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The mass adoption of AI tools has only recently gained momentum, so learning how to use AI efficiently, effectively and – most importantly – responsibly will provide Internal auditors with a powerful tool capable of not only supporting their role but enhancing how they work, and ultimately help organisations strengthen their control environment.
AI tools have stood out through their ability to understand, interpret, and generate language, allowing them to not only analyse large amounts of varied information, but also interpret written or spoken instructions. This sophistication, combined with their broad accessibility, creates many opportunities to misuse its benefits, but also brings with it additional risks that must be managed.
The use of data has revolutionised internal audit. What used to require onerous testing of a minute sample, can now cover an entire population through data analytics. AI adds additional dimensions through its ability to rapidly conceptualise and analyse both quantitative and qualitative information. This gives it an edge in diverse datasets such as spreadsheets or surveys. Large language models efficiently summarise complex information, answer queries, and identify insights – sometimes beyond human capability – in a fraction of the time.
Internal auditors are relied upon to understand and recommend better practice controls. As technology keeps developing, practitioners must be at the forefront of what is available. This includes incorporating AI solutions that may aid in enhancing the control environment. AI is being used to continuously monitor and detect internal and external threats such as fraud and cyberattacks where unusual patterns and anomalies may be present.
Some organisations are promoting compliance through the development of policy chatbots that allow staff to query key policy areas and obtain answers quickly. Other onerous and time-consuming compliance processes are also being streamlined through the automation of reporting.
With the rapid change, Internal auditors will need to quickly understand AI to ensure they are able to review and assess if these controls are working effectively.
Developing relevant audit plans and scopes are a critical element of an internal auditor’s role; AI is a key tool that can be used to inform this process. Machine learning can draw upon a wealth of external information that allows internal auditors to be abreast of emerging risks and issues. AI tools can be used to analyse internal company information, such as financials, to provide insights into the overall health of the organisation as well as identify areas for more targeted reviews and assurance.
The ease of use and accessibility of AI along with its ability to provide seemingly high-quality outputs can make it tempting to rely on. However, it is important to keep the limitations of AI in mind, in particular its ability to output incorrect information. A core tenet of the role of an internal auditor is the need to exercise a healthy level of scepticism – the same principles apply to AI, which must be rigorously verified as to its accuracy.
Large language models are constantly being taught only from the information it receives. Therefore, users must be aware they lose control of the data once it is placed into an AI. There have also been reports of AIs being queried in ways to divulge sensitive information about a person or a company.
Withstanding what all the above tools offer, an opportunity for all professionals, including internal auditors, to enhance the value of what we do. While we should be careful, we must also think about the positive outcomes when exploring what is available. This means having the courage to embrace this largely unfamiliar technology and put in place the right controls to prevent yourself and the company from its negative impacts.
AI and machine learning tools are ever-evolving – therefore, it’s critical for risk professionals to stay aware of these changes and how they can impact the industry and greater business environment.
