Webinars On-Demand

Ethics series Topic 2  "Ethics & AI: When Smart Tools Meet Sound Judgment"

Overview 

AI is transforming the way accountants work, offering powerful tools for analysis, reporting, and decision-making, but with these benefits come significant ethical responsibilities. Accountants must ensure that integrity, confidentiality, professional judgment, and public trust remain central in an environment where automation and machine learning increasingly influence outcomes. The International Federation of Accountants (IFAC) Code of Ethics provides a vital framework for navigating these challenges, helping professionals balance innovation with accountability. 

Join Caryn Maitland CA(SA) as she unpacks how accountants can apply ethical principles when integrating AI tools into practice, preserving the profession’s credibility while embracing technological change. 

Learning objectives 

Attending this webinar will equip you with the following skills:  

• Learn how to apply the IFAC Code’s Fundamental Principles (integrity, objectivity, professional competence and due care, confidentiality, and professional behavior) when working with AI. 

• Understand the limits of professional competence when delegating or relying on AI-driven outputs. 

• Explore ethical issues including bias, privacy risks, data security, and accountability when using AI platforms. 

• Develop practical guidelines for using AI responsibly in audits, tax work, financial reporting, and advisory services. 

• Reflect on how accountants can preserve human judgment and ethical responsibility in a machine-assisted profession 

Content 

The webinar will cover the following topics:   

• Introduction to AI in Accounting 

  • Current applications: drafting, data analysis, risk assessment, advisory support 

  • Benefits vs risks: efficiency, accuracy, accountability 

• Ethical Framework: The IFAC Code 

  • Integrity: ensuring truth and fairness in AI-assisted work 

  • Objectivity: guarding against bias and undue influence from automated outputs 

  • Professional competence & due care: understanding limits of AI reliance 

  • Confidentiality: protecting client and firm data when using third-party tools 

  • Professional behavior: reputation, credibility, and compliance with laws 

• Key Ethical Questions 

  • Who is accountable for AI-generated errors? 

  • Can client-sensitive data be shared with third-party AI platforms? 

  • How do we ensure AI does not compromise independence or objectivity? 

  • Attribution: when and how should reliance on AI be disclosed? 

• Practical Scenarios & Case Studies 

  • AI use in audits: risk flagging, substantive testing, and fraud detection 

  • AI in tax: drafting opinions, preparing returns, and compliance risks 

  • AI in advisory: modelling, valuations, and decision-making support 

  • Real-world dilemmas: data leaks, bias, over-reliance on automation 

• Developing Ethical AI Guidelines 

  • Establishing firm-level policies 

  • Educating staff and clients on AI limitations 

  • Monitoring and review of AI-generated work 

  • Balancing innovation with ethical responsibility 

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