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
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
The way to receive the information from the trainer