As enterprises adopt AI at scale, risk spreads across multiple layers instead of sitting in one place. The main challenges include:

• Fragmented AI usage by employees: Employees use hundreds of AI tools across browsers, desktops, and IDEs. Security teams often don’t know which tools are in use, who is using them, or what data is being shared.
• Unpredictable AI application behavior: AI applications generate outputs in real time using probabilistic reasoning. This can lead to unpredictable or harmful outputs, data leakage, or prompt injection if not monitored and controlled.
• Autonomous agents with broad access: AI agents act on human authority and can connect to corporate systems and tools. Without proper guardrails, they can create unsafe autonomy loops, abuse privileges, or access sensitive resources.
• Shadow AI and lack of visibility: Many AI tools and agents are adopted without formal approval (“Shadow AI”). This leaves security teams without a single lens to see and manage AI risk across people, apps, and agents.
• Traditional controls don’t fit AI: Legacy security tools were not designed for prompts, model outputs, or agent actions. They struggle to inspect AI interactions or enforce policy inline where AI decisions are made.

Because of these factors, AI adoption often outpaces security and governance, creating a growing gap between how AI is used and how it is controlled.

Check Point’s AI Defense Plane is designed as a single control plane to manage AI risk across the entire enterprise. In practice, this means one unified platform that provides:

• Unified visibility: A single view into AI usage across employees, applications, and agents. It helps you discover:
  • Which AI tools are in use
  • Who is using them
  • How they are being used and with what level of risk
• Inline protection where AI operates: The platform inspects prompts, outputs, and agent actions in real time to prevent:
  • Prompt injection
  • Data exfiltration and sensitive data leakage
  • Harmful or non-compliant outputs
  • Risky connections to corporate resources
• Centralized governance: Security and compliance policies are enforced consistently across:
  • Workforce AI usage (browsers, desktops, clientless access)
  • AI applications in production
  • AI agents acting on corporate systems
• Low-latency, production-ready controls: The platform is built for production environments with sub-50ms latency, so security checks do not materially slow down AI interactions.
• Enterprise-grade coverage: The AI Defense Plane is:
  • Model-agnostic – works with any LLM provider
  • Multimodal and multilingual – supports text and voice, with global coverage
  • Proven in regulated industries that require strong governance

By consolidating visibility, protection, and governance into one platform, organizations can reimagine AI security as an integrated “defense plane” instead of a patchwork of point solutions.

Check Point’s AI security approach covers the full AI lifecycle with three key capability areas:

1. Workforce AI Security – govern employee AI usage

This focuses on employee tools and Shadow AI without blocking productivity:

• Discover AI tools across browsers and devices
• Break down AI activity by application and user
• Apply granular policies by application and data type
• Enforce security and policy per interaction, not just at the network level
• Continuously govern evolving AI usage over time

2. AI Agent Security – protect AI applications and agents at runtime

This secures AI where decisions are made, in real time:

• Inspect prompts, outputs, and agent actions inline
• Prevent prompt injection and unsafe autonomy loops
• Identify unapproved and Shadow AI usage
• Understand user intent to better assess risk
• Block risky connections from agents to corporate resources

3. AI Red Teaming – expose AI failure modes before attackers do

This helps you test and harden AI systems before launch:

• Simulate real-world AI attacks and misuse
• Identify vulnerabilities in reasoning, workflows, and tool usage
• Detect and prevent prompt injection and data leakage paths
• Prioritize risks based on business impact
• Receive actionable remediation guidance to fix issues

Together, these capabilities allow enterprises to secure AI usage before launch, in production, and over time, using one AI Defense Plane as the source of truth for AI risk.