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 Duration 14 hours

Course Outline

Fundamentals of Artificial Intelligence

  • Definitions and foundational principles
  • Historical development and classification of AI systems
  • Applications of AI in enterprise operations and information technology

Frameworks for Information Technology Auditing

  • Objectives and boundaries of IT audit engagements
  • Critical elements in IT audit: Governance, risk management, and compliance standards
  • Comparative analysis of conventional methods versus AI-integrated auditing

AI Technologies Applied to IT Audit

  • Machine learning algorithms
  • Natural language processing (NLP)
  • Robotic process automation (RPA)
  • Advanced data analytics

Data Acquisition and Analytical Procedures

  • Identifying data sources within IT audit frameworks
  • Leveraging AI for sophisticated data examination
  • Application of predictive analytics in audit processes

AI-Enhanced Risk Evaluation

  • Detection and evaluation of risks utilizing AI capabilities
  • Automation of risk assessment workflows
  • AI-driven tools for sustained monitoring and audit activities

Integrating AI into IT Audit Workflows

  • AI-supported audit strategy and planning
  • Automation of standard audit procedures through AI
  • Real-time reporting mechanisms and AI-enabled dashboards

Ethical Imperatives and Operational Challenges

  • Mitigating AI bias and ensuring equitable outcomes
  • Safeguarding data privacy and security in AI-driven audits
  • Navigating legal and regulatory requirements for government and public sectors

AI in Cybersecurity Audit Practices

  • Utilizing AI for security incident detection and response
  • Auditing the integrity and efficacy of AI-based cybersecurity systems

AI Governance and IT Audit Alignment

  • Incorporating AI into IT governance structures
  • Defining the role of IT auditors in overseeing AI governance

Future Developments in AI and IT Auditing

  • Emerging AI technologies influencing future audit standards
  • Strategic preparation for the evolving AI landscape in IT auditing

Conclusion and Implementation Roadmap

Requirements

  • Foundational proficiency in IT auditing methodologies
  • Basic understanding of artificial intelligence, machine learning, and data analytics principles

Intended Audience

  • IT auditors engaged in public sector or regulated environments
  • AI specialists and data analysts supporting audit functions

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