Overview

AI is already being used in many organizations, both openly and behind the scenes. At the same time, new risks are emerging around traceability, control, and the reliability of results. For auditors, this raises a key question: how to work with AI in their own practice, and what to look for when encountering AI-supported processes or outputs. This 60-minute impulse session provides a structured, audit-focused perspective. It covers: * how AI can be used effectively in audit activities, * common risks and misconceptions, * and how to assess and challenge AI usage within audited functions. A specific focus is placed on recent developments such as agentic AI, where systems increasingly execute multi-step tasks autonomously. This shifts the audit focus from individual outputs toward system logic, governance, and control mechanisms. The session is followed by a 15 to 20 minute discussion to address questions and practical scenarios from participants’ own environments. Objective: provide orientation, a realistic assessment, and practical starting points for dealing with AI in auditing.

Date :06.07.2026

Time:12.00-13.00 Uhr (ca. 45 min presentation + ca. 15 min Q&A)

Language: English

CPE points: 1

Deadline to register: 1July

Trainer name: Judith Magono

Type of session (Online training/ In-Person Training / Webinar): Webinar

Who should attend?

Internal auditors of any level, compliance professionals, and governance or assurance practitioners who want a practical overview of the questions AI-enabled business processes raise for audit, oversight, and control functions.

Course description (1-h webinar)

* How AI can be used effectively in audit activities * Common risks and misconceptions * How to assess and challenge AI usage within audited functions

Trainer bio

Judith Magono brings an internal audit perspective shaped by years of experience in quality management, management systems, and operational assurance. As an auditor, consultant, and AI trainer, she focuses on how generative AI is changing business processes, documentation, decision preparation, and governance expectations. Coming from a management systems and operational control background rather than a traditional internal audit pathway, she offers a practical perspective on what assurance functions should pay attention to as AI becomes embedded in day-to-day