Check Point Report reveals 51-point AI Security Gap as attackers crack cloud defenses faster

Security teams can't keep up with how fast AI is cracking cloud security

* Check Point's 2026 Cloud Security Report warns AI is overwhelming cloud defenses * While 77% updated cloud strategies, only 26% have architectures capable of enforcing them * Researchers urge a unified, prevention‑first architecture Artificial Intelligence is cracking cloud security at high speeds and security teams just can't keep up. This is one of the conclusions echoed in the "2026 Cloud Security Report: Enter the AI Era," a new in-depth report published by Check Point Software Technologies. In the report, shared with TechRadar Pro earlier this week, Check Point claims that businesses are aware of the risks posed by AI in the wrong hands, but simply don't have the means to address it. Apparently, in response to AI, 77% of organizations have updated their security strategy for cloud this year, but just a quarter (26%) have the architecture to actually enforce it. At the same time, AI is being increasingly weaponized in phishing and malware attacks, at speeds to which "traditional security models" cannot respond. Outpacing the architecture "The impact is already measurable: 78% of organizations reported confirmed or suspected AI-related security incidents over the past year," Check Point said. "AI adoption has outpaced the architecture built to govern it. Agents are acting inside live systems; data is moving through external AI services, and most enterprises still lack the visibility and enforcement to keep pace," commented Stuart Green, Cloud Solution Architect at Check Point. "Visibility, Control, and Security need to be present at all layers in the stack AI workloads will operate in." There are numerous challenges for businesses, especially cloud-native environments, the report further stresses. Besides infrastructure misalignment (52% of AI workloads span hybrid environments, yet 64% confirmed their architecture needs redesign), there are serious perimeter gaps (76% rated datacenter security as critical for AI, but just 35% said it can support current trends), as well as performance challenges (only 25% can fully inspect AI traffic without impacting performance). Finally, there are issues with operational complexity (88% said AI increased security complexity), as well as problems with limited visibility (54% experienced an AI-related security incident, with 24% saying they couldn't confirm due to lack of visibility). To mitigate these risks, businesses need a unified, prevention-first architecture across cloud, datacenter, SaaS, and endpoints, Check Point says. Follow TechRadar on Google News and add us as a preferred source to get our expert news, reviews, and opinion in your feeds.

Check Point Report: Rapid AI Adoption Leaves Critical Gaps in Enterprise Cloud Security

77% of organizations update security for AI, but only 26% can enforce it, exposing a growing 'AI Security Gap' across the enterprise Check Point Software Technologies Ltd. today released its 2026 Cloud Security Report: Enter the AI Era, revealing a growing disconnect between rapid AI adoption and security readiness. The report reveals a critical shift from the cloud "blind spots" of 2025 to a deeper challenge in 2026: organizations are no longer just struggling with visibility, but with governance, control, and real-time enforcement. AI is changing how users behave, how applications communicate, and where threats enter the environment. This year, 77% of organizations have updated their security strategy for cloud in response to AI, yet only 26% report having the architecture to enforce it. This reveals a 51-point gap between intent and capability. Meanwhile, attackers are weaponizing AI tools to accelerate phishing, generate malware, and launch adversarial attacks faster than traditional security models can respond. The impact is already measurable: 78% of organizations reported confirmed or suspected AI-related security incidents over the past year. "The 2026 Cloud Security Report confirms what many security practitioners already sense," said Paul Barbosa, Vice President of Cloud Security and SASE at Check Point Software Technologies. "AI adoption has outpaced the architecture built to govern it. Agents are acting inside live systems; data is moving through external AI services, and most enterprises still lack the visibility and enforcement to keep pace. At Check Point, we believe security has to be built into the architecture from the start. Beginning at the infrastructure layer, through clouds, and especially at runtime. Visibility, Control, and Security need to be present at all layers in the stack AI workloads will operate in. " Key findings for cloud-native environments include: * Infrastructure Misalignment: 52% of AI workloads span hybrid environments, yet 64% say their architecture needs redesign * Perimeter Gaps: 76% rate datacenter security as critical for AI, but only 35% say it can support current needs * Performance Challenges: Only 24% can fully inspect AI traffic without impacting performance; 71% report increased WAF false positives * Operational Complexity: 88% say AI has increased security complexity; 67% report fragmented policies * Limited Visibility: 54% of organizations have experienced an AI-related security incident, while another 24% cannot confirm due to lack of visibility. This means more than three-quarters have either been hit or cannot determine whether they have * Identity Risks: 48% cite non-human identities (AI agents, APIs) as a top concern * Inconsistent access model: Organizations have yet to converge on a single access model. 24% say they have no AI-specific access controls, and only 16% enforce controls consistently across the environment Closing the AI Security Gap To address these challenges, the report emphasizes the need for a unified, prevention-first architecture across cloud, datacenter, SaaS, and endpoints. Check Point's Hybrid Mesh Network Security approach delivers: * Unified Management: 86% of leaders rate unified security management across cloud, datacenter, and edge as critical for AI workloads. A hybrid mesh architecture keeps policies and protections consistent everywhere, no matter where data or workloads run * Prevention-First Security: Real-time blocking of ransomware, zero-day threats, and data leaks using AI-driven insights, validated by a 99.8% security effectiveness score in the 2026 Miercom report * Secure Connectivity and Threat Prevention: Identity-based protection ensures every user, device, and application is verified and protected in real time, with consistent security across all access points and without impacting performance * AI Defense Plane: A unified control plane governing how AI is connected, deployed, and operated, with runtime protection across employee AI use, applications, and agentic systems