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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

  • Fundamental 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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