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Accountant

Audit Support

Enhances◐ 1–3 years

What You Do Today

Respond to auditor requests — PBC lists, sampling selections, process walkthroughs, confirmations. During audit season, 30% of your time goes to pulling support while still doing your regular job.

AI That Applies

AI-organized PBC packages that auto-compile documents. Automated confirmation generation and tracking. Intelligent document retrieval from unstructured file systems.

Technologies

How It Works

The system ingests unstructured file systems as its primary data source. A language model processes the input by identifying relevant context, generating appropriate responses, and structuring the output to match the expected format and domain conventions. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context. The walkthrough conversations.

What Changes

PBC requests get fulfilled in hours instead of days. The AI finds the invoice, contract, and approval email without you digging through 3 systems.

What Stays

The walkthrough conversations. Explaining your processes, controls, and judgment calls to auditors. Audit is a relationship — the better you explain, the smoother it goes.

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 audit support, understand your current state.

Map your current process: Document how audit support 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 walkthrough conversations. 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 Retrieval-Augmented Generation 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 audit support 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 CFO or VP Finance

Which compliance checks are we doing manually that could be continuous and automated?

They're prioritizing which finance processes to automate first

your ERP or finance systems admin

How would our regulator react to AI-assisted compliance monitoring — have we asked?

They know what automation capabilities exist in your current stack

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.