Global cybersecurity leader Forcepoint launched AI Data Security, a cloud-native security platform engineered to unify data oversight with proactive threat protection across autonomous AI agents, shadow AI applications, and sanctioned corporate AI ecosystems. The new platform establishes an enterprise framework for AI Data Security, enabling organizations to deploy sensitive data within AI applications without compromising speed, operational performance, or compliance.
The release comes as modern corporate workflows shift toward agentic AI models. Today, both human employees and autonomous software agents continuously feed sensitive intellectual property, customer data, and operational files into AI applications, LLMs, and enterprise copilots. Historically, managing data loss prevention (DLP) and governing artificial intelligence were treated as separate IT disciplines. However, in an agentic environment, protecting corporate information requires direct governance of the AI systems that process it. Industry research underscores this operational gap, with 79% of enterprise organizations reporting difficulties in securing the data assets powering their AI initiatives.
“For 20 years, security meant keeping sensitive data away from risk. AI flips that,” said Ryan Windham, CEO of Forcepoint. “The data you most want to protect is the data that makes AI worth using. I’d urge every agentic enterprise to stop locking AI down and start securing it where the risk actually lives, in the data itself. Other approaches will only tell you what’s at risk. Forcepoint’s protection travels with your data into AI and proves it can be trusted there.”
Unifying Classification and Protection Across Multi-Agent Ecosystems
The Forcepoint AI Data Security Platform resolves visibility and enforcement gaps by anchoring security policies directly to the data layer. Instead of using only passive monitoring techniques, it deploys context-based policy enforcement in real-time to both structured and unstructured data, regardless of whether the data source is hosted on-premises or in multi-cloud environments like Google Workspace, Databricks, and Snowflake.
The security functions of the platform tackle the full governance of AI data lifecycle across five pillars: discovery classification control, guardrails, and compliance:
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Comprehensive AI Visibility & Governance: It scans automatically all active AI agents throughout the company, assigning each autonomous action to a direct human attribution, a computer agent, or a user-agent pair.
An AI Agent Gateway and a Least- Privilege Access: method that works as an interface between autonomous agents and enterprise SaaS systems. The least privilege and field-level DLP enforcement by the gateway means agents are forbidden from making sensitive write or delete changes directly through agents, while they need human-in-the-loop approval for such actions, and also agents must not keep directly application credentials with the system.
Prioritize Inline Control of Shadow AI: Beyond detecting unverified shadow AI, it also classifies shadow AI usage, while giving policy controls in line with admin to let, limit, or prevent the unapproved third-party AI tools as well as the personal tenant accounts.
Confidential Document and Prompt Protection: The feature that supports Microsoft Information Protection (MIP) tagging not only helps in isolating confidential documents from AI summaries but also ensures that data protected by regulations such as (PII/PC/PIs) should not leak via prompts or API integrations at all.
Natural Language Governance via ARIA: Features an embedded AI assistant, ARIA, that allows IT and security teams to build, audit, and enforce complex AI data protection policies using plain-English instructions.
“The hardest problem in enterprise security right now is ensuring that sensitive data stays protected once employees put it into AI, whether sanctioned or not,” said Roland Cloutier, Strategic Security Advisor and former Chief Security Officer at TikTok, ADP and EMC, among others. “Forcepoint’s approach is notably different, because it moves past visibility to enforcement that follows the data itself, which is what defensibility to auditors and boards actually requires. Knowing where your data goes is table stakes now.”
Verifiable Auditing for Boards and Regulatory Compliance
By extending its proven security architecture across web, email, network, and endpoints into AI interaction layers, Forcepoint equips enterprises and government agencies with a defensible security posture. The platform automatically generates centralized, board-ready executive reports through Forcepoint Insights. These immutable audit trails track risk trends, document blocked threats, and detail user-agent interactions, providing the empirical evidence required by corporate boards, external auditors, and regulatory bodies.
The Forcepoint AI Data Security Platform is available immediately for global deployment across cloud and on-premises environments. Chief Information Security Officers (CISOs), risk officers, and IT architecture teams can evaluate platform capabilities, access technical documentation, and request an operational demonstration by visiting Forcepoint’s official platform hub.