SHADOW AI GOVERNANCE

See the AI your organisation is
already using, and govern it

Employees, contractors and applications are adopting AI faster than any approval process can track. Shadow AI Governance gives you the discovery, data controls and enforcement to make that adoption safe, without slowing the business down.

Discover sanctioned and unsanctioned AIProtect sensitive data in promptsEnforce policy at the tool layerLeast-privilege and revoke-on-risk

AI arrived in the enterprise from the bottom up. Staff paste sensitive material into public assistants, teams wire third-party models into workflows, and applications quietly acquire agentic behaviour that can read data and take actions on their own. Most of this never passes through procurement, security review or a policy gate. The result is a fast-growing layer of AI activity that leadership cannot see, cannot measure and cannot control.

Shadow AI Governance is the engine that brings that activity into the open. It discovers where AI is being used across your environment, classifies the data flowing into and out of it, and applies your policy at the point where it matters most, the prompt and the tool call. It works above the tools you already run, so you gain oversight and control without ripping out sanctioned services or forcing a single approved model on everyone.

What it delivers

AI usage discovery

Surface the AI assistants, copilots, models and agents in use across your organisation, including the ones nobody registered. Turn an invisible sprawl into a governed inventory you can reason about.

Data-aware guardrails

Recognise sensitive and regulated content as it moves toward AI systems and apply your handling rules before it leaves your control. Protect the business without blocking legitimate work.

Prompt-layer policy

Apply governance where AI actually happens, at the prompt and response boundary. Allow, redact or block based on the content, the destination and the risk, consistently across sanctioned tools.

Agentic AI control

Govern autonomous agents at the tool and action layer, so an agent can only reach the systems and data it genuinely needs. Keep automation inside guardrails you define.

Least-privilege by default

Grant AI systems and agents the narrowest access that lets them do the job, and nothing more. Reduce the blast radius of any single misstep or compromise.

Revoke on risk

When behaviour crosses a line or context changes, pull access fast rather than waiting for a ticket. Turn a slow manual response into a governed, immediate one.

Illustrative Shadow AI governance map: the core discovers sanctioned, shadow, and agentic AI, enforces least-privilege links, and revokes access on risk in real time.

Discover the AI you didn't know you had

You cannot govern what you cannot see. Before policy, before controls, you need an honest picture of where AI already touches your organisation, which teams rely on it, which applications have quietly gained AI features, and which agents are acting on data with little oversight.

Shadow AI Governance builds that picture and keeps it current. It distinguishes sanctioned services from unsanctioned ones, highlights the usage that carries the most risk, and gives security leaders a governed inventory instead of a guess. From there, adoption becomes a decision you make deliberately rather than a surprise you discover after an incident.

Secure the data, enforce the policy

The core risk of shadow AI is data leaving your control, sensitive records, regulated information, source material and intellectual property flowing into systems you do not govern. Shadow AI Governance addresses this at the boundary where prompts and responses cross, recognising content that should not leave and applying your rules to it in the moment.

Enforcement is consistent and explainable. Rather than a blunt block-everything posture that pushes staff toward workarounds, you set graduated policy, allow, redact, warn or deny, aligned to the sensitivity of the content and the trust in the destination. The outcome is protection people can live with, so governed AI stays the path of least resistance.

Illustrative AI-governance graph: sanctioned tools bound to least-privilege policy vs. discovered shadow AI (dashed) and a rogue agent revoked on risk.
Illustrative view of an enterprise agentic-AI estate across the Discover, Secure and Govern lifecycle. Segment weights are illustrative and categorical only, not real counts.

Govern agentic AI at the prompt and tool layer

Autonomous agents change the stakes. An agent does not just answer, it acts, calling tools, reaching into systems and moving data on its own initiative. Left ungoverned, an over-permissioned agent is a standing risk that scales with every task you hand it.

Shadow AI Governance treats the tool call as the control point. Agents operate under least-privilege access, reaching only the systems and data their role requires, and that access is continuously matched against risk. When context shifts or behaviour crosses a threshold, entitlements can be pulled immediately rather than left in place until someone notices. This keeps the value of automation while containing what it can do when something goes wrong.

Part of one vendor-neutral platform

Shadow AI Governance is one engine of the AEGIS Nexus platform, the layer that sits above the security tools a large enterprise already runs and unifies their signals into one ranked, explainable picture. Its findings do not live in isolation, they feed the same exposure, prediction and response view as the rest of the platform, so AI risk is weighed alongside every other exposure you manage.

Because the platform is vendor-neutral, you are not asked to standardise on one model or abandon the assistants your teams find useful. You gain a governance layer that spans them, giving security leadership oversight and control while the business keeps moving.

Illustrative shadow-AI lifecycle over 12 months: newly discovered unmanaged agents (amber) progressively pulled into secured (blue) then fully governed (teal) states as the governance plane matures. Quantities are illustrative, not real telemetry.

Frequently asked

No. The goal is governed adoption, not prohibition. You decide which services are sanctioned and set graduated policy, so staff can keep using AI productively while sensitive data and high-risk actions stay under control.

Traditional controls were built for files and network traffic, not for the prompt-and-response and tool-call patterns of modern AI and autonomous agents. Shadow AI Governance is designed for that boundary, and it feeds the wider platform picture rather than acting as a standalone gate.

Yes. Agents are governed at the tool and action layer under least-privilege access, with the ability to revoke entitlements when risk rises, so an agent can only ever reach what its role genuinely requires.

No. AEGIS Nexus is vendor-neutral and sits above the tools you already run. You add a governance and oversight layer across your AI usage without rebuilding your environment.

Bring your shadow AI into the light

See how AEGIS Nexus discovers, secures and governs the AI your organisation is already using.

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