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Course Outline

Introduction to AI

  • Core definitions and key concepts
  • The development and classification of AI systems
  • The role of AI in business and IT sectors

Fundamentals of IT Auditing

  • Objectives and scope of IT audit functions
  • Essential IT audit concepts: governance, risk, and compliance
  • Comparing traditional auditing methods with AI-enhanced approaches

AI Technologies in IT Audit

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

Data Collection and Analysis

  • Sources of data within IT audits
  • Applying AI for advanced data analysis
  • The role of predictive analytics in IT auditing

AI-Driven Risk Assessment

  • Identifying and evaluating risks using AI
  • Automation of risk assessment processes
  • Utilizing AI tools for continuous monitoring and audit activities

Integrating AI into IT Audit Processes

  • AI-assisted audit planning
  • Automating audit procedures through AI
  • Real-time reporting and AI-powered dashboards

Ethical Considerations and Challenges

  • Addressing AI bias and ensuring fairness
  • Data privacy and security considerations in AI-driven audits
  • Legal and regulatory frameworks and implications

AI in Cybersecurity Auditing

  • Using AI to detect and mitigate security incidents
  • Auditing systems driven by AI for cybersecurity

AI Governance and IT Audit

  • The place of AI within IT governance frameworks
  • The evolving role of IT auditors in AI governance

Future Trends in AI and IT Auditing

  • Emerging AI technologies that will shape IT audit
  • Preparing for the future landscape of AI in IT auditing

Summary and Next Steps

Requirements

  • Foundational knowledge of IT auditing principles
  • Basic comprehension of artificial intelligence, machine learning, and data analytics concepts

Target Audience

  • IT auditors
  • AI and data analysts
 14 Hours

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