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Ext. PublicationSecond Line Ready: How to Use AI in SOX Compliance Without Over Complicating It
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About the Second Line Ready Series: While our Second Line Ready series aims to inform those who govern, oversee or operate in the second line of defense, those who participate in the third line — internal auditors, SOX professionals, external auditors, risk professionals and directors — will also find this content extremely beneficial to gain efficiency in their responsibilities.
When considering artificial intelligence (AI) in Sarbanes-Oxley Act (SOX) compliance, there’s a simple guiding principle: use AI to replace the repetitive tasks, not the judgment.
For most companies, the real value of using AI isn’t in chasing futuristic tools — it’s in transforming SOX into a more efficient, consistent and risk-aligned process. That means, use AI to navigate the necessary but time-consuming SOX tasks, so auditors can focus on the areas that demand the highest level of professional judgment.
Planning and Scoping: Starting Sharper
Every year brings process updates, new reports and control changes. The challenge isn’t knowing whether there are updates required. It’s really about quickly pinpointing where there’s internal control over financial reporting (ICFR) impact and where the risks are shifting in the processes.
- AI summaries of prior-year work: By loading prior findings, management responses and walkthrough notes into a secure AI environment, you can quickly generate concise “scoping packs” with linked references. This saves hours of preparation and ensures discussions start with a shared understanding of items carried forward from last year. Scoping packs represent a bundle of materials prepared at the start of an audit, review or project that defines what will and won’t be covered. It gives stakeholders a clear view of the scope, objectives, timeline and responsibilities before work begins.
- Drafting walkthrough questions: Microsoft Copilot in Word or Teams can turn scoping packs into focused walkthrough questions. For example, if revenue cutoff was a recurring issue in prior years, AI will draft targeted questions that can be refined before discussions with stakeholders begin.
- Risk balance calibration: AI can also scan control sets and highlight where risk coverage may be disproportionate. Keep in mind this doesn’t replace scoping decisions. It is, however, a quick prompt to validate that you’re aligned to where the actual risk exists.
Test of Design: Sharpening Precision
Control design is not about the volume of documentation generated. It’s about whether the controls are written in sufficient detail to effectively describe how financial errors are prevented and/or detected and precisely enough to represent what actually occurs when the control is performed. A heavy amount of judgment is involved in striking the right balance when describing a control. This also needs to stand up to external audit scrutiny. Used effectively, AI can strengthen the control’s description and precision.
- Strengthening management review controls: Copilot in Excel can review control language and flag vague descriptions like “review for reasonableness” without thresholds or frequency. Reviewers then decide what needs to be clarified.
- Consistency checks: When similar controls exist across business units, AI is able to highlight subtle differences. Comparisons can be made in seconds using Excel, giving reviewers a quick side-by-side view.
- New cycles: For new applications or processes, Copilot drafts controls in a standard format (objective, frequency, owner and evidence). Reviewers then can edit instead of starting from scratch.
Test of Effectiveness: Managing Volume at Scale
Subsequent to first year compliance, recurring SOX requirements are spent testing control effectiveness. Gathering test evidence, documenting exceptions and maintaining consistency across a large team is where AI shines.
- Evidence management: Copilot Studio flows can monitor a Teams channel or mailbox, automatically rename evidence files with a control ID and test period, and file them in SharePoint with metadata. Setup takes hours, not months, and removes tedious administrative tasks.
- Exception narratives: Copilot can also take raw tester notes and produce a standard, concise exception narrative that explains what failed, the impact and root cause. Reviewers can then spend valuable time finalizing the information much more efficiently, and exceptions will read consistently across dozens of testers.
- Expanded testing with documentation: AI also helps scale areas like journal entries or segregation of duties (SoD) testing. Equally important, it drafts the documentation, assesses which data was analyzed, which thresholds applied and what judgments were made. In this manner, broader testing is both defensible and ready for external audit review.
Remediation and Reporting: Moving Beyond Dashboards
Many SOX compliance programs use dashboard reporting tools. AI adds value by keeping a status report continuously current, holding owners accountable and turning raw data into usable management information.
- Automated owner follow-up: A Copilot Studio flow can alert issue owners weekly, capture updates and log them into a tracker for monitoring. Escalations trigger automatically, reducing the excessive time managers spend on follow-up with internal audit staff and process owners.
- Surfacing systemic themes: AI can scan your issue log and identify patterns. Examples include “most delays tie back to change management,” or “exceptions cluster in one geography.” This is the kind of trend information that is powerful for executives to use in decision-making.
- Executive-ready summaries: This is where AI really shows its power. Instead of exporting a tracker and manually formatting slides, Copilot takes issue and remediation data, and produces polished board update materials, such as current status by entity, trendlines since last quarter and the top three risks requiring attention. Reviewers can modify the information as needed, but the heavy lifting is done. The result: reporting that’s consistent, current and polished enough to drop into an audit committee deck in minutes.
Governance: Using AI in SOX Safely
To trust AI in SOX, the framework matters as much as the output. There are five guardrails to keep in place when using AI in SOX compliance:
- AI policy: Include SOX compliance in the organization’s AI policy or develop a separate policy, if necessary.
- Save the trail: Make sure that prompts, drafts and reviewer changes are part of the workpapers. Even a short appendix — “AI-assisted draft, reviewed by X” — may be enough.
- Reviewer owns the decision: AI outputs should always be considered drafts. A human makes the final decision, and this is a key step in the AI oversight process.
- Keep it secure: Use AI tools inside Microsoft 365, AuditBoard or Azure with logging (Purview, a Microsoft data governance service) turned on. Never paste evidence into open tools.
- Collaboration with external auditors: Clearly note where AI was used in the SOX compliance effort and ensure the AI inventory is complete. When collaborating with your external auditors in using AI in SOX compliance, they should care more about clarity than perfection. However, each audit team is different. Confirming how AI tools will be used during the planning phase of the SOX compliance process will lessen the likelihood of missed expectations.
- Start narrow, then scale: Pick one or two high-volume pain points, like evidence routing or exception write-ups, to pilot test. Be sure the process is effective before expanding.
Final Thoughts
AI won’t change the fundamentals of SOX, but it can take the weight off the high-volume, repetitive aspects of the compliance effort. This can enable key stakeholders to spend more time on where professional judgment is needed and on what really matters. That’s where AI can deliver the most value — not in shortcuts, but in freeing capacity so process owners, those charged with oversight and internal audit teams stay focused on risk.
Is your SOX cycle weighed down by manual tasks? Contact us. Weaver can help you use AI to free up time for what matters most: risk and judgment.
©2025
Second Line Ready Series
This article is part of a series for professionals who govern, oversee or operate the second line of defense — from CFOs and controllers to audit directors and risk managers — this series delivers practical strategies, emerging risk insights and real-world guidance to strengthen oversight, improve existing programs and help add value within the business. Those in the third line of defense have also found the content beneficial in employing ways to gain efficiency.
