During Check Point Software’s Engage 2026 conference in Paris, CTO Jonathan Zanger shared compelling insights into how artificial intelligence is transforming the cyber landscape. As the company navigates emerging threats, Zanger emphasized a paradigm shift in cybersecurity, driven by AI, that has the potential to redefine how organizations protect themselves.
The AI Revolution in Cybersecurity
Zanger pointed out that the current technological era, highlighted by rapid advancements in AI, resembles the seismic shifts introduced by the internet. “2026 is a fascinating year to work in this field,” Zanger remarked, suggesting that unprecedented changes are underway. The convergence of AI with cybersecurity has not just streamlined existing protocols but raised new challenges that demand attention.
Enhanced Detection and Defense Capabilities
The integration of AI into cybersecurity operations has drastically altered how threats are detected and mitigated. Traditionally, cybersecurity relied heavily on the expertise of human analysts to monitor and respond to threats. Zanger discussed how AI has scaled these operations substantially: “Now, we have approximately 300 AI instances monitoring and testing our systems around the clock.” This integration has empowered red teams to work with enhanced efficacy—up to 20 times more efficiently—thus significantly bolstering the security of Check Point’s products.
The Flip Side: Risks from Malicious AI Use
However, the adoption of AI in cybersecurity isn't devoid of risks. Zanger highlighted the alarming trend of malicious actors harnessing similar AI tools, enabling a surge in attacks. The evolution of threat groups has led to smaller, agile units that can execute elaborate phishing campaigns with far less expertise than before. With more players entering the offensive cybersecurity arena, the challenge for defenders inevitably increases: “We must now focus on protecting the very AI systems we’re implementing,” Zanger said.
New Security Challenges with AI Systems
As AI systems gain access to enterprise networks, organizations face unique security challenges. Unlike deterministic systems, which provide predictable outputs, AI inherently involves a degree of unpredictability, making it harder to safeguard. Zanger reflected on the tension within organizations—where security teams aim to limit AI connections to control risks, while proponents advocate for wider AI integration to maximize data utility. “The more connections AI has, the greater the attack vector,” he cautioned.
Combating the Evolving Threat Landscape
The rise of generative AI has simplified threat creation, permitting cybercriminals to ramp up phishing, ransomware, malware, and exploitation efforts. For cybersecurity professionals, Zanger advised a fundamental shift: prevention must take precedence over mere detection and response. As attackers grow increasingly sophisticated, collaboration amongst teams and across companies becomes a pivotal strategy to maintain the upper hand in cybersecurity.
Building Security into AI Development
A major concern that Zanger raised is the frequency of vulnerabilities present in AI platforms. He argued that speed of innovation often outpaces necessary security measures. Companies must prioritize incorporating security from the outset rather than retrofitting it post-development. “Many organizations overlook potential security gaps," Zanger said, highlighting his firm’s role in helping companies navigate these challenges as they leverage AI technologies safely.
Defensive Innovations and Customer Protection
When discussing the state of security technology, Zanger identified three critical areas where AI is reshaping defenses. First, he noted the enhancement of defense operations, allowing teams to address vulnerabilities promptly and efficiently. Second, he underscored the need to safeguard AI applications themselves from becoming new points of vulnerability. Lastly, Zanger advocated for the adoption of advanced models capable of detecting emerging threats and simulating ethical hacker behavior, allowing organizations to preemptively reinforce their defenses.
Addressing the Needs of Smaller Organizations
Small and medium-sized enterprises often seek transparent AI systems that allow for easy auditing of their threat detection and response mechanisms. Zanger stressed that explainability remains key in fulfilling client needs, as organizations desire to understand the reasoning behind automated security decisions. He advocated for systems that block threats automatically while providing insights into those decisions, striking a balance that enhances both security and user understanding.
Víctor Manuel Fernández attended Engage 2026 as a guest of Check Point Software.
