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Course Outline

Introduction to Artificial Intelligence

  • Core definitions and foundational concepts
  • Historical development and categories of AI systems
  • Integration of AI within business operations and information technology frameworks

Overview of Information Technology Auditing

  • Objectives and scope of IT audit engagements
  • Fundamental principles: Governance, risk management, and compliance
  • Comparison between traditional methods and AI-augmented IT auditing approaches

Application of AI Technologies in IT Audit

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

Data Collection and Analytical Procedures

  • Identification of relevant data sources for IT audits
  • Leveraging AI for comprehensive data analysis
  • Utilization of predictive analytics in audit processes

Risk Assessment Capabilities Enhanced by AI

  • Detection and evaluation of risks using automated tools
  • Streamlining risk assessment workflows
  • Deployment of AI systems for continuous monitoring and audit support

Integration of AI into IT Audit Workflows

  • Strategic audit planning driven by AI insights
  • Automation of standard audit procedures
  • Generation of real-time reporting and interactive dashboards for government stakeholders

Ethical Implications and Operational Challenges

  • Addressing algorithmic bias and ensuring equitable outcomes
  • Maintaining data privacy and security standards in AI-enabled audits
  • Navigating legal requirements and regulatory frameworks

Application of AI in Cybersecurity Auditing

  • Deployment of AI for identification and mitigation of security incidents
  • Evaluation of AI-based cybersecurity control systems

Governance of AI Systems within IT Audit Contexts

  • Incorporation of AI into established IT governance structures
  • Responsibilities of IT auditors in overseeing AI governance

Anticipated Developments in AI and IT Auditing

  • Identification of emerging AI technologies influencing audit practices
  • Strategic preparation for the evolving landscape of AI in government IT auditing

Summary and Actionable Next Steps

Requirements

  • Foundational comprehension of information technology audit principles
  • Fundamental familiarity with artificial intelligence, machine learning methodologies, and data analytics applications

Audience

  • Information technology auditors
  • Specialists in artificial intelligence and data analysis
 14 Hours

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