Senior Manager, Intelligent Audit Transformation

JOB DESCRIPTION:

Lead the overall Intelligent Audit Transformation of GIA by establishing a clear strategic direction, target operating model and implementation roadmap that align with GIA's audit strategy and evolving business risks.

Strategic Intelligent Audit Planning & Architecture Design

• Develop and maintain the Intelligent Audit Transformation roadmap, defining priorities, key initiatives, milestones, resource requirements and success measures.
• Define the target operating model and capability architecture for Digital Audit, automation, AI-enabled auditing and progressively Continuous Assurance.
• Assess emerging technologies and identify high-value and practical use cases for Internal Audit, prioritizing initiatives based on risk impact, feasibility and expected value.
• Establish appropriate governance, standards and performance measures to monitor transformation progress and ensure sustainable implementation.

Digital Audit Methodology, Data & Technology Enablement

Lead the integration of digital technologies, data analytics and automation across the end-to-end audit lifecycle to strengthen audit quality, efficiency, consistency and risk coverage.

• Integrate data analytics, automated testing, workflow automation and digital tools into risk assessment, audit planning, fieldwork, evidence analysis and reporting.
• Translate audit risks, objectives and procedures into scalable data analytics and automated testing approaches, with greater use of full-population testing where appropriate.
• Collaborate with IT, business functions and audit teams to establish reliable data access, governance, quality standards and reusable audit data assets across key ERP and business systems.
• Develop and standardize reusable digital audit tools, solutions and methodologies that can be applied across audit engagements and business areas.
• Continuously assess and enhance the effectiveness, reliability and scalability of digital audit solutions and embed them into standard audit practices.

AI-Powered Risk Analytics & Continuous Assurance

Lead the development of data-driven and AI-enabled risk monitoring and assurance capabilities to improve risk visibility, identify emerging risks earlier and progressively advance GIA towards Continuous Auditing and Continuous Assurance.

• Develop key risk indicators, automated testing rules, anomaly and exception detection, and risk-trigger mechanisms for priority risk areas.
• Build capabilities for continuous risk monitoring and risk-based alerts using available system and business data.
• Establish processes to validate, prioritize and follow up on risk signals and exceptions to ensure they are reliable, actionable and appropriately addressed.
• Develop mechanisms to convert significant risk signals into audit reviews, investigations or management follow-up actions.
• Expand Continuous Monitoring, Continuous Auditing and Continuous Assurance to suitable areas based on data availability, risk characteristics and control maturity.

AI Enablement, Change Management & Capability Building

Drive the adoption of AI-enabled and technology-driven ways of working across GIA by strengthening digital capabilities and enabling auditors to use technology effectively while maintaining professional judgement and audit quality.

• Identify, develop and institutionalize practical AI applications and AI agents to support audit planning, testing, evidence analysis, report review, knowledge retrieval and other audit activities.
• Develop LLM/RAG-based audit knowledge solutions and intelligent workflows to improve access to audit methodologies, standards, historical knowledge and professional guidance.
• Establish appropriate AI governance, usage guidelines and quality controls to ensure responsible AI adoption with adequate human oversight and professional judgement.
• Develop and deliver training, coaching, guidance and reusable tools to strengthen auditors digital, data analytics and AI capabilities.
• Lead adoption and change management initiatives to embed data-driven, technology-enabled and AI-augmented ways of working into GIA's audit culture and operating model.

REQUIREMENTS:

• Bachelor's Degree in Accounting, Finance, Information Technology, Computer Science, Data Analytics, Business, Risk Management or a related discipline.
• Total Work Experience: Minimum 8 years
• Total Relevant Experience: Minimum 5 years in Internal Audit, Risk Management, Risk Advisory, Digital Audit or related fields, with demonstrated experience in digital transformation, data analytics, automation or AI-enabled audit initiatives.
• Proven experience in leading or managing digital audit, audit transformation, data analytics, automation or AI-enabled audit initiatives from strategy/design through implementation and adoption.
• Experience working with ERP and enterprise business systems (e.g. SAP) and cross-functional stakeholders such as IT, Finance, Operations and business functions is preferred.
• Experience in manufacturing, automotive, supply chain or other complex multinational business environments would be an advantage.
• Prior experience in a Big Four, leading professional services firm, or large corporate Internal Audit / Risk function is preferred.

Essential

• Strong knowledge of Internal Audit, risk management, internal controls and risk-based audit methodology.
• Strong understanding of Digital Audit, Data Analytics, automated audit testing and technology-enabled audit methodologies.
• Practical understanding of AI/GenAI, AI Agents, LLM/RAG, intelligent automation and their applications in Internal Audit and risk management.
• Ability to translate audit risks and business requirements into data-driven, automated or AI-enabled audit solutions.
• Strong understanding of data governance, data quality, data access and enterprise data architecture from an audit and business-user perspective.
• Proven project leadership, stakeholder management and change management skills.
• A person of integrity and possess strong critical thinking, analytical, problem-solving and communication skills, with the ability to communicate effectively with senior management and stakeholders.
• Ability to balance technology opportunities, audit objectives, risk considerations and professional judgment, rather than relying solely on technology outputs.
• Comfortable with working in information-heavy environment and willing to work under pressure.

Preferred / Advantageous

• CIA, CISA, ACCA, CPA or equivalent professional qualification.
• Additional qualifications or certifications in Data Analytics, AI, Digital Transformation, Technology Risk or related areas.
• Experience with Power BI, SQL, Python, process mining, RPA or audit analytics platforms.
• Experience designing or implementing Continuous Monitoring, Continuous Auditing or Continuous Assurance solutions.
• Experience developing AI Agents, LLM/RAG-based knowledge solutions or AI-enabled audit workflows.
• Familiarity with major ERP/business systems, particularly SAP, and experience working with large and complex datasets.