Why Choose AI for Internal Audit: Continuous Auditing and Control Testing Training Course?
Internal audit teams are expected to provide timely assurance across growing volumes of transactions, systems and business activity. Periodic testing and small samples remain useful, but they may miss patterns that emerge between audit cycles. Continuous auditing gives teams a way to examine selected controls and transactions more frequently, identify exceptions earlier and focus audit effort where it is most needed.
AI can support this work by helping auditors analyse large datasets, classify records, review documents and identify unusual activity. It can also assist with planning, drafting and summarising audit work. These capabilities require careful judgement: an unusual transaction is not necessarily a control failure, and an AI-generated conclusion cannot replace verified audit evidence. Auditors need to understand the data, validate results and maintain clear records of how findings were reached.
This AI for Internal Audit: Continuous Auditing and Control Testing training course shows participants how to design continuous auditing activities and apply AI to control testing across the audit lifecycle. It covers data preparation, test design, exception review, reporting and follow-up. Participants develop a continuous audit plan for a selected process and define the safeguards needed to use AI while preserving audit quality, confidentiality and professional judgement.
What are the Goals?
By the end of this course, participants will be able to:
- Identify audit activities and controls suitable for continuous testing.
- Define data requirements and assess the quality of available records.
- Design repeatable tests for transactions and key controls.
- Use AI to support document review, classification and exception analysis.
- Distinguish indicators of risk from verified audit findings.
- Validate AI-assisted results and maintain an evidence trail.
- Develop dashboards and alerts for ongoing audit monitoring.
- Apply confidentiality, access control and human review requirements.
- Build a phased plan for continuous auditing within an internal audit function.
Who is this Training Course for?
This training course is suitable to a wide range of professionals but will greatly benefit:
- Internal auditors and audit managers
- Heads of internal audit and assurance
- IT auditors and information systems auditors
- Risk and compliance professionals
- Internal control and governance specialists
- Data analysts supporting audit teams
- Professionals responsible for audit transformation
How will this Training Course be Presented?
The course combines instructor-led discussion, audit case studies and data-based exercises. Participants design control tests, review sample exceptions and assess where AI can assist without weakening audit evidence. Throughout the course, they develop a continuous audit plan for a selected business process.
The Course Content
- The role of continuous auditing within the audit plan
- Distinguishing continuous auditing from management monitoring
- Identifying processes and controls suitable for frequent testing
- Mapping risks, control objectives and available data
- Understanding AI applications across the audit lifecycle
- Defining audit ownership, independence and access requirements
- Assessing data availability and quality
- Selecting a process for a continuous audit pilot
- Translating control descriptions into testable rules
- Identifying required fields, sources and transaction populations
- Testing completeness, accuracy and consistency of audit data
- Designing tests for approvals, access, limits and segregation of duties
- Analysing duplicate, missing or unusual transactions
- Setting thresholds and determining test frequency
- Documenting test logic and expected results
- Reviewing false positives and refining test rules
- Using AI to classify transactions and supporting documents
- Extracting relevant information from contracts, invoices and records
- Identifying patterns and anomalies for further investigation
- Summarising large volumes of audit information
- Using AI to support risk assessment and audit planning
- Evaluating model outputs against known examples
- Recognising inaccurate, incomplete or unsupported AI responses
- Preserving auditor review and professional judgement
- Creating a workflow for reviewing and assigning exceptions
- Distinguishing data errors, legitimate variations and control failures
- Obtaining corroborating evidence for potential findings
- Recording test results, decisions and review history
- Establishing escalation criteria for significant issues
- Designing dashboards for trends, exceptions and control performance
- Communicating findings clearly to control owners
- Tracking management actions and repeat exceptions
- Prioritising controls for a phased implementation
- Defining responsibilities across audit, IT and process owners
- Establishing secure access and confidential data handling
- Managing changes to data sources, systems and test logic
- Monitoring test effectiveness and alert volumes
- Evaluating the value and limitations of AI-assisted audit work
- Presenting a continuous audit pilot plan
- Developing a 90-day implementation roadmap
Certificate
- AZTech Certificate of Completion for delegates who attend and complete the training course
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