AI-Driven Auditing: Mastering Automation and Analytics for the Future of Internal Audits

Course Code: ARG 2566

445 Course Visits

Course Sector:

Audit, Risk and Governance

Request in house training Call Me Back

Course Dates and Locations

Choose a date and location to book your seat

No.

Date

Days

Location

Fees

Enrollment

25 - 29 Aug 2025

5 Days

Online, Virtual

$2,150

17 - 21 Nov 2025

5 Days

Amsterdam, Netherlands

$4,950

Introduction

Training course introducion / brief

AI-Driven Auditing:

This training program will immerse participants in the world of AI-powered audit analytics and automation, equipping them with the tools, techniques, and ethical frameworks necessary to integrate AI into their internal auditing functions.

The training program will cover the core principles of AI and its applications in auditing, from enhancing traditional audit processes to automating key tasks such as data analysis, fraud detection, and compliance monitoring.

Participants will also explore ethical considerations surrounding AI in auditing, including addressing biases and ensuring data privacy, while learning how to leverage AI tools and platforms effectively.

By the end of this training, participants will have a solid understanding of how AI can transform internal audit operations and will be equipped to apply AI solutions to improve audit quality, productivity, and decision-making.

Learn key concepts of AI, including machine learning and natural language processing, and how they are reshaping the audit landscape.
Understand how AI can automate and enhance specific audit tasks such as data analysis, fraud detection, risk assessment, and compliance monitoring.
Dive deeper into AI’s capabilities beyond traditional analytics, including predictive analytics, anomaly detection, and scenario analysis.
Gain hands-on experience with AI-powered tools and platforms relevant to internal audits, such as ACL Analytics, MindBridge Ai Auditor, CaseWare IDEA, and others.
Explore ethical concerns such as AI bias, transparency, data privacy, and the regulatory frameworks that govern their use in auditing (GDPR, CCPA).
Understand audit automation tools and techniques, including platforms such as UiPath and Automation Anywhere, and how to integrate automation into audit processes.
Learn how AI-powered tools can assist in recovering missing or corrupted data and discovering external data sources relevant to audit objectives.
Discover how AI tools can automate the process of aligning and standardizing audit data from various sources, formats, and naming conventions.
Learn how to strategically plan for the adoption of AI and automation within the internal audit function, and how to make data-driven decisions with AI-enhanced insights.

Internal Auditors & Managers
Risk & Compliance Officers
Finance & IT Auditing Professionals
Data Analysts & Consultants in Audit
Professionals seeking to adopt AI in audit processes

Introduction to AI and the Role of AI in Internal Auditing

Introduction to Artificial Intelligence: Key concepts and technologies.
Machine Learning, Natural Language Processing, and their role in AI.
How AI is transforming data analysis and audit processes?
Use of AI in risk management, fraud detection, and compliance monitoring.
How AI enhances audit data interpretation and analysis.
Using AI to improve accuracy and efficiency in audit analytics.
Case Studies.

How AI Can Automate or Improve Specific Audit Tasks

Automating data analysis, testing, and evidence gathering using AI.
Automating fraud detection and risk assessment tasks.
AI’s role in real-time audit monitoring and reporting.
Automating compliance checks and regulatory reporting.
Case Studies.

AI Beyond Traditional Analytics

What Traditional Analytics Misses?
Limitations of traditional audit analytics methods.
How AI enhances traditional analytics?
Predictive analytics, anomaly detection, and forecasting.
Natural Language Processing (NLP) for analyzing unstructured data.
Going beyond historical data to predict and mitigate future risks.
AI in scenario analysis and stress testing.
Practical Analysis.

Emerging AI Tools and Platforms for Internal Audit

Introduction to AI platforms specifically designed for internal auditing.
ACL Analytics – Automating data analysis and audit sampling.
MindBridge Ai Auditor – AI-powered anomaly detection in financial transactions.
CaseWare IDEA – Data analysis and audit automation tools.
TruQua Solutions – AI and machine learning for risk and compliance.
How to choose the right tool based on audit objectives?
Integration with existing systems (ERP, financial software).
Practical application.

Ethical Considerations When Using AI for Audit Analytics

AI biases, transparency issues, and data privacy concerns.
The impact of biased training data on audit outcomes.
Techniques to minimize bias in AI models.
Ensuring data privacy when using AI for auditing.
Regulatory frameworks (GDPR, CCPA) and their implications on AI auditing.
How to ensure audit trail transparency when AI tools are used?
Ethical considerations in AI decision-making and reporting.
Case Studies.

Introduction to Audit Automation

What is Audit Automation?
Overview of audit automation and its role in streamlining the audit lifecycle.
Benefits of Automating Audits
Introduction to automation platforms and tools (UiPath, Automation Anywhere).
How to Get Started with Audit Automation tools?
Steps for adopting automation in your audit department.
Practical application.

AI-Powered Tools for Intelligent Data Recovery

Introduction to intelligent data recovery techniques.
How AI Enhances Data Recovery
AI for extracting and validating missing or corrupted data from various sources.
Overview of AI tools used for recovering data from different systems (Like: DataRobot).
Practical application.

AI for Connecting and Discovering External Data Sources

The importance of external data for comprehensive audits.
How AI Discovers and Connects to External Data?
AI algorithms that search and connect to external data sources based on audit objectives.
Alteryx – AI-powered tool for data preparation and external data connection.
Talend – AI-enhanced data integration and discovery tools.
Practical application.

Automated Data Harmonization Using AI

Understanding Data Harmonization in Auditing
Importance of aligning and standardizing data for audits.
Tools and techniques that automate the process of aligning data from different formats or naming conventions.
AI Tools for Data Harmonization:
Informatica – AI-based data integration and harmonization platform.
DataRobot – Automating data harmonization with AI.
Practical Application.

Practical Workshop.

Boost certificate of completion

BOOST's Professional Attendance Certificate “BPAC” is always given to the delegates after completing the training course, and depends on their attendance of the program at a rate of no less than 80%, besides their active participation and engagement during the program sessions.

ENDORSED EDUCATION PROVIDER

Flexible deadlines

Customized dates accordance to your schedule

Shareable Certificate

Earn certificate upon completion

COURSE METHODOLOGY

Our Training programs are implemented by combining the participants' academic knowledge and practical practice (30% theoretical / 70% practical activities).

At The end of the training program, Participants are involved in practical workshop to show their skills in applying what they were trained for. A detailed report is submitted to each participant and the training department in the organization on the results of the participant's performance and the return on training. Our programs focus on exercises, case studies, and individual and group presentations.

Download Company profile

Download Calendar

Trending Courses

The most bespoke and flexible training courses

Open courses table

Dec

- 05 -
Days

The Business Analyst (PBA) - PMI Certified

Dubai, UAE

TRAINING COURSE: AI-Driven Auditing: Mastering Automation and Analytics for the Future of Internal Audits