Internal Audit needs to leverage AI/GenAI to enhance assurance delivery by developing, prototyping, and integrating AI/GenAI tools into execution, strengthening and driving efficiency in audit delivery.
Requirements
- Strong understanding of AI and machine learning concepts, algorithms and techniques.
- Strong understanding of technical and system architecture, leading development of conceptual design and working with technical teams around solutioning.
- Strong knowledge of IT governance and control frameworks (e.g. COBIT, NIST, Cybersecurity Framework).
- Knowledge of MLOps principles and practices, including model deployment, monitoring, explainability, and lifecycle management.
- Familiarity with leading cloud-based AI/ML platforms and their associated governance, security, and deployment best practices.
- Understanding of security vulnerabilities and risks specific to AI/ML systems, including adversarial attacks and data privacy considerations.
- Familiarity with data governance principles, data quality management and data security practices.
Responsibilities
- Develop, prototype, and integrate AI/GenAI tools into execution.
- Identify, implement, and drive the adoption of specific AI-enabled assurance tests.
- Oversee prototyping and piloting of GenAI audit accelerators.
- Act as a design authority to ensure tool integrity, scalability and resilience in production.
- Lead the development of AI-enabled audit methods across prioritized domains.
- Pioneer and drive the adoption of continuous assurance approaches leveraging AI and GenAI capabilities.
- Partner with Learning & Development to design and deliver training on GenAI-enabled audit techniques, prompt engineering and AI methodologies.
Other
- Critical thinking will be essential in this role, enabling the individual to assess complex and ambiguous problems, identify risks and opportunities, and challenge assumptions constructively.
- Excellent executive communication skills to influence senior leaders and stakeholders.
- Ability to translate business needs into actionable technical solutions, bridging the gap between auditors, data scientist and technology teams.
- Act as a subject matter expert on complex AI topics, providing guidance and assurance to audit teams.
- Candidates should have a minimum of 15 years of diversified management experience in audit or a related role with a focus on technology and data.
