Professional training in London and 13 international cities info@llmi.uk
Enquire

Professional training course · AF-015

AI for Internal Audit: Continuous Auditing and Control Testing

Internal audit functions are increasingly expected to provide timely assurance over complex business processes, digital transactions, financial controls, and emerging…

  • 5 daysClassroom
  • 13Upcoming dates
  • 6Cities
  • £2,840Fees from
View dates & register Get quotation Download PDF
AI for Internal Audit: Continuous Auditing and Control Testing
Next classroom session Barcelona 14 - 18 Dec 2026 · £3,850 Also available Istanbul 18 - 22 Jan 2027 · £2,850

Course overview

Why Attend

Internal audit functions are increasingly expected to provide timely assurance over complex business processes, digital transactions, financial controls, and emerging risks. Traditional audit approaches based on periodic reviews and limited transaction samples may fail to identify control failures, unusual activities, and emerging risk patterns early enough for effective management action.

The AI for Internal Audit: Continuous Auditing and Control Testing course develops practical capabilities for applying artificial intelligence, machine learning, process mining, data analytics, and intelligent automation to internal audit activities. Participants learn how to analyze complete transaction populations, develop continuous auditing routines, identify control exceptions, evaluate anomalies, and use AI-assisted techniques to strengthen audit planning, fieldwork, reporting, and follow-up.

The programme emphasizes practical applications across finance, procurement, payroll, inventory, and enterprise systems while addressing data quality, false positives, explainability, confidentiality, and the professional judgment required when using AI-generated audit evidence.

Professional Problems This Course Is Designed to Solve

  • Delayed identification of control failures: Using continuous auditing and automated testing to detect unusual transactions, policy violations, and control exceptions between scheduled audit engagements.

  • Limited audit coverage: Moving beyond small transaction samples by applying data analytics to complete populations of financial and operational records.

  • Manual and repetitive control testing: Reducing time spent extracting data, reconciling records, checking approvals, and identifying exceptions through repeatable analytical procedures.

  • Difficulty detecting sophisticated anomalies: Applying statistical analysis and machine learning to identify unusual patterns, duplicate payments, suspicious transactions, and potential control weaknesses.

  • Fragmented audit data: Combining information from ERP systems, financial applications, procurement platforms, payroll systems, and operational databases for more effective assurance.

  • Unreliable AI-generated audit findings: Managing false positives, incomplete data, model limitations, unsupported conclusions, and insufficient audit evidence.

  • Weak follow-up on control deficiencies: Developing dashboards, exception management workflows, and continuous monitoring indicators that support timely remediation and management accountability.

Course Methodology

The programme combines instructor-led technical sessions, audit analytics demonstrations, realistic transaction datasets, control-testing workshops, AI-assisted audit exercises, case studies, and practical simulations. Participants explore workflows using Excel, Power BI, SQL, Python-based analytical techniques, and generative AI assistants where appropriate.

Exercises focus on audit objectives, data requirements, testing logic, exception analysis, evidence validation, and the communication of audit findings. Participants progressively develop a continuous auditing framework and an AI-supported control-testing approach for selected business processes.

Course Objectives

By the end of this course, participants will be able to:

  • Understand the applications and limitations of AI in internal auditing

  • Distinguish continuous auditing from continuous monitoring and periodic assurance

  • Identify business processes suitable for automated control testing

  • Extract, prepare, and validate data from financial and operational systems

  • Develop analytical tests for key financial and operational controls

  • Apply anomaly detection techniques to identify unusual transactions and potential control failures

  • Use process mining concepts to examine workflow deviations and control effectiveness

  • Apply generative AI to selected audit planning, documentation, and reporting activities

  • Design dashboards and exception reporting mechanisms for continuous auditing

  • Evaluate AI-generated results and maintain sufficient, reliable audit evidence

  • Address privacy, cybersecurity, model risk, and governance considerations

  • Develop an implementation roadmap for AI-enabled continuous auditing

Target Audience

This course is suitable for:

  • Internal auditors and senior internal auditors

  • Internal audit managers and heads of internal audit

  • IT auditors and information systems auditors

  • Risk management and compliance professionals

  • Internal control specialists

  • Fraud examination and investigation professionals

  • Financial controllers and assurance professionals

  • Audit analytics and business intelligence specialists

  • Governance, risk, and compliance managers

  • Professionals responsible for continuous auditing and control monitoring

Target Competencies

Participants will develop competencies in:

  • AI-enabled internal auditing

  • Continuous auditing

  • Automated control testing

  • Audit data analytics

  • Transaction anomaly detection

  • Process mining

  • Risk-based audit analytics

  • Audit evidence validation

  • Continuous assurance dashboards

  • AI governance and audit quality

Course outline

  1. 1Day 1: AI-Enabled Internal Auditing and Continuous Assurance

    • Examining how artificial intelligence, machine learning, generative AI, and data analytics support risk-based internal audit activities

    • Distinguishing continuous auditing, continuous controls monitoring, and conventional periodic audit engagements

    • Identifying opportunities for AI-assisted assurance across financial reporting, procurement, payroll, inventory, and operational processes

    • Mapping business risks to key controls, audit assertions, transaction data, and measurable control-testing criteria

    • Evaluating data availability, system access, audit trails, data quality, and technology readiness for continuous auditing

    • Practical exercise: Developing a continuous auditing use-case map linking audit risks, key controls, required datasets, and expected assurance outcomes

  2. 2Day 2: Audit Data Preparation and Automated Control Testing

    • Extracting and combining audit data from ERP applications, accounting systems, procurement records, payroll databases, and transaction logs

    • Preparing audit datasets using SQL, Excel, and Power Query to address duplicates, missing values, inconsistent formats, and incomplete records

    • Designing automated tests for approval limits, segregation of duties, duplicate payments, unauthorized transactions, and policy compliance

    • Applying full-population testing, reconciliation procedures, rule-based analysis, and exception identification to financial and operational controls

    • Establishing repeatable testing workflows with documented logic, data validation checks, and traceable audit evidence

    • Practical workshop: Building automated control tests for accounts payable and procurement transactions, including exception identification and supporting evidence

  3. 3Day 3: Machine Learning, Anomaly Detection and Process Mining

    • Understanding supervised and unsupervised machine learning applications for audit risk identification and transaction analysis

    • Applying statistical outlier detection, clustering concepts, and pattern analysis to identify unusual financial and operational activity

    • Investigating duplicate vendors, abnormal payment behaviour, unusual journal entries, transaction splitting, and potential fraud indicators

    • Using process mining concepts to analyze event logs, identify process deviations, and examine approval and authorization workflows

    • Evaluating model outputs through false-positive analysis, explainability, validation, and professional assessment of potential control failures

    • Case study: Analyzing a procurement transaction dataset to identify anomalies, investigate exceptions, and distinguish control weaknesses from legitimate business activity

  4. 4Day 4: Continuous Auditing Dashboards and AI-Assisted Audit Workflows

    • Designing continuous auditing routines with defined testing frequency, data refresh requirements, control thresholds, and exception escalation procedures

    • Developing Power BI dashboards to monitor control exceptions, transaction anomalies, risk indicators, and remediation status

    • Establishing risk-based alert thresholds and exception prioritization methods to reduce unnecessary investigations

    • Applying generative AI to audit planning, risk-control matrix development, working-paper summaries, and draft audit observations

    • Integrating analytical results into audit management workflows while maintaining reviewer approval, evidence traceability, and appropriate access controls

    • Practical workshop: Creating a continuous control-testing dashboard and exception management workflow for a selected financial or operational process

  5. 5Day 5: AI Audit Governance, Assurance Quality and Implementation

    • Assessing AI-related audit risks involving data confidentiality, access permissions, algorithmic bias, model reliability, and cybersecurity

    • Establishing validation procedures for AI-generated findings, analytical models, automated tests, and supporting audit evidence

    • Defining responsibilities between internal audit, IT, data owners, compliance teams, and management for continuous auditing operations

    • Measuring continuous auditing effectiveness through control coverage, exception resolution time, testing efficiency, detection timeliness, and remediation performance

    • Developing a phased implementation roadmap covering use-case selection, technology requirements, staff capabilities, pilot testing, governance, and operational deployment

    • Capstone exercise: Designing and presenting an AI-Enabled Continuous Auditing and Control Testing Framework covering risk assessment, automated tests, anomaly detection, reporting dashboards, evidence validation, and implementation priorities

Schedule

Dates and fees

13 upcoming dates in 6 cities. Fees are per delegate; bring colleagues and every seat is discounted.

All dates as PDF
December 2026
14DEC 14 - 18 Dec 2026Mon to Fri · 5 daysNext session
Spain flag BarcelonaSpain · Classroom
£3,850per delegate2+ people: £3,080 each
Register
January 2027
18JAN 18 - 22 Jan 2027Mon to Fri · 5 days
Turkey flag IstanbulTurkey · Classroom
£2,850per delegate2+ people: £2,280 each
Register
February 2027
15FEB 15 - 19 Feb 2027Mon to Fri · 5 days
South Africa flag Cape TownSouth Africa · Classroom
£2,840per delegate2+ people: £2,272 each
Register
March 2027
15MAR 15 - 19 Mar 2027Mon to Fri · 5 days
Spain flag BarcelonaSpain · Classroom
£3,850per delegate2+ people: £3,080 each
Register
April 2027
19APR 19 - 23 Apr 2027Mon to Fri · 5 days
France flag ParisFrance · Classroom
£4,500per delegate2+ people: £3,600 each
Register
May 2027
17MAY 17 - 21 May 2027Mon to Fri · 5 days
Germany flag FrankfurtGermany · Classroom
£3,250per delegate2+ people: £2,600 each
Register
June 2027
21JUN 21 - 25 Jun 2027Mon to Fri · 5 days
Spain flag BarcelonaSpain · Classroom
£3,850per delegate2+ people: £3,080 each
Register
July 2027
19JUL 19 - 23 Jul 2027Mon to Fri · 5 days
Spain flag BarcelonaSpain · Classroom
£3,850per delegate2+ people: £3,080 each
Register
August 2027
16AUG 16 - 20 Aug 2027Mon to Fri · 5 days
Turkey flag IstanbulTurkey · Classroom
£2,850per delegate2+ people: £2,280 each
Register
September 2027
20SEP 20 - 24 Sep 2027Mon to Fri · 5 days
Austria flag ViennaAustria · Classroom
£4,250per delegate2+ people: £3,400 each
Register
October 2027
18OCT 18 - 22 Oct 2027Mon to Fri · 5 days
Spain flag BarcelonaSpain · Classroom
£3,850per delegate2+ people: £3,080 each
Register
November 2027
15NOV 15 - 19 Nov 2027Mon to Fri · 5 days
France flag ParisFrance · Classroom
£4,500per delegate2+ people: £3,600 each
Register
December 2027
20DEC 20 - 24 Dec 2027Mon to Fri · 5 days
Germany flag FrankfurtGermany · Classroom
£3,250per delegate2+ people: £2,600 each
Register

Questions

Frequently asked questions

How long is the AI for Internal Audit: Continuous Auditing and Control Testing course?

The course runs over 5 days of classroom training, usually Monday to Friday.

When is the next AI for Internal Audit: Continuous Auditing and Control Testing course?

The next public date is 14 - 18 Dec 2026 in Barcelona. There are 13 upcoming dates in total.

Where is this course held?

Upcoming sessions run in Barcelona, Istanbul, Cape Town, Paris, Frankfurt, Vienna.

How much does the course cost?

Fees start from £2,840 per delegate, depending on the city. Fees include tuition and course materials.

Do participants receive a certificate?

Yes. Delegates who complete the course receive a London Leadership Management Innovation certificate of completion.

Can this course be delivered in-house for our team?

Yes. LLMI can tailor and deliver this course privately for your organisation at your premises or in one of our training cities.

Course information last updated 14 November 2026.

Related

More Accounting and Finance courses

View all

Training a team?

Any course in our catalogue can be delivered privately for your organisation, at your offices or in one of our cities, with content shaped around your goals.

Plan in-house training Speak to an advisor