AI Governance - August 7, 2026 - 202608.1.0 (Summer Release)

General Availability

AI Policy Manager & Seeded AI Policies

Automatically detect AI policy violations across platforms to provide AI governance teams with actionable steps to ensure governance and compliance throughout the lifecycle of an AI entity, including AI systems, agents, and models. This policy orchestration experience allows users to create custom policies for unique scenarios and support guardrail enforcement and detection.

To complement the AI Policy Manager, seeded AI policies are also available to help organizations get started quickly with AI governance and compliance monitoring. These out-of-the-box policies help identify common governance gaps and provide remediation guidance, while also serving as templates for customers to build and customize their own AI policies in OneTrust.

For more information, see AI Policies Feature Guide.

Guardrail Detection & Enforcement

Automatically detect policy violations related to guardrail coverage and enforce missing guardrails on AI agents and models across supported AI development platforms. This enhancement helps enforce guardrails more consistently across the following platforms:

  • Amazon Bedrock

  • Azure Foundry

  • Databricks

For more information, see AI Policy Enforcement Guide.

AI Guard SDK and Classification for Worker Node Deployments

Protect critical AI systems by introducing the AI Guard SDK by OneTrust for worker node deployments, a comprehensive classification and inspection layer that helps ensure AI interactions are safe, secure, and compliant during development and runtime. This enhancement helps identify PII risks early through advanced data classification, enabling teams to test AI agents and quantify PII risk before moving to production. Integrate easily using the SDK-based approach designed for Python runtime environments, ideal for build-phase validation rather than high-volume, externally facing AI use cases.

For more information, see OneTrust AI Guard SDK Guide.

AI Guard SDK and Classification for On-Premises Deployments

Protect critical AI systems with the AI Guard SDK for standalone on-premises deployments. This enhancement enables AI classification and inspection within your environment while maintaining local control of AI Guard.

For more information, see OneTrust AI Guard SDK Guide.

AI Policy Email Digest

Send daily and weekly email digests of policy activity, including policy-violation trends, severity breakdowns, and the most critical policy findings, to help policy owners and governance teams stay informed without manually monitoring each policy. Configure recipients and severity thresholds for each digest to help ensure the right stakeholders are informed about critical issues and can take action when needed.

For more information, see AI Policy Email Notifications.

AI Policy - Lifecycle Management

Manage AI policy lifecycles more effectively by duplicating policies to create organization-specific variants and suppressing violations for specific AI models and agents. This enhancement helps manage policies and handle exceptions more efficiently.

For more information, see the following:

addendum: The release stage for this release note was corrected from Public Preview to General Availability on August 14, 2026.
AI Governance Program Efficiency Insights

Improve visibility into AI governance reviews with Program Efficiency Insights, which shows how long reviews take, where records are getting stuck, and which approval groups are involved. Use these insights to identify bottlenecks, adjust routing or capacity, and keep reviews moving with more predictability.

For more information, see AI Governance Program Efficiency Insights.

Observability for Amazon Bedrock

Extend continuous AI monitoring for Amazon Bedrock to gain visibility into AI agent and model activity. This enhancement supports ongoing governance by capturing agent and model metadata, usage information, evaluation metrics, and more directly from Amazon Bedrock-powered AI systems as they operate in production.

Additionally, you can detect and measure PII leakage for Amazon Bedrock using the AI Log Analyzer by scanning AI logs stored in Amazon S3, identifying sensitive prompts and responses, and surfacing PII counts in OneTrust for the associated AI assets to reduce risk from non-deterministic AI behavior.

For more information, see the following:

Observability for Databricks

Extend AI Governance for Databricks models and agents with runtime observability, including evaluation metrics for agents and operational visibility. This enhancement improves understanding of agent behavior before production, monitoring of Databricks model and agent activity through usage and token metrics, and support of automated governance at scale.

For more information, see the following:

Observability for Google Vertex (now Gemini Enterprise Agent Platform)

Add runtime observability for Google Vertex (now Gemini Enterprise Agent Platform) to bring native evaluation metrics and operational visibility for agents into AI Governance. This enhancement helps teams monitor agent behavior through agent-level request and latency metrics, enabling automated governance at scale.

For more information, see the following:

Observability for Microsoft Foundry

Enable continuous monitoring for AI agents and models built on Microsoft Foundry by surfacing Evaluation Metrics for Agents and Models, shifting from AI systems. This enhancement helps shift from one-time assessments to ongoing evaluation using live telemetry from Foundry-based AI systems.

For more information, see the following:

Formula/Score Type Attributes Support in Workflows and Automation Rules

Use formula and score attributes in AI Governance workflows and automation rules. This enhancement helps you use configured scoring attributes to drive workflow and automation behavior across AI Governance objects.

For more information, see Risk Aggregation Scoring in AI Inventories.

User Type Condition Support in Automation Rules

Configure automation rules using User type attributes for user selection, in addition to system users. This enhancement helps governance teams automate reassessments and follow-up assessments more flexibly by routing each assessment to the appropriate record-level owner.

For more information, see Configuring Automation Rules for AI Governance.

Cloudflare Integration for AI Systems

Integrate with the seeded Cloudflare: App Discovery workflow to automatically discover, inventory, and govern AI systems in use by ingesting Cloudflare “AI activity” signals, including unsanctioned Shadow AI, into OneTrust AI Governance. This helps teams identify sanctioned and unsanctioned AI use earlier, maintain a more complete AI inventory, and reduce governance risk across the organization.

For more information, see Cloudflare Integration for AI Governance Systems.

AWS Bedrock AgentCore Detection Connector

Automatically scan AWS Bedrock AgentCore environments to discover agent runtimes and related governance, evaluation, and observability data, then map them into AI Governance as AI agents. This creates a searchable inventory of AgentCore systems in OneTrust, helping teams govern, approve, and monitor them over time.

For more information, see AI Automation Feature Guide.

Custom Notifications for Assessment Templates

Send customized, trigger-based automated email messages from a new global Notifications tab on the Assessment templates screen. This enhancement speeds up assessment completion, reduces support requirements, and provides users with more relevant information in the assessment.

For more information, see Configuring Custom Email Notifications on Assessment Templates. This feature is related to the following ideas: OT-I-949, OT-I-1270, OT-I-3522, OT-I-7945, and OT-I-16348.

Configuring Approver-only Assessment Sections

Configure approver-only sections on assessments automatically using template rules or inventory-based values. These enhancements mean users can launch assessments with approver-only sections directly from the self-service portal.

For more information, see Configuring Approver-only Assessment Sections. This feature is related to the following ideas: AA-I-293 and AA-I-302.

Leveraging AI Auto-responses for Assessments

Opt out of automatically scanning your three most recent assessments, plus add more files, more file types, and bigger files to your uploads. These enhancements improve the performance and accuracy of the AI Doc Scanner.

For more information, see Leveraging AI Auto-responses for Assessments.

User Groups as Respondents in Launch Assessment Actions

Assign user groups as respondents in the Launch Assessment action for supported object workflows, and send assignment notifications to the selected group. This makes it easier to assign assessments to groups of users without adding each user individually.

Impacted object workflows:

  • AI agents

  • AI systems

  • Models

addendum: This release note was updated on August 14, 2026 to remove Project workflow support for User Groups as Respondents in Launch Assessment actions.
addendum: The release note pertaining to Preserve/Delete Hidden Data to AI Governance Objects was removed on August 14, 2026.

Fixed

  • Resolved an issue that caused renaming a URL-type document in a project’s Documents tab to update a different document.

  • Resolved an issue that prevented users from adjusting column widths in the AI systems screen.

  • Resolved an issue that prevented users with Data Mapping access from creating or editing Project summary reports when they did not have AI Governance access.

  • addendum: The release note pertaining to AI system records displaying the source object ID instead of the source object name in task reports was removed on August 14, 2026.

New Public Preview Features

Attribute-Based Access Control (ABAC) Phase 1

Introducing Attribute-Based Access Control (ABAC), a new access-control model that brings record-level access management to the OneTrust Platform as part of ABAC Phase 1: Foundations. ABAC complements the platform's existing Role-Based Access Control (RBAC) model by using assignments through sharing, attributes, or workflows to determine which records users can access and what permissions they have on those records. This feature introduces assignment-based permissions, sharing and access management, and record-level auditing, helping organizations implement least-privileged access, improve governance, and simplify collaboration across teams and workflows.

For more information, see Attribute-Based Access Control (ABAC) Phase 1: Foundations in the Settings & Administration release notes. This feature is related to the following ideas: PLTI-I-638 and GCIA-I-918.

Note:

ABAC is being introduced through a phased rollout that begins with ABAC Phase 1: Foundations, available in Public Preview as part of OneTrust 202608.1.0 for supported objects across AI Governance.

For more information, see Attribute-Based Access Control (ABAC) User Guide and Managing Attribute-Based Access Control (ABAC) for AI Governance.

Microsoft Copilot Studio Agent Detection

Automatically scan Microsoft Copilot Studio environments to detect agents and capture key metadata such as ownership, environment, model bindings, connected channels, and authentication settings. This creates a searchable inventory of Copilot Studio agents and their configurations in OneTrust, helping teams support governance, risk assessment, and audit readiness.

For more information, see AI Automation Feature Guide.

GenAI Component Intelligence for AI Models

Create and enrich AI model records by using the Model library with information from commonly used third-party AI models. This gives teams a continuously updated technical context to understand model behavior, assess suitability and risk, and start governance workflows without manual research.

For more information, see Creating and Managing AI Models.

AI Policy - Automation Actions

Configure automated actions for AI policies to automatically flag risks and send email notifications when AI models and agents violate policies. This enhancement helps governance teams reduce manual monitoring, streamline governance workflows, and respond more quickly to issues by triggering actions based on policy compliance outcomes.

For more information, see AI Policy Enforcement Guide.

Permissions

Things to Know

Added support for bulk importing risks through theBulk importflow for AI systems, AI agents, projects, models, and datasets.

Moved the Context Menu icon from the left to the right side of the AI Governance entity details screen.

About Known Defects

Issues that may impact our customers are documented in our Known Defects Database located here with approved workarounds and targeted releases for resolving the issue.