---
sourceDocument: Australia Enable AI
sourceDocumentLink: https://www.servicenow.com/docs/r/australia/intelligent-experiences

 Release :

    - australia

ft:locale :

    - en-US

ft:publication_title :

    - Australia Enable AI

ft:clusterId :

    - platai

bundleId :

    - platai

workflow :

    - Platform


---

# Recommendations and AI insights

# Recommendations and AI insights {#ariaid-title1}

Release version: Australia  
Updated September 10, 2026  
![](https://www.servicenow.com/docs/portal-asset/ico-clock) 8 minutes to read
Summarize  
![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI  
This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete.  

## Summary of Recommendations and AI insights

Recommendations and AI insights within AI Control Tower help ServiceNow customers prioritize and address critical AI governance issues efficiently.
By continuously evaluating AI assets against governance, security, value, risk, and compliance criteria, AI Control Tower highlights key findings as recommendations or insights, guiding users on what requires action and what provides contextual information.
Show full answer Show less  

## Key Features

* **Prioritized Recommendations:** Focus on high-impact governance tasks without manual searching, with recommendations tailored to your role and ranked by severity, confidence, and age.
* **Resolution Options:** Resolve routine issues automatically using unsupervised agents (Automate with Otto), handle complex matters through guided conversations with supervised agents (Manage with Otto), or manually address issues via direct navigation.
* **Integration with AI Agent Advisor:** Surfaces top automation opportunities as recommendations, enabling discovery and action on agent-building scenarios without separate checks.
* **AI Insights:** Provide contextual facts displayed in dashboards and widgets to enrich understanding without requiring user action.
* **Activity Center:** Offers a comprehensive, filterable view of recommendations across your AI portfolio, supporting bulk or focused governance work.

## Practical Use and Application

* **Access Recommendations:** View top recommendations on the Home page, Risk \& Compliance tab, or asset-specific Overview tabs to quickly identify and act on governance issues.
* **Resolve Efficiently:** Utilize automated or guided workflows to remediate issues, or manually complete tasks when alternative resolutions are applied.
* **Monitor Recommendation Status:** Track progress through lifecycle states such as Not started, In progress, Complete, Failed, or Cancelled to manage governance workflows effectively.
* **Customize Prioritization:** Filter and sort recommendations by priority, confidence, category, or outcome in Activity Center to focus on areas relevant to your governance responsibilities.

## Outcomes Supported

* **Drive AI Productivity:** Identify high-value AI assets for scaling and retire underperforming assets.
* **Improve AI Governance:** Strengthen oversight by completing lifecycle tasks and enforcing policies.
* **Improve Inventory Signal:** Enhance asset data accuracy and completeness.
* **Monitor Security:** Address AI security threats and deviations proactively.
* **Monitor Risk and Compliance:** Maintain adherence to regulatory and policy requirements.

## Why It Matters

By highlighting the most critical AI governance matters and offering actionable recommendations, AI Control Tower enables ServiceNow customers to maintain secure, compliant, and high-performing AI portfolios with less manual effort. This proactive approach helps organizations reduce risk, improve AI asset value, and streamline governance workflows.  
Recommendations and AI insights direct your attention to the AI governance work that matters most, so you can resolve high-impact issues without searching for them.

AI Control Tower continuously evaluates your managed AI assets against governance, security, value, risk, and compliance criteria. When AI Control Tower detects an issue or an opportunity, it surfaces that finding as either a recommendation or an AI insight, depending on whether the user is expected to take action or to read contextual
information.

## Key benefits {#aict-recommendations-ai-insights__section_xqj_zbm_1jc}

* Focus on the highest-priority governance work without searching the product for issues that need your attention.
* Resolve routine issues hands-off by letting an unsupervised agent run the remediation workflow for you.
* Work through complex issues in a guided conversation with a supervised agent that proposes actions you can accept, refine, or reject.
* See the recommendations and insights most relevant to your role, with the severity, confidence, and age of each finding factored into the order.
{#aict-recommendations-ai-insights__ul_ty1_vbm_1jc}

## Recommendations {#aict-recommendations-ai-insights__recommendations}

A recommendation is an action item that AI Control Tower has identified as worth your attention. Each recommendation names the condition that was detected, the outcome it supports, and how you can resolve it.

Recommendations appear throughout AI Control Tower.

Your top recommendations on the Home page
:   Your top recommendations on the Home page provides recommendations across your portfolio. Select See all Recommendations in Activity Center to open the full list.

Your top recommendations on the Risk \& Compliance tab
:   Your top recommendations on the Risk \& Compliance tab under Govern also lists stalled lifecycle tasks and significant issues. For more information, see [Detecting governance insights](https://www.servicenow.com/docs/OLoVKbm4Mga7m3k~bt8uCw "Scheduled detection jobs evaluate your AI portfolio and generate the Stalled Lifecycle Tasks and Significant Issues insights that appear as recommendations.") and [Act on AI asset governance insight recommendations](https://www.servicenow.com/docs/r7zcnSwmSYdiCRbNGk5r1Q "Resolve Stalled Lifecycle Tasks and Significant Issues recommendations to keep AI systems moving through their governance life cycle.").

Recommendations view in Activity Center
:   The full list of recommendations across your portfolio, with filters for category, priority, confidence, and outcome. Use this view when you want to work through recommendations at scale or focus on a specific
    category such as Security or Risk and compliance.

Needs attention section on an asset record
:   Recommendations scoped to a single asset, visible on the Overview tab of the asset record. The recommendations shown here are the subset that apply to that asset. For more information about the
Overview tab, see [Reviewing AI asset status](https://www.servicenow.com/docs/UQMzCwH~0yaQnwRjp6qCgw "Check the governance posture, pending work, key details, and value delivered by a specific AI asset, and act on what needs attention without leaving the record.").  
Note:  
The Assigned to you and Unassigned tabs of the Needs attention widget show lifecycle tasks rather than recommendations. Lifecycle tasks are governance and review work generated by AI asset lifecycle playbooks, not by AI detection.

## AI Agent Advisor recommendations {#aict-recommendations-ai-insights__aiaa-recommendations}

When you install AI Agent Advisor, its highest-value automation opportunities also surface as recommendations in AI Control Tower, so you can discover agent-building opportunities without checking AI Admin Center separately. AI Control Tower shows your top automation opportunities, ranked by projected return on investment, up to a limit you can configure with the
`sn_aict_genai.aaa_automation_opportunities_limit` property (10 by default).

Each recommendation card shows the opportunity's name and a short description. Selecting the recommendation's action opens the Automation details page for that specific opportunity in AI Admin Center, where you can act on it, such as by building an agent.

This integration requires no setup. The connection activates automatically when both AI Agent Advisor and AI Admin Center are installed on your instance. AI Agent Advisor must also complete at least one mining run before its opportunities appear. If AI Admin Center isn't installed, AI Agent Advisor doesn't send any recommendations to AI Control Tower.

Recommendations stay current on their own, refreshing daily. If an opportunity is still among the top group the next day, AI Control Tower updates the existing recommendation instead of adding a duplicate. If an opportunity drops out of the top group, or no longer exists in AI Admin Center by the time you select it, AI Control Tower removes the recommendation.

For details on AI Agent Advisor, see [AI Agent Advisor](https://www.servicenow.com/docs/0DhRnlvTRqtF1BUhnsuoxQ "The AI Agent Advisor automatically discovers automation opportunities in your instance based on actual operational data and helps you to deploy AI agents to implement them.").

## AI insights {#aict-recommendations-ai-insights__ai-insights}

An AI insight is a contextual fact that AI Control Tower adds to a dashboard to give you a richer reading of the data. Unlike a recommendation, an AI insight does not ask you to take action. It appears as a short line of text near the data it
explains, such as "Total productivity gains in last 30 days" or "Three AI systems delivered 82% of total value." AI insights appear inside widgets on the Home page, the Value page, the Risk and Compliance page, Security
page, and other AI Control Tower dashboards.

When an AI insight is associated with a supervised agent, you can select Manage with AI to start a conversation that expands on the insight with deeper analysis.

## Resolving recommendations {#aict-recommendations-ai-insights__resolution-patterns}

Each recommendation includes a primary resolution that AI Control Tower has selected as the most efficient path to address the underlying issue. Alternatively, you can mark the recommendation as complete if you address the issue another way. For the full
procedure, see [Resolving AI recommendations in Activity Center](https://www.servicenow.com/docs/YyvrK4Lt2xLlA~Jd0y01TQ "Resolve the AI recommendations that AI Control Tower generates when it detects an issue or an opportunity in your AI portfolio, using AI automation, a guided AI conversation, or your own review.").

The following options are available in the Actions menu:
{#aict-recommendations-ai-insights__resolution-patterns__entry__2}

| Action | Description |
|-|-|
| View details | Provides the reasoning behind the recommendation, the asset or scope it applies to, and the history of earlier runs. |
| Complete | Marks the recommendation as resolved without running the primary resolution action. Use this option when you have addressed the underlying issue in another way. |
| Delete | Removes the recommendation. A deleted recommendation might reappear if AI Control Tower detects the same condition again. |
[ ]

Depending on how the recommendation was produced, you can use one of the following resolution options:
{#aict-recommendations-ai-insights__resolution-patterns__entry__10}

| Primary resolution | Description |
|-|-|
| Automate with Otto | An unsupervised agent runs the resolution workflow on your behalf. When you confirm, the agent executes the steps and updates the recommendation status to In progress, then to Complete once the work is done. This resolution pattern is used for recommendations where the steps are routine and don't require your input, such as populating missing asset descriptions. |
| Manage with Otto | A supervised agent opens a conversation in the AI Control Tower chat interface. The agent proposes actions, and you accept, refine, or reject each one. This resolution pattern is used for recommendations that benefit from your judgment, such as reviewing the evidence behind a security threat before resolving it. |
| Open | AI Control Tower redirects you to the record, page, or workflow where you can resolve the issue directly. This resolution pattern is used for recommendations that require changes in another part of the product, such as creating tasks in an onboarding playbook. |
[ ]

When you select View details from the action menu, the side panel offers two views:

Focused
:   Shows the current status, the steps the agent will take or has taken, and an estimated time to complete. Use this view while an agent is running so you can monitor progress without leaving the page.

Details
:   Shows the full reasoning behind the recommendation, including the data sources that contributed to it and the history of earlier runs.

## Prioritizing recommendations {#aict-recommendations-ai-insights__prioritization}

AI Control Tower does not show every recommendation it detects. Recommendations are prioritized according to the following factors:

Your role
:   An AI steward and a product owner see different recommendations in different order. Each role is responsible for different outcomes. For example, a product owner sees recommendations that help drive productivity for
    their own AI assets first, while an AI steward sees recommendations that improve inventory signal and AI governance across the portfolio first.

Severity
:   Each recommendation carries a priority level of 1-Critical, 2-High, 3-Medium, or 4-Low. Higher severity items rank above
    lower severity items when other factors are equal.

Confidence
:   Each recommendation carries a confidence level of Low, Medium, or High. Confidence reflects how certain AI Control Tower is that the detected condition is accurate. A high-confidence recommendation ranks above a low-confidence recommendation at the same severity.

Age
:   Recommendations become less prominent over time if no one acts on them. This prevents a long-standing issue from permanently occupying the top of the list and gives newer recommendations a chance to surface.

In Activity Center, use the Refine list panel to filter recommendations by priority, confidence, category, or outcome, and override the default ranking to focus on a specific area.

## Recommendation outcomes {#aict-recommendations-ai-insights__outcomes}

Every recommendation is tagged with an outcome that identifies the business goal the recommendation supports. The outcome appears on the recommendation card.
{#aict-recommendations-ai-insights__outcomes__entry__2}

| Outcome | Description |
|-|-|
| Drive AI productivity | Helps you increase the value that your AI assets deliver, such as identifying high-performing assets to scale or underused assets to retire. |
| Improve AI governance | Helps you strengthen oversight of your AI portfolio, such as completing lifecycle tasks or enforcing policy across managed assets. |
| Improve inventory signal | Helps you make your inventory more complete and accurate, such as populating missing asset descriptions or reviewing newly discovered assets. |
| Monitor security | Helps you respond to AI security threats and access issues, such as reviewing high-severity security events or addressing agent output deviation. |
| Monitor risk and compliance | Helps you maintain regulatory and policy compliance, such as reviewing overdue risk assessments or addressing non-compliant controls. |
[ ]

## Recommendation status {#aict-recommendations-ai-insights__status}

Each recommendation moves through a lifecycle as you or an agent works on it. The status appears in the side panel that appears when you select View details.
{#aict-recommendations-ai-insights__status__entry__2}

| Status | Description |
|-|-|
| Not started | The recommendation has been generated but no one has acted on it. |
| In progress | An agent is running or the assignee is working on the recommendation. |
| Complete | The recommendation has been resolved. Completed recommendations are removed from the list. |
| Failed | An agent could not complete the recommendation, or could only complete it for some of the assets it targeted. You can retry the action or resolve the recommendation manually. |
| Cancelled | The recommendation was stopped before it completed, either by the user or by the system. |
[ ]

You can manually mark a recommendation as Complete or delete it from the action menu on the recommendation card, regardless of its current status.
**Related concepts**   

* [Activity Center](https://www.servicenow.com/docs/jYWhx1KSM0nillT3chhMNA "Track and act on the governance work generated across AI Control Tower from a single workspace, including lifecycle tasks, security tasks, change and offboarding requests, and AI recommendations.")
* [ServiceNow Otto in AI Control Tower](https://www.servicenow.com/docs/vDD~_m64OFmSaau1Lv3wWA "Ask questions about your AI portfolio in plain language and get answers drawn from your own AI Control Tower records.")
* [Detecting governance insights](https://www.servicenow.com/docs/OLoVKbm4Mga7m3k~bt8uCw "Scheduled detection jobs evaluate your AI portfolio and generate the Stalled Lifecycle Tasks and Significant Issues insights that appear as recommendations.")  
**Related tasks**   

* [Act on AI asset governance insight recommendations](https://www.servicenow.com/docs/r7zcnSwmSYdiCRbNGk5r1Q "Resolve Stalled Lifecycle Tasks and Significant Issues recommendations to keep AI systems moving through their governance life cycle.")

