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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
Testimonials (3)
The trainer was helpful..
Attila - Lifial
Course - Compliance and the Management of Compliance Risk
The report and rules setup.
Jack - CFNOC- DND
Course - Micro Focus ArcSight ESM Advanced
Speed of response and communication