AI is revolutionizing productivity and decision-making across departments. But as with every technological leap, security is struggling to keep pace.
The question on every security leader’s mind isn’t whether AI should be used, but how to ensure it’s safe.
That’s why we created The Practical Playbook for Secure AI Adoption. It provides a practical framework built around five key plays to help security teams manage AI risk without slowing innovation.
Here’s a quick look at the five plays that define safe and secure AI adoption.
Discovery: Gain Visibility Into AI Usage
You can’t protect what you can’t see.
AI isn’t always introduced through formal channels. It’s often embedded in existing applications, accessed through shadow tools, or introduced by employees experimenting with generative platforms. Discovery means continuously identifying every AI system, feature, or integration in use, whether known or not.
Visibility is the foundation of every security strategy, and with AI, it’s non-negotiable.
Registry: Build a Living AI Inventory
Once discovered, every AI tool and integration must be understood in context.
Which vendors are behind them? What data do they access? Are they using large language models, agentic behavior, or third-party APIs?
Building an AI registry enables security teams to manage risk intelligently by maintaining a single, dynamic record of every AI touchpoint across the organization, with ownership, permissions, and vendor posture clearly mapped.
Risk Management: Identify Threats, Misconfigurations, and Anomalies
AI introduces new types of vulnerabilities that traditional tools weren’t built to detect.
Misconfigured agents, unsafe model connections, and over-permissive integrations can lead to unauthorized data exposure or even business disruption. Proactive risk management means detecting and prioritizing these issues early, before they turn into incidents. The right approach turns AI-specific risk into actionable intelligence.
Governance: Build and Enforce Policy
AI is dynamic. Models change, permissions shift, and new features appear overnight.
Static security frameworks can’t keep up. Governance is about enforcing policy continuously: defining what “safe AI” looks like, monitoring for deviations, and automatically remediating risky activity. With governance in place, security teams move from reactive to proactive, controlling AI risk in real time.
Culture: Build AI Awareness Across the Organization
Technology alone can’t solve AI risk. Every employee plays a part in organizational safety. An AI-aware culture means educating teams on safe usage, data sensitivity, and evolving threats. When employees understand both the value and the responsibility of AI, governance becomes a shared effort and not just a security mandate.
AI Security Is Possible and It Starts With Structure
AI is moving fast, but so can your security. With the right framework, one built around discovery, a registry, risk management, governance, and culture, security teams can stay in control while continuing to innovate.
Download The Practical Playbook for Secure AI Adoption to learn exactly how to turn AI chaos into confident, secure adoption.