By ByteBot
Cyera, an Israeli data security startup, raised $400 million in Series F funding on January 8, 2026, reaching a $9 billion valuation—a 50% increase from its $6 billion valuation just six months ago. Led by Blackstone Growth, the round brings Cyera’s total funding to $1.7 billion and values the company higher than many established cybersecurity vendors. The company has tripled revenue in the past year, surpassed $100 million in annual recurring revenue, and now secures data for one-fifth of the Fortune 500, including AT&T, Peloton, Nordstrom, and Chipotle.
Cyera’s explosive growth reveals a critical enterprise reality: AI adoption is gated by data security infrastructure. Organizations cannot confidently deploy AI tools without first securing the sensitive data these systems access.
AI Adoption’s Dirty Secret: Security is the Bottleneck
While everyone celebrates AI productivity gains, most enterprises have no idea where their sensitive data is going. Cyera CEO Yotam Segev puts it bluntly: “Our business had legs before AI. But with AI, it’s got wings.” The numbers back him up. According to Kiteworks’ 2026 AI Data Security Crisis report, 83% of enterprises use AI daily, yet only 13% have strong visibility into how it’s being used.
This creates “shadow AI”—unsanctioned tools accessing sensitive customer data without security oversight. GenAI usage tripled in the past year while data policy violations doubled. The result? Enterprises blocked 18.5% of all AI and ML transactions in 2025, a 577% increase over nine months. Organizations are paralyzed: They need AI for competitiveness, but can’t risk exposing customer data to the 55% of data leaders who cite inadvertent LLM exposure as their biggest threat.
Data security posture management (DSPM) breaks this deadlock by discovering where sensitive data lives, who accesses it, and how to secure it before AI tools touch it. That’s why Cyera’s $9 billion valuation isn’t hype—it’s the market pricing in the cost of AI adoption done right.
Agentic Attackers Operate at Machine Speed
The threat landscape has fundamentally changed. Traditional security assumes human-speed threats: employees clicking phishing links, developers accidentally committing API keys. But agentic AI—both from attackers and from misconfigured internal tools—creates machine-speed risks that require automated, AI-native security responses.
According to Cyera’s CEO in a Fortune interview, organizations now face “agentic attackers” operating at machine speed with consistency no human can match. A misconfigured AI agent with access to sensitive data can expose thousands of customer records in minutes. These systems inherit all the data access of their human operators but act without the judgment that might cause a person to pause before making a risky decision.
Government guidance confirms the stakes: ML models learn their decision logic from data, so attackers who manipulate training data can manipulate AI system logic. Fortune 500 executives understand that major breaches carry career-ending consequences, driving urgent demand for robust security solutions that operate at AI speed.
Investors Pour $400M Into Data Security Despite Cautious Climate
Cyera’s valuation trajectory tells the market story: $3 billion in 2024, $6 billion in June 2025, $9 billion in January 2026. The 50% increase in six months isn’t an outlier—it’s validation that enterprises view data security as recession-proof and essential for the AI era.
The company’s growth metrics back the valuation. Cyera tripled revenue in the past year and signed nearly 10% of the Fortune 500 in the past year alone. The startup has scaled to 1,100 employees across 15 countries, representing 3x growth in 12 months. According to TechCrunch, customers span retail, finance, consulting, healthcare, insurance, manufacturing, and consumer products.
This isn’t just Cyera. According to PR Newswire’s industry analysis, cybersecurity funding in 2025 reached $20.7 billion across 820 deals—a 52% increase from 2024, marking the strongest year since 2021. Cloud security platforms command premium valuations of 21.7x to 35.5x revenue multiples, the highest in cybersecurity. Investors are pouring money into data security not despite a cautious funding climate, but because they see it as foundational infrastructure for the AI era.
DSPM: The Data-First Security Layer Enterprises Needed
Data security posture management differs from traditional security tools in a fundamental way: Instead of protecting systems and networks where data resides, DSPM protects the data itself. According to Palo Alto Networks’ DSPM guide, the technology automatically discovers and classifies sensitive data across multi-cloud environments, assesses vulnerability to threats, and enables rapid remediation.
Cyera’s AI-native platform deploys agentless scanning that maps all cloud datastores in minutes with 95%+ classification precision. It discovers “shadow data”—the 30-50% more sensitive information most organizations find once DSPM scans are complete. The platform tracks who (or what) accesses sensitive data and provides the context security teams need for fast remediation.
Traditional security tools like data loss prevention (DLP) monitor data in motion reactively. DSPM discovers and classifies all data proactively. This is why 63% of organizations have established limitations on what data can be entered into GenAI tools, and 27% have banned GenAI applications altogether—without DSPM visibility, policy enforcement is impossible.
Key Takeaways
- Cyera’s $9 billion valuation signals that DSPM is becoming critical infrastructure for the AI era, not optional tooling
- AI adoption is gated by data security—enterprises need visibility into where sensitive data lives before deploying AI tools that access it
- Agentic threats operate at machine speed, requiring AI-native security responses that traditional tools weren’t designed to handle
- One-fifth of the Fortune 500 already bet on Cyera, with nearly 10% signing up in the past year alone—market validation is real, not hype
- Shadow AI crisis (83% use AI daily, 13% have visibility) is driving urgent demand for DSPM platforms that can secure AI adoption
