Excel-based intelligent automation for audit evidence matching and testing.
AI SKILLS · Finance, accounting & investment
Use AI on audit evidence with professional scepticism
Use AI for sampling, tie-outs and anomaly flags while keeping evidence sufficient, appropriate and documented.
Why this skill matters
Audit standards still require the auditor to judge evidence; an AI flag or summary is not evidence on its own.
What to learn
- Explain what an AI test did and did not cover
- Re-perform a sample of AI tie-outs and anomaly flags
- Document AI use in workpapers so a reviewer can follow it
Before you begin
Audit fundamentals and an understanding of materiality
PUT IT INTO PRACTICE
Build a work sample
Run an AI anomaly check on a fictional general ledger, re-perform a sample of the flagged and unflagged items, and write the workpaper.
Evidence of progress
A workpaper showing scope, re-performed samples, false positives and conclusions. This is a practice exercise, not an audit performed under a standard.
This exercise is an original ToolGrail suggestion. Use public, synthetic, or approved data.
LEARNING RESOURCE
IAASB: technology and the future of audit and assurance
IAASB · Resource checked 2026-11-13
Open learning resource ↗This may be documentation, a framework, or a training path. Product access, accounts, or paid licenses may be needed for hands-on exercises.
Tools you could practice with
Chosen by an editor because they support this exercise. They are examples, not requirements or endorsements: use a tool you already have access to, with synthetic or approved data, and check its evidence level.
AI financial-risk analytics that scans ledgers for anomalies for audit teams.
Digital audit platform with AI assistants, data and workflow for human-led audits.
AI platform for the audit and accounting profession with workflow-embedded intelligence.
Skill descriptions, exercises, and priorities are editorial. They are not professional qualifications or guarantees of employment. Read our skills methodology →
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