Unified Human and AI Agent Risk: One View of Your Full Workforce

Which employees and AI agents are driving the most security risk in your organization? Most teams answer by stitching signals together with vlookups, spreadsheets, and hours of investigation. There is a better way. See a live demo to see unified human and AI agent risk visibility.

Security teams now manage two workforces: people and AI agents. Both can act, both can be compromised, and both introduce risk into the environment. Most platforms track them separately or ignore agents entirely, leaving the board with an incomplete picture of exposure.

Living Security, the leading Human Risk Management platform, surfaces the 10% of the workforce responsible for 73% of an organization's risk. That concentration means security teams do not need to monitor everyone equally; they need to find the few accounts, human or agent, that matter most.

Why Do Human and AI Agent Risks Belong in One View?

Human and AI agent risk share the same failure modes. A human with excessive access can exfiltrate data; an AI agent with excessive access can do the same at machine speed. If the board sees only the human half of the equation, it is making decisions on partial data.

AI agents inherit the identity context, permissions, and data access of the systems they touch. Managing AI agent risk requires the same discipline as human risk: track what it can access, measure what it does, and intervene when its behavior deviates from expectations.

How Does the Platform Score Human and AI Risk Together?

The Living Security Platform applies one risk model to both populations. Dynamic human risk scores update automatically as conditions change, and the same scoring applies to AI agents operating on the organization's identity infrastructure.

• 300+ signals. Behavioral, identity, and threat data drawn from the platform's integrations with the security tools the customer already runs.
• Dynamic scoring. Risk scores update automatically as conditions change, so the view is never stale.
• Plain-language explainability. Livvy explains in clear terms why a score is what it is, no spreadsheets required.
• Concentration detection. The platform identifies the small percentage of accounts responsible for the majority of risk.

The 73% concentration figure comes from the Ponemon Institute and IBM. The Cost of a Data Breach research has long shown that a minority of accounts drive the majority of risk, and the platform's job is to surface that minority before an event occurs.

What Can CISOs Do With Unified Risk Visibility?

Unified visibility changes the board conversation. Instead of reporting separate programs for people and agents, the CISO presents one human risk picture: what is exposed, who and what is driving it, and what the plan is to reduce it.

1. Prioritize the riskiest accounts. Security teams focus monitoring and intervention on the 10% driving the most risk.
2. Predict, not just detect. Risk trajectories show where exposure is heading before an incident happens.
3. Defend to the board. Human and AI risk, presented in plain language, becomes a board-ready narrative.
4. Extend coverage to agents. As the organization deploys more AI agents, the same risk model protects them.

Human and AI agent security risks are predictable and preventable. Prediction requires the right signals, and prevention requires the right response, and both require a single view of risk across the entire workforce.

How Does Explainability Make Risk Actionable?

A risk score without an explanation is a number that invites arguments. Livvy pairs every score with clear reasoning, so a CISO can say exactly why a user or agent is elevated, and each stakeholder can see what to do next.

Explainability also protects the security team. When a score drives an intervention, the employee or agent owner needs to understand the basis, and plain-language reasoning makes the intervention defensible and effective.

Frequently Asked Questions

What is AI agent risk?

AI agent risk is the risk introduced by autonomous AI systems that access identity infrastructure, permissions, and data, through compromised credentials, excessive access, or unintended actions.

Can human and AI agent risk be measured together?

Yes. Living Security applies one risk model to both populations, scoring behavior, identity, and threat signals with dynamic scores and plain-language explainability.

How much of the workforce drives most risk?

Research from Ponemon and IBM shows a minority of accounts drives the majority of risk. Living Security surfaces the 10% of the workforce responsible for 73% of the organization's risk.

Ready to See Your Full Risk Picture?

Security teams using the Living Security Platform reduce risky users by 50% starting from day one, across both human and AI agent populations. See a live demo to view unified human and AI agent risk in one platform, or watch the demo video first.