AI usage tracking is currently in early access. Features, pricing, and packaging are subject to change.
With AI usage tracking, you can see where and how AI services and tools are being used across your environment, based on signals collected by your IT Agents and IT sensors.
Capturing AI-related activity from Windows, Linux, and macOS devices is disabled by default, and must be explicitly enabled per discovery action.
Enable AI tracking per discovery action
You can enable or disable AI usage tracking per discovery action, giving you clearer control over how AI-assisted discovery is monitored in your environment.
To enable or disable AI tracking:
In your Lansweeper Site, go to Discovery > Actions.
Select the discovery action you want to configure.
In the discovery action’s details page, enable or disable AI usage tracking.
You can keep track of discovered AI services and tools by going to Dashboards > All dashboards > AI Asset Management.
Personalize the AI Asset Management dashboard
The AI Asset Management dashboard comes with pre-configured filters that cover the most common AI sources. Since default dashboards are read-only, you'll need to duplicate it before you can make changes.
To personalize the dashboard:
Go to Dashboards > All dashboards > AI Asset Management.
Select Duplicate.
Select a dashboard item, then choose Data > Filters to filter by specific AI sources.
Select Close editor when you're done.
You can also create a dashboard from scratch, though starting from the duplicate gives you all the existing filters as a foundation.
For more information on filtering your dashboard, see Filter dashboards.
Scope of AI usage tracking
Below is the scope of signals typically captured when AI usage tracking is enabled.
Network & communication
Network traffic analysis: detects connections to known AI services (e.g. OpenAI, Anthropic, Google AI, Microsoft Copilot), including 14-day historical tracking.
Browser history scanning: identifies visits to AI platforms across Chrome, Firefox, and Edge.
Event log analysis (Windows): monitors Windows event logs for AI-related network activity indicators.
Software & applications
Installed software detection: scans for locally installed AI applications (e.g. ChatGPT, Cursor, Ollama, LM Studio, Stable Diffusion, TensorFlow, PyTorch).
Browser extension detection: identifies AI-powered browser extensions (e.g. GitHub Copilot, ChatGPT extensions).
IDE/plugin detection: detects AI coding assistants in IDEs (e.g. VS Code, Visual Studio, IntelliJ, and other JetBrains IDEs).
Local AI infrastructure
Local AI server detection: detects running AI model servers (e.g. Ollama, LM Studio, GPT4All, Jan, ComfyUI).
Browser-cached AI model indicators: scans browser storage (e.g. IndexedDB/LocalStorage) for indicators of cached AI models and WebGPU inference components.
Security & compliance indicators
API key/credential indicators: identifies stored AI service credentials (e.g. in environment variables or configuration files).
Cached AI data indicators: detects locally stored AI model data and inference artifacts.