Protecting Cloud Data in the GenAI Era

As technology evolves, the traditional attack surface has exploded into what we now call a data surface. Data is everywhere. It is flowing across cloud environments, hybrid work setups and now being leveraged by Generative AI.

Generative AI (GenAI) is now part of everyday work. Employees across industries are utilizing GenAI tools for drafting proposals and summarizing meetings to building agentic workflows that automatically act on data.  

As such, security teams are grappling with a new paradox: GenAI is both a breakthrough in productivity and also a whole new surface for data risk.  

The path forward isn’t more point tools or heavier rules. It’s AI‑native security controls designed for a world where data, users, apps, and AI systems are constantly interacting with each other.

Forcepoint’s AI-Native Controls

Forcepoint is leading the future of data protection with AI-native controls purpose-built for the GenAI era. At the heart of Forcepoint Data Security Posture Managment's (DSPM) innovation is AI Mesh, a layered decision engine that fuses specialized models, like LLM-lite classifiers, entity detection, sentiment analysis and Bayesian reasoning, all to deliver explainable, context-rich security decisions. AI Mesh technology powers Forcepoint DSPM's data classification engine.  

Complementing this is the award-winning Forcepoint Data Loss Prevention (DLP), which moves beyond static rules to apply dynamic, context-aware enforcement that adapts to how users interact with data and GenAI tools. This shift from reactive controls to intelligent, adaptive defense is what makes Forcepoint uniquely positioned to secure GenAI-ready enterprises.

Forcepoint CASB: Securing Cloud Data in the GenAI Era

As GenAI becomes embedded across SaaS platforms and enterprise workflows, the challenge isn’t just about securing users. It’s about securing how AI interacts with data. Forcepoint Cloud Access Security Broker (CASB) is purpose-built to meet this challenge, offering dual-mode protection through both API-based scanning and inline enforcement.  

This ensures that sensitive data is protected whether it’s being accessed, shared, or transformed by users or by AI.  Here’s how it addresses the most critical GenAI risks:

• Visibility into enterprise AI apps - Identify sensitive content created within the enterprise-approved AI apps, preventing unauthorized access, data leaks and compliance violations.
• GenAI Access Control - Enforce who can access and use the AI apps, and under what conditions. Restrict access from unmanaged or non-compliant devices to prevent uncontrolled data exposure.
• Automatic Remediation for Sensitive Conversations - When sensitive data appears in AI prompts or responses, CASB can delete or copy non-compliant conversations using DLP policies to prevent data exposure.
• Prevent Prompt Injection & Output Tampering - Inline inspection stops malicious prompts designed to exfiltrate data or manipulate AI outputs. CASB ensures AI responses don’t leak sensitive information back to the user.
• Regulatory & Compliance Assurance - Generate audit-ready reports on GenAI usage, including prompts and responses, to demonstrate adherence to industry regulations and internal policies.
• Secure Sanctioned AI usage on Unmanaged Devices - Apply adaptive controls when users access enterprise AI from personal or unmanaged endpoints, enforcing restrictions on risky users and devices.

Preparing for Agentic AI and Autonomous Workflows

The next challenge is not just how employees use AI, but how AI itself will act on data. Agentic AI systems will bring new levels of efficiency but will also create new data risks. These autonomous agents can make decisions, initiate actions and carry out workflows on behalf of users or organizations. Instead of waiting for a query, an agentic AI might proactively retrieve data, write code, trigger transactions or interact with third-party systems to accomplish a task.  

In this phase, security must evolve from governing human-initiated activity to controlling machine-driven actions. Forcepoint CASB is already positioned for this future. Its combination of inline and API-based enforcement, along with integration into Forcepoint’s broader data security platform provides a foundation for securing agentic AI workflows. By embedding policy controls directly into the flow of data, organizations can prepare today for the autonomous AI era that is rapidly approaching.

Data protection in the GenAI era requires more than bolt-on tools. Organizations need AI-aware controls that combine inline enforcement, API-based visibility, and adaptive policy frameworks. Forcepoint CASB delivers exactly that: securing SaaS and GenAI usage without slowing productivity, while also extending protection to unmanaged devices and shadow AI applications.

As GenAI matures and agentic AI becomes reality, the organizations best prepared will be those that unify data-first security with real-time, inline enforcement. Forcepoint CASB is purpose-built to help security teams meet that challenge, protecting sensitive data everywhere it moves while enabling innovation with confidence.