AI in the Enterprise: Key Findings from the ThreatLabz 2025 AI Security Report

Artificial intelligence (AI) has rapidly shifted from buzz to business necessity over the past year—something Zscaler has seen firsthand while pioneering AI-powered solutions and tracking enterprise AI/ML activity in the world’s largest security cloud.As enterprises embrace AI to boost productivity, accelerate decision-making, and automate workflows, to name a few benefits, cybercriminals are using the same technology to automate and scale more sophisticated attacks. From hyper-realistic deepfakes to advanced vishing scams, AI-generated threats have quickly raised the stakes for enterprise security.With AI fundamentally changing both how businesses operate and how cybercriminals attack, organizations must maintain a current and comprehensive understanding of the enterprise AI landscape. The just released ThreatLabz 2025 AI Security Report examines the intersection of enterprise AI usage and security, drawing insights from 536.5 billion AI/ML transactions in the Zscaler Zero Trust Exchange. The report reveals how enterprises worldwide and across industries are using and managing AI/ML tools, highlighting both their benefits and the security concerns that come with them. It examines the rising risks associated with AI, from cybercriminals weaponizing AI for more sophisticated attacks to the security implications of recent AI advancements like the open source model DeepSeek, while providing best practices for mitigating these risks.This blog post summarizes several highlights from the report. For the full analysis and security guidance, download the ThreatLabz 2025 AI Security Report now. 5 key findings: AI usage and threat trendsThe ThreatLabz research team analyzed activity from over 800 known AI/ML applications between February–December 2024. The following finding reveal notable trends—and concerns—surrounding AI usage:AI/ML usage surged exponentially: AI/ML transactions in the Zscaler cloud increased 36x (+3,464.6%) year-over-year, highlighting the explosive growth of enterprise AI adoption. The surge was fueled by ChatGPT, Microsoft Copilot, Grammarly, and other generative AI tools, which accounted for the majority of AI-related traffic from known applications. Figure 1: Top AI applications by transaction volume Enterprises blocked a large proportion of AI transactions: 59.9% of AI/ML transactions were blocked, signaling concerns over data security and the uncontrolled use of AI applications. As organizations work to establish AI governance framewo

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