---
title: Prevent and resolve technical debt with AI
description: Use the Scan Engine and ServiceNow Otto AI agent to prevent technical debt as you code or remediate existing findings from completed scans.
locale: en-US
canonical_url: https://www.servicenow.com/docs/r/australia/impact/prevent-resolve-technical-debt-ai.html
release: australia
topic_type: concept
last_updated: "2026-10-09"
reading_time_minutes: 2
breadcrumb: [Platform Health, Using Impact, Impact]
---

# Prevent and resolve technical debt with AI

Use the Scan Engine and ServiceNow Otto AI agent to prevent technical debt as you code or remediate existing findings from completed scans.

## Prevention and remediation workflows

AI-powered code fixes are available through two distinct workflows. Understanding which workflow applies to your situation helps you take action quickly.

<table><thead><tr><th>

Workflow

</th><th>

When You Use It

</th><th>

Outcome

</th></tr></thead><tbody><tr><td>

Real-time Prevention

</td><td>

-   You're actively writing or modifying code in your development environment.
-   When you save a record, the Scan Engine detects violations inline and you generate an AI fix before committing or promoting the code.

</td><td>

-   Prevents technical debt from reaching production.
-   Reduces time spent in code review cycles.

</td></tr><tr><td>

Batch Remediation

</td><td>

-   A scan has completed and findings are displayed in the findings dashboard.
-   You review the list of violations and generate AI fixes in bulk or individually to clean existing technical debt.

</td><td>

-   Accelerates remediation of existing issues.
-   Reduces manual development effort and errors when fixing production code.

</td></tr></tbody>
</table>## Unified AI engine

Whether you're preventing technical debt during development or remediating findings from scans, you interact with the same AI fix generation engine.

-   ServiceNow Otto AI agent analyzes your code against scan definitions
-   Side-by-side code comparison interface shows original code versus suggested changes
-   You accept, reject, or revise suggested fixes using the same controls
-   Exception workflows for Recommend level findings follow the same process
-   All changes are tracked in your active update set with full audit trails

## AI-suggested fix capabilities

The AI fix engine handles common coding violations quickly and accurately. Common fix types include the following:

-   Replacing deprecated API calls with current equivalents, for example, gs.log to gs.error
-   Adding missing error handlers to prevent unhandled exceptions
-   Correcting scoped app API usage to match ServiceNow general guidelines
-   Removing unsafe or deprecated functions to improve security
-   Formatting code to match style guidelines and improve maintainability

## Key benefits

-   Faster development: Developers can apply AI-generated fixes instantly instead of manually reviewing and correcting code
-   Consistency: All fixes follow the same coding standards and patterns, reducing variability across your codebase
-   Learning: Side-by-side code comparisons help developers understand ServiceNow general guidelines and leading practices
-   Scale: Bulk generate fixes to remediate dozens of violations in one workflow instead of fixing them individually
-   Reduced risk: AI fixes are generated from validated patterns and include full audit trails for compliance

## Next steps

Choose the workflow that matches your current task.

-   You're writing code and want to catch violations before saving, See [Use Real-time prevention monitoring while coding](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/impact/real-time-prevention-monitoring.md)
-   A scan has completed and you want to fix existing findings, See [Remediate existing findings with AI-suggested fixes](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/impact/batch-remediation-with-ai.md).