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Internal Auditor

Present to the audit committee and board

Enhances✓ Available Now

What You Do Today

You report audit results, risk assessments, and internal control status to the audit committee — providing the independent assurance that governance requires.

AI That Applies

AI generates board-level dashboards, summarizes audit activity and findings, and creates trend analyses that show the organization's risk and control trajectory.

Technologies

How It Works

The system ingests that show the organization's risk and control trajectory as its primary data source. The analytics engine aggregates data across sources, applies statistical analysis to identify significant patterns and outliers, and presents the results through visualizations that highlight what needs attention. The output — board-level dashboards — surfaces in the existing workflow where the practitioner can review and act on it.

What Changes

Board reporting becomes more visual and data-driven with AI-generated dashboards and trend analyses.

What Stays

The credibility and independence that make your reports meaningful, the courage to deliver uncomfortable findings, and the judgment about what the board truly needs to know.

What To Do Next

This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.

1

Establish Your Baseline

Know where you are before you move

Before adopting AI tools for present to the audit committee and board, understand your current state.

Map your current process: Document how present to the audit committee and board works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: The credibility and independence that make your reports meaningful, the courage to deliver uncomfortable findings, and the judgment about what the board truly needs to know. These are the boundaries AI won't cross.
Assess your data readiness: AI tools for this area need data to work. Check whether your organization has the historical data, integrations, and data quality to support Executive Reporting AI tools.

Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.

2

Define Your Measures

What to track and how to calculate it

Time per cycle

How to calculate

Measure how long present to the audit committee and board takes end-to-end today, then after AI adoption.

Why it matters

The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.

Quality of output

How to calculate

Track error rates, rework frequency, or stakeholder satisfaction scores before and after.

Why it matters

Speed without quality is just faster mistakes. Measure both.

When to check: Check after 30 days of consistent use, then quarterly.
The commitment: Give new tools at least 30 days before judging. The first week is always awkward.
What NOT to measure: Don't measure AI adoption rate as a KPI. Adoption follows value — if the tool helps, people use it.
3

Start These Conversations

Who to talk to and what to ask

your Chief Compliance Officer

If we automated the routine parts of present to the audit committee and board, what would the team do with the freed-up time?

They set the risk appetite for AI adoption in regulated processes

your legal counsel

Who on the team has the most experience with present to the audit committee and board — and have they seen AI tools that could help?

AI in compliance creates new regulatory interpretation questions

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.