How can IT auditors develop and update their skills and competencies in AI and ML domains?

1 Understand the basics

Before diving into the technical details, it is important to have a clear understanding of the basic concepts and terminology of AI and ML, such as data, algorithms, models, training, testing, validation, accuracy, bias, explainability, and ethics. You can start by reading some introductory books, articles, or online courses on these topics, or by attending some webinars, workshops, or seminars offered by professional associations, academic institutions, or industry experts.

2 Learn the tools

To perform effective IT audits of AI and ML systems, you need to be familiar with the tools and platforms that are used to design, develop, deploy, and monitor them. These may include programming languages, frameworks, libraries, APIs, cloud services, and software applications. You can learn these tools by taking some online courses, watching some tutorials, or practicing some hands-on exercises or projects. You can also use some open-source or free tools to experiment with different AI and ML techniques and scenarios.

3 Follow the standards

As AI and ML systems become more widespread and critical, there is a growing need for standards and guidelines to ensure their quality, reliability, security, and compliance. IT auditors should be aware of the existing and emerging standards and best practices that apply to AI and ML systems, such as ISO, NIST, ISACA, IIA, COBIT, and others. You can keep up to date with these standards by reading some publications, reports, or white papers, or by joining some committees, working groups, or forums that are involved in developing or reviewing them.

4 Engage with the stakeholders

One of the key skills of IT auditors is to communicate effectively with the stakeholders of the IT systems they audit, such as the owners, users, developers, managers, regulators, and customers. This is especially important for AI and ML systems, as they may involve diverse and multidisciplinary teams, complex and dynamic processes, and sensitive and ethical issues. IT auditors should engage with the stakeholders of AI and ML systems to understand their needs, expectations, challenges, and feedback, and to share their findings, recommendations, and insights.

5 Update your knowledge

AI and ML are fast-evolving and innovative fields, with new developments, applications, and trends emerging every day. IT auditors should keep abreast of the latest news, research, and insights on AI and ML, and how they affect the IT audit profession and practice. You can update your knowledge by subscribing to some newsletters, blogs, podcasts, or magazines on AI and ML, or by attending some conferences, events, or webinars that showcase the latest advances and best practices in these domains.

6 Seek certification

One of the ways to demonstrate your skills and competencies in IT audit of AI and ML systems is to seek certification from a reputable organization or institution. Certification can help you validate your knowledge, enhance your credibility, and expand your network. There are various certification programs available for IT auditors who want to specialize in AI and ML, such as ISACA's Certified in Emerging Technology (CET), Certified in Artificial Intelligence (CAI), or Certified in Machine Learning (CML), or IIA's Artificial Intelligence Auditing Certificate (AIA).

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?