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    Can you control what your AI agents are doing?

    Take the quick readiness check first. You get a score out of 100 and see where your gaps are. Want more detail? The full scorecard is right below.

    Go deeper: see the full scorecard ↓
    Solutions · Scorecard

    Agentic Security Scorecard

    Who is actually in control when an AI agent starts taking action? Use this scorecard to assess whether your agent governance is keeping up with adoption, across inventory, tool visibility, autonomy, sensitive data, runtime enforcement, and audit evidence.

    Take the Interactive Checklist Excel versionPDF guide Book a meeting
    For security, platform, and technology leaders

    Can you control what your AI agents are doing across the business?

    A runtime governance scorecard for mid-market teams deploying agents across internal workflows.

    Executive summary

    AI agents are moving from experiments into business workflows. They are no longer only answering questions; they are accessing systems, calling tools, triggering processes, updating records, and operating across internal, platform-based, SaaS, browser, and endpoint environments. For security, platform, and technology leaders, the governance question is shifting from which AI tools are being used to what agents are allowed to do, under whose control, and whether the organization can prove the right policy was followed. This scorecard helps teams evaluate agentic security readiness across six areas: inventory and control boundary, tool and action visibility, autonomy, sensitive data exposure, runtime policy enforcement, and audit-ready evidence. Use it to pick one high-risk agent workflow, identify the first control gap that matters, and decide what needs direct runtime control or vendor-enforced proof.

    The shift

    The governance question just changed.

    Access control
    Who is allowed to see the data?
    Action control
    What is the agent allowed to do with it, once it has access, on its own?
    That shift is why prompt logs and access reviews alone no longer cover the risk.
    The practical path

    Inventory. Prioritize. Govern. Prove.

    1
    Inventory
    the agents that exist
    2
    Prioritize
    the highest-consequence agents
    3
    Govern
    the actions that need runtime control
    4
    Prove
    what happened, why, and which policy applied
    What we score

    Six areas the scorecard evaluates

    Score your riskiest agent workflow across each one.
    Inventory & control boundary
    Do you know every agent that exists?
    Tool & action visibility
    What can each agent actually do?
    Autonomy
    How much runs without a human checkpoint?
    Sensitive data exposure
    What data can agents touch or expose?
    Runtime policy enforcement
    Can you block or mask an action live?
    Audit-ready evidence
    Can you prove what happened, and why?
    Prioritization

    Which agents should you govern first?

    Start with agents that have authority, autonomy, sensitive data, or downstream impact.
    1
    Action-taking
    Calls APIs, updates systems, issues refunds
    2
    Autonomous / background
    Runs without continuous human review
    3
    No-code / business-built
    Created outside security visibility
    4
    Data-sensitive
    Touches regulated or confidential data
    5
    Tool-heavy / multi-agent
    Passes data across tools and agents
    Before you score

    Know who controls the runtime

    That boundary changes how you should score each agent.
    Enterprise-operated
    You host it — evaluate your own controls
    Platform-based
    Score the actual deployment model
    Vendor-controlled SaaS
    Demand vendor-enforced policy and proof
    Browser / endpoint
    Highest risk — special caution advised

    See where your agents stand.

    Apply the scorecard to one high-risk workflow in your own environment. Takes about ten minutes.
    Take the Interactive Checklist
    or download the Excel version / PDF guide

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