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AI adoption widens security gaps: Zscaler Report
The report said many organizations lack inventories of AI models and embedded AI features, pushing governance concerns to the board level.
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Anushka Pathak - Mon, 02, Feb 2026
- 11:47 EST
- 14
Representative Image / Courtesy: AI-generated
Enterprises are facing a widening security gap as artificial intelligence adoption gathers speed, a new report stated.
According to the ThreatLabz 2026 AI Security Report released by Zscaler, AI adoption rose 91 percent year over year; it exposed enterprise vulnerabilities at machine speed, increasing overall security risks.
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The report analyzed 989.3 billion AI and machine learning transactions from about 9,000 organizations across the Zscaler Zero Trust Exchange platform between Jan. 2025 and Dec. 2025.
It warns that accelerated AI integration has shifted AI from a productivity aid to a primary vector for autonomous cyber threats.
“AI is no longer just a productivity tool but a primary vector for autonomous, machine-speed attacks by both crimeware and nation-state,” said Deepen Desai, EVP Cybersecurity at Zscaler.
“In the age of Agentic AI, an intrusion can move from discovery to lateral movement to data theft in minutes, rendering traditional defenses obsolete. To win this race, organizations must fight AI with AI by deploying an intelligent Zero Trust architecture that shuts down the potential paths for the attackers of all kinds,” he added.
The finance and insurance sector accounted for 23 percent of total AI and ML traffic, while technology and education recorded year-over-year growth of 202 percent and 184 percent, respectively.
The report said many organizations lack inventories of AI models and embedded AI features, pushing governance concerns to the board level.
Red team testing by Zscaler found critical vulnerabilities in all analyzed enterprise AI systems, with a median compromise time of 16 minutes. Ninety percent of systems were breached in under 90 minutes, and one was compromised in a single second.
The findings point to the rise of “agentic” AI capable of automating reconnaissance, exploitation, and lateral movement.
Data transfers to AI and ML applications reached 18,033 terabytes in 2025, up 93 percent from the previous year. Applications such as ChatGPT and Grammarly emerged as major repositories of corporate data, with 410 million data loss prevention violations linked to ChatGPT alone, involving information such as Social Security numbers, source code, and medical records.
Standalone AI platforms dominated transaction volumes, led by ChatGPT with 115 billion transactions and Codeium with 42 billion. Embedded AI features within SaaS platforms such as Atlassian tools Jira and Confluence were cited as creating unmanaged risks by bypassing legacy security controls.
The report recommends adopting Zero Trust security models to reduce attack surfaces, block threats in real time, protect data, limit lateral movement, and improve response through AI-native capabilities.
Discover more at New India Abroad.
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