Issue summarization

ServiceNow Otto for IRM quickly analyzes issue records, descriptions, activity logs, remediation tasks, and generates concise summaries to help you understand the issue.

Issue resolution agentic workflow

The issue resolution agentic workflow in Integrated Risk Management (IRM) enables issue managers and analysts to resolve GRC issues through the ServiceNow Otto panel. The workflow uses AI agents to suggest targeted solutions for key steps during the resolution process.

Risk assessment summarization

Risk assessment summary generation uses generative AI to assist assessors during assessment submissions and provide approvers and stakeholders with a quick overview of assessment progress and key insights.

Control objective rationalization and deduplication

The control objective rationalization and deduplication process uses generative AI to identify similar or duplicate control objectives, enabling teams to consolidate them by retaining one, retiring duplicates, or merging them into a common control objective, enhancing overall efficiency across compliance operations.

Risk event summarization

The risk event summarization feature helps risk managers quickly understand the context and key details of a risk event, even when multiple coordinators have been involved over time. It streamlines onboarding for new assignees and improves decision-making efficiency for approvers, especially in multi-level approval workflows, by providing concise AI-generated summaries of each event.

Rationalization of control objectives

Skill for creating a common control objective as part of the control objective rationalization process.

Control recommendation on regulatory alert

Skill for recommending controls for an incoming regulatory alert.

Issue submission agent

The issue submission AI agent is now available in Employee Center, enabling employee users to report issues through a guided conversational experience. The agent helps structure the issue and recommends relevant controls, entities, and policies based on the input provided. This ensures that the issue is well-defined and enriched with contextual information before submission.

Suggest potential risks agentic workflow

AI-driven risk identification analyzes entity context and surfaces relevant risks from internal libraries, industry patterns, and optional external sources. It generates a single, ready-to-triage risk list, reducing manual effort and duplication while ensuring comprehensive coverage.

Control objective impact analyzer

This generative AI feature analyzes changes in citations and identifies control objectives that should be reviewed based on the modified citation content. It intelligently matches changed citation requirements with existing control objectives to suggest potential updates, helping teams maintain alignment between citations and control objectives.

Control objective change agent

This capability introduces an AI-driven process to automatically update a control objective’s description and supplemental guidance whenever its associated citations are modified. It leverages agentic AI to analyze citation changes, identify their impact on the control objective, and generate precise, contextually relevant updates.