AI Security is a Data Problem. Forcepoint Starts There.

AI data security is the set of controls that keeps sensitive data safe as it moves into and through AI tools, including prompts, file uploads and the responses that come back. Forcepoint's approach starts with the data rather than the model. Data is classified before it reaches an AI tool, then policy is enforced at the moment of interaction. Forcepoint AI Data Security applies that standard across sanctioned AI, shadow AI and AI agents, so the same policy holds no matter which one an employee is using.

Without AI data security, sensitive data leaves the organization one prompt at a time, and nobody notices until it is gone. A customer record pasted into a chatbot or a contract uploaded for a summary is a data transfer that moves outside normal network and endpoint controls. Sanctioned AI apps and shadow AI both create this exposure, and tools built only to watch sanctioned software never see the unapproved activity. Forcepoint AI Data Security monitors AI use, stops unapproved access and prevents data loss.

Traditional DLP protects known file types moving across static channels, such as email, USB drives and file shares. Forcepoint AI Security runs on the same classification engine as Forcepoint DLP and extends it to inspect prompts, responses and file uploads the moment someone interacts with an AI tool, whether inline at the endpoint or through API connectors to sanctioned platforms. Forcepoint DLP and Forcepoint AI Security are both capabilities of the Forcepoint AI Data Security platform, so AI coverage extends the policies you already have instead of replacing them.

Forcepoint AI Security's AI Detection and Response capability connects to sanctioned AI platforms, including ChatGPT Enterprise, Microsoft 365 Copilot and AWS Bedrock, through native API connectors. It inspects prompts, responses and file uploads against your existing data classification policy and, when a violation is found, triggers remediation automatically: audit, quarantine, copy or delete the conversation, or revoke access to an overshared file.

Forcepoint AI Security's Shadow AI Discovery and Control capability discovers unsanctioned AI apps, websites and AI agents running on endpoints, including shadow AI that stays invisible until something actively looks for it. It also detects personal account use versus corporate account use, which matters because it is how security teams tell whether someone typing into an AI chatbot is on a sanctioned business account or a personal login with no policy protection at all.

Forcepoint classifies sensitive files in OneDrive and SharePoint before Copilot can reach them, then uses API-based remediation to revoke access or restrict sharing on overshared content automatically. For agents that run in the cloud and call business applications directly, such as Salesforce, Microsoft 365 and Jira, the AI Agent Gateway, a capability of Forcepoint AI Security, sits between the agent and the application. No agent holds direct application credentials, every response is inspected at field level, and write or delete actions can be held for human approval. One policy governs what an agent can reach, whether it is reading an overshared file or calling an application API directly.

Enterprises should look for software that classifies and controls data at the point of AI interaction, not software that only alerts to data-related risks. That is the difference between catching risk in real time and finding out only after data has moved. Coverage should also extend to autonomous agents, shadow AI and sanctioned AI apps, not just chat tools, since AI risk is not confined to the tools IT approved. Forcepoint AI Data Security is built around that standard.

Forcepoint AI Data Security monitors AI use, stops unapproved access and prevents data loss, which is the underlying enforcement activity an auditor needs evidence of. Audit-ready reports layer automated tracking on top of that activity to produce a document that regulators and auditors can use to understand the mechanisms in place to mitigate AI data risk, rather than a live feed of enforcement events.

The underlying mechanism does not change across industries, but the sensitive data types do. Forcepoint AI Data Security draws on Forcepoint's classification engine and nearly 2,000 out-of-the-box templates, policies and classifiers to discover and enforce policy against PII, PHI, clinical records and other mission-critical data. Whether the requirement is compliance-bound financial records or public-sector information, a wide range of industries can take advantage of Forcepoint AI Data Security. That consistency across industries is what lets Forcepoint AI Data Security deploy without being rebuilt around each company's unique requirements.

Forcepoint AI Data Security is built to produce the evidence auditors ask for, going beyond simply putting policies in place. Every AI interaction — prompts, file uploads, agent actions and policy decisions — is logged with attribution to the user, device and application, exportable on demand in formats auditors recognize. Because enforcement happens at the same moment as detection, the record reflects exactly what the platform did, not just what it flagged. Organizations subject to SOC 2, ISO 27001, GDPR and similar frameworks use Forcepoint to demonstrate that AI governance is operational and continuous, not a one-time assessment.

Forcepoint AI Data Security provides a unified risk dashboard that gives security teams a prioritized view of AI risk across sanctioned tools, shadow AI and autonomous agents, without treating every finding as equally urgent. The X-Labs AI application database ranks every tool in use by type and risk profile, so teams can focus remediation on the highest-risk surfaces first. Posture reporting tracks policy violations, data-access patterns and risk trends over time, giving security and compliance teams the ongoing visibility they need to demonstrate an improving posture rather than a point-in-time snapshot.