Zscaler report reveals AI adoption outpacing governance, exposing enterprises to heightened cyber risks and vulnerabilities.
Quiver AI Summary
Zscaler's ThreatLabz 2026 AI Security Report highlights the rapid growth of AI adoption in enterprises, revealing that many organizations lack oversight and a basic inventory of AI models, increasing the urgency for AI governance at the board level. The report found that enterprise AI systems are highly vulnerable, with critical flaws identified in all systems tested, and the potential for a breach occurring within minutes. The number of applications utilizing AI surged significantly, with data transfers to AI/ML applications increasing by 93%, marking a dangerous trend as these platforms become prime targets for cybercriminals. As AI becomes integral to business operations, the report emphasizes the need for a Zero Trust security architecture to quickly address these evolving threats and safeguard sensitive data effectively.
Potential Positives
- Highlights Zscaler's leadership in cloud security amid the rapid acceleration of AI adoption, increasing its relevance and importance in the market.
- Identifies critical vulnerabilities in enterprise AI systems, positioning Zscaler as a key provider of solutions to protect against these emerging threats.
- Showcases the significant growth in AI/ML transactions and data transfers, indicating a rising demand for advanced security measures, which Zscaler can fulfill.
- Promotes the Zscaler Zero Trust architecture as a necessary evolution in security strategy, enhancing the company's brand as an innovator in cybersecurity solutions.
Potential Negatives
- Many organizations remain unprepared for AI threats, lacking a basic inventory of AI models, which raises significant governance and security concerns.
- All tested enterprise AI systems were found to have critical vulnerabilities that can be exploited in a very short time, suggesting widespread security inadequacies.
- The dramatic increase in data transfers to AI/ML applications, along with numerous policy violations, highlights a substantial risk of sensitive data exposure, making AI platforms attractive targets for cybercriminals.
FAQ
What are the main findings of the 2026 AI Security Report?
The report highlights rapid AI adoption outpacing enterprise oversight, vulnerabilities in AI systems, and rising data risks for organizations.
How fast could enterprise AI systems be compromised?
Zscaler found that most enterprise AI systems could be compromised in just 16 minutes due to critical vulnerabilities.
What sectors are leading in AI adoption?
Finance & Insurance leads with 23% of all AI/ML traffic, followed by Technology and Education with significant year-over-year growth.
How much data was transferred to AI applications in 2025?
Data transfers to AI/ML applications soared to over 18,000 terabytes, a 93% increase from the previous year.
What security measures does Zscaler recommend for AI governance?
Zscaler recommends implementing an intelligent Zero Trust architecture to mitigate AI-driven threats and enhance security visibility.
Disclaimer: This is an AI-generated summary of a press release distributed by GlobeNewswire. The model used to summarize this release may make mistakes. See the full release here.
$ZS Insider Trading Activity
$ZS insiders have traded $ZS stock on the open market 25 times in the past 6 months. Of those trades, 0 have been purchases and 25 have been sales.
Here’s a breakdown of recent trading of $ZS stock by insiders over the last 6 months:
- ADAM GELLER (Chief Product Officer) has made 0 purchases and 7 sales selling 25,337 shares for an estimated $6,968,864.
- ROBERT SCHLOSSMAN (Chief Legal Officer) has made 0 purchases and 9 sales selling 19,471 shares for an estimated $5,515,151.
- MICHAEL J. RICH (CRO and President of WW Sales) has made 0 purchases and 2 sales selling 15,818 shares for an estimated $4,235,574.
- RAJ JUDGE (EVP, Corp. Strategy & Ventures) has made 0 purchases and 2 sales selling 7,962 shares for an estimated $2,063,436.
- JAGTAR SINGH CHAUDHRY (CEO & Chairman) has made 0 purchases and 2 sales selling 5,708 shares for an estimated $1,460,417.
- KEVIN RUBIN (Chief Financial Officer) sold 3,303 shares for an estimated $762,396
- JAMES A BEER sold 653 shares for an estimated $148,048
- ANDREW WILLIAM FRASER BROWN sold 5,000 shares for an estimated $0
To track insider transactions, check out Quiver Quantitative's insider trading dashboard.
$ZS Revenue
$ZS had revenues of $788.1M in Q1 2026. This is an increase of 25.5% from the same period in the prior year.
You can track ZS financials on Quiver Quantitative's ZS stock page.
$ZS Hedge Fund Activity
We have seen 451 institutional investors add shares of $ZS stock to their portfolio, and 427 decrease their positions in their most recent quarter.
Here are some of the largest recent moves:
- UBS GROUP AG removed 1,236,962 shares (-69.1%) from their portfolio in Q3 2025, for an estimated $370,668,032
- PRICE T ROWE ASSOCIATES INC /MD/ added 1,077,613 shares (+150.2%) to their portfolio in Q3 2025, for an estimated $322,917,511
- CITADEL ADVISORS LLC removed 1,023,480 shares (-85.3%) from their portfolio in Q3 2025, for an estimated $306,696,016
- UBS AM, A DISTINCT BUSINESS UNIT OF UBS ASSET MANAGEMENT AMERICAS LLC added 948,836 shares (+39.2%) to their portfolio in Q3 2025, for an estimated $284,328,195
- AQR CAPITAL MANAGEMENT LLC added 741,756 shares (+61.8%) to their portfolio in Q3 2025, for an estimated $222,274,602
- VANGUARD GROUP INC added 652,771 shares (+6.1%) to their portfolio in Q3 2025, for an estimated $195,609,357
- D. E. SHAW & CO., INC. removed 645,603 shares (-34.3%) from their portfolio in Q3 2025, for an estimated $193,461,394
To track hedge funds' stock portfolios, check out Quiver Quantitative's institutional holdings dashboard.
$ZS Analyst Ratings
Wall Street analysts have issued reports on $ZS in the last several months. We have seen 15 firms issue buy ratings on the stock, and 0 firms issue sell ratings.
Here are some recent analyst ratings:
- Citigroup issued a "Buy" rating on 01/13/2026
- Keybanc issued a "Overweight" rating on 01/12/2026
- RBC Capital issued a "Outperform" rating on 01/05/2026
- BTIG issued a "Buy" rating on 11/26/2025
- Rosenblatt issued a "Buy" rating on 11/26/2025
- Stifel issued a "Buy" rating on 11/26/2025
- Citizens issued a "Market Outperform" rating on 11/26/2025
To track analyst ratings and price targets for $ZS, check out Quiver Quantitative's $ZS forecast page.
$ZS Price Targets
Multiple analysts have issued price targets for $ZS recently. We have seen 27 analysts offer price targets for $ZS in the last 6 months, with a median target of $335.0.
Here are some recent targets:
- Fatima Boolani from Citigroup set a target price of $305.0 on 01/13/2026
- Eric Heath from Keybanc set a target price of $300.0 on 01/12/2026
- Matthew Hedberg from RBC Capital set a target price of $290.0 on 01/05/2026
- Rob Owens from Piper Sandler set a target price of $260.0 on 01/05/2026
- Gregg Moskowitz from Mizuho set a target price of $310.0 on 12/16/2025
- Peter Weed from Bernstein set a target price of $264.0 on 12/01/2025
- Catharine Trebnick from Rosenblatt set a target price of $365.0 on 11/26/2025
Full Release
News Highlights
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AI adoption is accelerating faster than enterprise oversight. Despite 200% AI usage growth in key sectors, many organizations still lack a basic inventory of AI models and embedded AI features, elevating AI governance to a board-level priority.
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Enterprise AI systems are vulnerable at machine speed. Zscaler experts found most enterprise AI systems could be compromised in just 16 minutes, with critical flaws uncovered in 100% of systems analyzed.
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AI capabilities are proliferating rapidly across the enterprise. The number of applications driving AI/ML transactions quadrupled year-over-year to more than 3,400, increasing complexity and reducing centralized visibility.
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AI is becoming a high-volume conduit for sensitive enterprise data. Data transfers to AI/ML applications surged 93%, totaling more than 18,000 terabytes which paints an expanding target on AI platforms for cybercriminals across the globe.
SAN JOSE, Calif., Jan. 27, 2026 (GLOBE NEWSWIRE) -- Zscaler, Inc. (NASDAQ: ZS), the leader in cloud security, today released the findings of the ThreatLabz 2026 AI Security Report, warning that enterprises are unprepared for the next wave of AI‑driven cyber risk, even as AI becomes embedded in business operations. Based on an analysis of nearly one trillion AI/ML transactions across the Zscaler Zero Trust Exchange™ platform between January and December of 2025, the research shows that enterprises are reaching a tipping point where AI has transitioned from a productivity tool to a primary vector for autonomous, machine-speed conflict. The report analyzes AI and ML traffic together because enterprise AI systems rely on machine learning models to operate at scale.
"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."
AI in the Enterprise: Emerging Trends and Security Issues from the 2026 Report
AI Adoption is Outpacing Oversight
AI usage now spans every business function, yet in many sectors, adoption is scaling faster than the C-suite can manage. Finance & Insurance remains the most AI-driven sector by volume, accounting for 23% of all AI/ML traffic, while the Technology and Education sectors recorded explosive year-over-year growth in transactions — 202% and 184%, respectively. Despite this, Zscaler research reveals a critical gap: many organizations still lack a basic inventory of active AI models and embedded features, leaving them unaware of exactly where sensitive data is exposed.
As Agentic AI Looms, 100% of Enterprise AI Systems Found Vulnerable to Breach at Machine Speed
While AI security discussions often focus on hypothetical future threats, Zscaler’s red team testing revealed a more immediate reality: when enterprise AI systems are tested under real adversarial conditions, they break almost immediately. In controlled scans, critical vulnerabilities surfaced in minutes, not hours. The median time to first critical failure was just 16 minutes, with 90% of systems compromised in under 90 minutes. In the most extreme case, the defense was bypassed in a single second.
As more evidence of AI‑driven attacks by cybercriminals and nation‑state espionage groups is uncovered, ThreatLabz warns autonomous and semi‑autonomous “agentic” AI will increasingly automate cyberattacks, with AI agents assuming responsibility for reconnaissance, exploitation, and lateral movement. Defenders must assume that attacks can scale and adapt at machine speed, not human speed.
AI Usage Surges 4x, Fueling New Enterprise Supply Chain Vulnerabilities
ThreatLabz found AI/ML activity increased 91% year-over-year across an ecosystem of more than 3,400 applications. This rapid adoption has left many organizations with no clear map of the AI models interacting with their data or the supply chains behind them. ThreatLabz warns that this AI supply chain is now a primary target, as weaknesses in common model files allow attackers to move laterally into core business systems.
Unmanaged Embedded AI Creates Critical Data Exposure Risks
An enormous volume of activity is happening on "standalone AI" such as ChatGPT, which logged 115 billion transactions in 2025 and Codeium, which logged 42 billion transactions. “Embedded AI,” AI capabilities built directly into everyday enterprise SaaS applications and platforms, have become one of the fastest growing sources of unmanaged risk. Because these features are often active by default and escape detection by legacy security filters, they create a back door for sensitive corporate data to flow into AI models without oversight. Among all platforms analyzed, Atlassian was a leading source of embedded AI activity, reflecting widespread use of AI-powered features within its core platforms, such as Jira and Confluence.
18,000 TB of Data Poured into AI: A New Target for Machine-Speed Attacks
In 2025, enterprise data transfers to AI/ML applications surged to 18,033 terabytes (TB)—a 93% year-over-year increase and roughly equivalent to 3.6 billion digital photos. The massive influx has transformed tools like Grammarly (3,615 TB) and ChatGPT (2,021 TB) into the world’s most concentrated repositories of corporate intelligence.
The scale of this risk is quantified by 410 million Data Loss Prevention (DLP) policy violations tied to ChatGPT alone, including attempts to share Social Security numbers, source code, and medical records. These findings signal that AI governance has transitioned from a policy discussion to an immediate operational necessity. ThreatLabz warns that as these repositories grow, they are becoming high-priority targets for cyber espionage.
Modernize AI security with Zero Trust
Legacy firewalls and VPNs fail in dynamic AI environments, creating visibility gaps and security blind spots. Zscaler replaces this complexity with AI-native security, providing the real-time visibility and guardrails needed to innovate safely.
The Zscaler Zero Trust Exchange helps organizations stay ahead of AI-powered threats by:
- Eliminating Attack Surfaces : Enforce continuous verification and least-privileged access.
- Blocking AI Threats : Inspect all traffic, including encrypted data, to stop threats in real time.
- Protecting Data Everywhere : Automatically discover and classify sensitive data across all environments.
- Neutralizing Lateral Movement : Use AI-powered segmentation to contain attackers.
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Optimizing Responses
: Leverage predictive AI to accelerate security operations and posture management.
Master the new rules of AI security and download the full report
Rapidly accelerating AI adoption demands a new approach to protection. To stay ahead of evolving risks, download the full ThreatLabz 2026 AI Security Report for comprehensive threat analysis and actionable best practices.
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Research Methodology
The report draws on an analysis of 989.3 billion AI/ML transactions generated by ~9K organizations across the Zscaler Zero Trust Exchange™ from January 2025–December 2025, providing a grounded view into how AI is actually being used (and restricted) across global environments.
About Zscaler
Zscaler (NASDAQ: ZS) is a pioneer and global leader in zero trust security. The world’s largest businesses, critical infrastructure organizations, and government agencies rely on Zscaler to secure users, branches, applications, data & devices, and to accelerate digital transformation initiatives. Distributed across 160+ data centers globally, the Zscaler Zero Trust Exchange™ platform combined with advanced AI combats billions of cyber threats and policy violations every day and unlocks productivity gains for modern enterprises by reducing costs and complexity.
Media Contact
Nick Gonzalez, Director of Global Public Relations,
[email protected]
A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/f6075799-2667-4962-9e31-b5a6d3a18410