Course Outline

Introduction to AI

  • Definition and key concepts
  • Evolution and types of AI
  • AI in business and IT

Overview of IT Auditing

  • Purpose and scope of IT audit
  • Key concepts in IT audit: Governance, risk, and compliance
  • Traditional vs. AI-enhanced IT auditing

AI technologies in IT Audit

  • Machine learning
  • Natural language processing (NLP)
  • Robotic process automation (RPA)
  • Data analytics

Data Collection and Analysis

  • Data sources in IT audits
  • Using AI for data analysis
  • Predictive analytics in IT auditing

AI-Driven Risk Assessment

  • Identifying and assessing risks with AI
  • Automating risk assessments
  • AI tools for continuous monitoring and auditing

Implementing AI in IT Audit Processes

  • AI-driven audit planning
  • Automating audit procedures with AI
  • Real-time audit reporting and AI dashboards

Ethical Considerations and Challenges

  • AI bias and fairness
  • Data privacy and security in AI audits
  • Legal and regulatory implications

AI in Cybersecurity Auditing

  • AI for detecting and responding to security incidents
  • Auditing AI-driven cybersecurity systems

AI Governance and IT Audit

  • AI in IT governance frameworks
  • Role of IT auditors in AI governance

Future Trends in AI and IT Auditing

  • Emerging AI technologies impacting IT audit
  • Preparing for the future of AI in IT auditing

Summary and Next Steps

Requirements

  • Basic knowledge of IT auditing concepts
  • Basic understanding of artificial intelligence, machine learning, and data analytics

Audience

  • IT auditors
  • AI and data analysts
 14 Hours

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