AI Automation Overview
Overview
As organizations deploy AI across multiple departments and cloud environments, there's limited visibility into which AI systems are operating, what data they use, and how they make decisions. This blind spot increases regulatory risk and undermines ethical governance efforts.
AI Automations automatically scan cloud environments, APIs, pipelines, and applications to detect active AI models, agents, or datasets respective to the connector. It captures metadata including model type, owners, input/output behavior, and associated datasets. This provides a real-time, searchable inventory that serves as the foundation for governance policies, risk assessments, and audit trails.
AI Automations are deployed using the lightweight worker node, which grants a simplified experience and minimizes the need for specialized personnel. It can retrieve all prerequisites and images from a cloud API, ensuring smooth, firewall-independent deployment. For more information, see Lightweight Worker Node Deployment for AI Automations.
Supported Systems
OneTrust currently supports the following connector types to conduct AI automations:
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Amazon Bedrock & AgentCore
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Amazon SageMaker
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Azure Foundry
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Databricks
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Google Cloud Vertex
For more information on setting up automations, see AI Automation Feature Guide.
Prerequisites
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A lightweight worker node installed through one of the supported cloud service providers: AWS, Azure, or GCP.
To manage automations
Set up automations so they appear on the list screen. Refer to the feature guides above to get started.