Internal Auditing in AI-Driven Organizations

Introduction to Internal Auditing in AI-Driven Organizations

• Overview of Internal Auditing
  • Principles of internal auditing in modern organizations.
  • The evolving role of auditors in AI-driven environments.
• AI in Business Operations
  • Understanding AI technologies: Machine Learning, NLP, and Automation.
  • How AI is transforming decision-making and business models.
  • Key considerations for internal auditing in AI-powered firms.

Risks and Controls in AI Systems

• AI-Specific Risks
  • Data privacy and security risks in AI systems.
  • Model biases and ethical considerations in AI.
  • Operational risks due to automation and machine learning models.
• AI Control Frameworks
  • Developing internal controls for AI systems.
  • Risk mitigation strategies: Data governance, model validation, and transparency.

Auditing AI Governance and Compliance

• AI Governance Structures
  • Roles and responsibilities in AI governance.
  • Assessing AI model oversight, accountability, and decision-making.
• Compliance and Legal Frameworks
  • Overview of GDPR, AI-specific regulations, and ethical standards.
  • Evaluating adherence to AI compliance requirements and best practices.

Conducting AI Audits and Reporting

• AI Audit Methodology
  • Planning and executing an AI audit: Key steps.
  • Tools and techniques for assessing AI systems and data workflows.
• Audit Reporting and Recommendations
  • Structuring audit reports for AI-driven organizations.
  • Communicating findings, risks, and recommendations to stakeholders.
  • Best practices for continuous monitoring and improvement.

1ST BATCH: Tuesday, February 17, 2026 — Friday, February 20, 2026.

2ND BATCH: Tuesday, June 9, 2026 — Friday, June 12, 2026.

3RD BATCH: Tuesday, October 6, 2026 — Friday, October 9, 2026.

The training methodology integrates lectures, interactive discussions, collaborative group exercises, and
illustrative examples. Participants will acquire a blend of theoretical insights and hands-on practical
experience, emphasizing the application of learned techniques. This approach ensures that attendees return
to their professional environments equipped with both the competence and self-assurance to effectively
implement the acquired skills in their responsibilities.