data being integral to an endpoint. Using AI to automate reconnaissance at scale, adversaries have an upper hand.
All these factors, taken together, set the stage for a new era of AI-powered endpoint security.
AI-powered endpoint security ushers in a new era of unified defense
Legacy approaches to endpoint security — interdomain trust relationships, assumed trust, perimeter-based security designs, to name a few — are no longer enough. If any network’s security is based on assumed or implied trust, it is as good as breached already.
Likewise, relying on static defenses, including antivirus software, perimeter firewalls or, worse, endpoints with dozens of agents loaded on them, leaves an organization just as vulnerable as if they had no cyber defense strategy at all.
Gartner observes that: “Identity theft, phishing and data exfiltration are workspace security risks that require further attention. To address these issues, organizations need a holistic workspace security strategy that places the worker at the center of protection and integrates security across device, email, identity, data and application access controls.”
Daren Goeson, SVP of unified endpoint management at Ivanti, underscored the growing challenge. “Laptops, desktops, smartphones and IoT devices are essential to modern business, but their expanding numbers create more opportunities for attackers,” he said. “An unpatched vulnerability or outdated software can open the door to serious security risks. But as their numbers grow, so do the opportunities for attackers to exploit them.”
To mitigate risks, Goeson emphasizes the importance of centralized security and AI-powered endpoint management. “AI-powered security tools can analyze vast amounts of data, detecting anomalies and predicting threats faster and more accurately than human analysts,” he said.
Vineet Arora, CTO at WinWire, agreed: “AI tools excel at rapidly analyzing massive data across logs, endpoints and network traffic, spotting subtle patterns early. They refine their understanding over time — automatically quarantining suspicious activities before significant damage can spread.”
Gartner’s recognition of Cato Networks as a Leader in the 2024 Magic Quadrant for Single-Vendor SASE further underscores this industry shift. By delivering networking and security capabilities through a single cloud-based platform, Cato enables organizations to address endpoint threats, identity protection and network security in a unified manner — which is critical in an era when adversaries exploit any gap in visibility.
Integrating AI, UEM and zero-trust
Experts agree that AI-powered automation enhances threat detection, reducing response times and minimizing security gaps. By integrating AI with unified endpoint management (UEM), businesses gain real-time visibility across devices, users and networks — proactively identifying security gaps before they can be exploited.”
By proactively preventing problems, “the strain on IT support is also minimized and employee downtime is drastically reduced,” said Ivanti’s field CISO Mike Riemer.
Arora added that, while AI can automate routine tasks and highlight anomalies, “human analysts are critical for complex decisions that require business context — AI should be a force multiplier, not a standalone replacement.”
To counter these threats, more organizations are relying on AI to strengthen their zero-trust security frameworks. Zero trust comprises systems that continuously verify every access request while AI actively detects, investigates and, if necessary, neutralizes each threat in real time. Advanced security platforms integrate EDR, XDR and identity protection into a single, intelligent defense system.
“When combined with AI, UEM solutions become even more powerful,” said Goeson. “AI-powered endpoint security tools analyze vast datasets to detect anomalies and predict threats faster and more accurately than human analysts. With full visibility across devices, users and networks, these tools proactively identify and close security gaps before they can be exploited.”
AI-powered platforms and the growing demand for XDR solutions
Nearly all cybersecurity vendors are fast-tracking AI and gen AI-related projects in their DevOps cycles and across their roadmaps. The goal is to enhance threat detection incident response, reduce false positives and create platforms capable of scaling out with full XDR functionality. Vendors in this area include BlackBerry, Bitdefender, Cato Networks, Cisco, CrowdStrike, Deep Instinct, ESET, Fortinet, Ivanti, SentinelOne, Sophos, Trend Micro and Zscaler.
Cisco is also pushing a platform-first approach, embedding AI into its security ecosystem. “Security is a data game,” Jeetu Patel, EVP at Cisco, told VentureBeat. “If there’s a platform that only does email, that’s interesting. But if there’s a platform that does email and correlates that to the endpoint, to the network packets and the web, that’s far more valuable.”
Nearly every organization interviewed by VentureBeat values XDR for unifying security telemetry across endpoints, networks, identities and clouds. XDR enhances threat detection by correlating signals, boosting efficiency and reducing alert fatigue.
Riemer highlighted AI’s defensive shift: “For years, attackers have been utilizing AI to their advantage. However, 2025 will mark a turning point as defenders begin to harness the full potential of AI for cybersecurity purposes.”
Riemer noted that AI-driven endpoint security is shifting from reactive to proactive. “AI is already transforming how security teams detect early warning signs of attacks. AI-powered security tools can recognize patterns of device underperformance and automate diagnostics before an issue impacts the business — all with minimal employee downtime and no IT support required.”
Arora emphasized: “It’s also crucial for CISOs to assess data handling, privacy and the transparency of AI decision-making before adopting such tools — ensuring they fit both the organization’s compliance requirements and its security strategy.”
Cato’s 2024 rollouts exemplify how advanced SASE platforms integrate threat detection, user access controls, and IoT/OT protection in one service. This consolidation reduces complexity for security teams and supports a true zero-trust approach, ensuring continuous verification across devices and networks.
Conclusion: Embracing AI-driven security for a new era of threats
Adversaries are moving at machine speed, weaponizing gen AI to create sophisticated malware, launch targeted phishing campaigns and circumvent traditional defenses. The takeaway is clear: Legacy endpoint security and patchwork solutions are not enough to protect against threats designed to outmaneuver static defenses.
Enterprises must embrace an AI-first strategy that unifies endpoint, identity and network security within a zero-trust framework. AI-powered platforms — built with real-time telemetry, XDR capabilities and predictive intelligence — are the key to detecting and mitigating evolving threats before they lead to a full-on breach.
As Kramer put it, “The era of cobbled-together security solutions is over.” Organizations choosing a SASE platform are positioning themselves to proactively combat AI-driven threats. Cato, among other leading providers, underscores that a unified, cloud-native approach — marrying AI with zero-trust principles — will be pivotal in safeguarding enterprises from the next wave of cyber onslaughts.