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What if you could test more transactions, identify control weaknesses faster, and produce audit evidence that stands up to scrutiny?
Artificial intelligence is transforming internal auditing. But identifying anomalies is only the beginning. The real challenge is turning data into reliable, reproducible, and defensible audit conclusions.
AI-Powered Control Testing is a practical guide for internal auditors, risk professionals, and compliance specialists who want to combine AI-assisted analysis with effective control testing and professional judgment.
Written by Salih Ahmed Islam, MBA, CIA, GRCP, an internal audit professional with more than 25 years of international experience, this book bridges the gap between AI theory and real-world audit practice.
WHAT YOU WILL LEARN
Apply 30 practical internal audit control tests across key business processes.
Identify potential duplicate payments, unauthorized transactions, unusual discounts, and supplier-related risks.
Test procurement, accounts payable, sales, receivables, travel expenses, payroll, inventory, finance, and IT general controls.
Translate control objectives into clear, repeatable data analytics rules.
Use AI assistants responsibly to support audit planning, exception analysis, and documentation.
Validate potential exceptions using reliable source evidence and independent verification.
Build continuous controls monitoring and AI-enabled internal audit capabilities.
WHAT MAKES THIS BOOK DIFFERENT?
Rather than focusing on generic AI prompts, this book provides a structured control-testing methodology.
Each practical test includes a control objective, associated risks, required data, screening logic, investigation procedures, AI-assisted review guidance, and documentation considerations.
A detailed procurement case study demonstrates how individual tests can form part of an integrated audit approach.
WHO SHOULD READ THIS BOOK?
This book is designed for internal auditors, audit managers, chief audit executives, compliance professionals, risk managers, internal control specialists, and audit analytics practitioners.
Whether you are beginning your AI journey or strengthening an established audit function, you will discover practical ways to improve the efficiency, consistency, and defensibility of your control testing.
AI does not replace professional judgment. It helps auditors ask better questions, examine more evidence, and make better-informed decisions.
Move beyond AI experimentation. Start building a more data-driven, evidence-focused internal audit practice.
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