Adlumin now surfaces AI tool usage by processes, endpoints, and users; powered by existing technology already protecting your environment.

AI tools are spreading across organisations faster than security and compliance teams can track them. Employees reach for ChatGPT, Copilot, Gemini, Claude and dozens of other AI services to accelerate their work, often without approval, governance, or any visibility from IT. This is Shadow AI: unsanctioned, unmonitored, and increasingly risky.

Adlumin’s new Shadow AI Visibility capability gives security teams a continuously updated inventory of which AI tools are being used, on which machines, by which users, and through which processes; so you can enforce acceptable-use policies before sensitive data leaves the organisation and produce the user-level, machine-level compliance evidence auditors and regulators demand.

Built on Technology already in your Environment

Every AI tool interaction begins with a DNS query. When an employee opens ChatGPT, a background process calls the Anthropic API, or a browser extension reaches out to an AI backend. Those requests leave a DNS trail. Adlumin’s existing DNS Disruption Detection infrastructure already captures and baselines this activity at the environment level.

Shadow AI Visibility extends that foundation by correlating DNS query patterns against a continuously updated catalogue of known AI tool domains and endpoints.

What It Detects

Shadow AI Visibility identifies AI tool usage across 4 key dimensions, giving security and compliance teams the attribution they need to take action:

• Which Tools are being used
• Which Machines are accessing them
• Which Users are generating activity
• Which Processes are initiating interactions

How It Works

Adlumin’s detection engines continuously models the DNS behaviour of each customer environment, establishing what is normal. Shadow AI Visibility applies a second analytical layer on top of this baseline: a domain classification engine that maps resolved hostnames and query patterns to known AI service providers.

When a match is found, Adlumin correlates the DNS event with endpoint telemetry to attribute the activity to a specific process, machine, and user.

Why Shadow AI Is a Security and Compliance Risk

The risks of unmanaged AI tool usage extend well beyond productivity concerns. Employees frequently submit proprietary data, customer records, source code, and internal documents to AI services hosted outside the organisation’s control. Without visibility, security teams cannot:

• Enforce data handling policies
• Meet regulatory obligations around data residency
• Detect exfiltration via AI tool submissions
• Respond to incidents involving third-party AI processing
• Maintain an accurate inventory of data flows

Shadow AI Visibility closes this gap with a detect-first approach surfacing the problem before it becomes a compliance finding.

Operational Value

Shadow AI Visibility delivers immediate, actionable insights for security operations, compliance, and governance teams:

• Instant inventory
  • A live map of every AI tool active in your environment, updated continuously.
• Policy enforcement
  • Identify and act on policy violations before data leaves the organisation.
• Compliance evidence
  • Linking AI tool usage to specific users, machines, and timeframes.

Conclusion

Shadow AI is one of the fastest-growing blind spots in enterprise security. As AI tool adoption accelerates the attack surface expands in ways that traditional controls simply cannot see.

By extending Adlumin’s proven DNS Disruption Detection technology into the AI visibility domain, Shadow AI Visibility provides organisations with the coverage they need: continuous, identity-attributed, process-level insight into AI tool usage across the entire environment, delivered through infrastructure already in place.