A new world unfolding: Evaluating the importance of artificial intelligence in information systems auditing

IT is no doubt that a new world is unfolding right in front of our eyes, with artificial intelligence (AI) revolutionising the way we see the world.

However, years of science fiction movies (my favourite is the Terminator franchise) created divisions on whether humanity is better off with AI or otherwise.

It is however not my objective to start an age-old argument, but rather, to situate were I see AI making a difference in my trade of information systems auditing.

Specifically, in this instalment, I will primarily focus on the significance of AI in information systems auditing and how it has transformed traditional auditing practices.

A disclaimer: This is not comprehensive, but rather, it is a conversation starter, and an attempt to show some of the potential benefits of AI.

Enhanced data analytics

It is no secret that most organisations globally rely on large datasets throughout the production cycle, with some even focusing mainly on harvesting, organising and selling big data.

One of the primary benefits of AI, therefore, is its ability to process and analyse large volumes of data with speed and accuracy.

AI-powered tools can sift through vast datasets to identify patterns, anomalies, and potential risks, enabling auditors to gain comprehensive insights into the organisation’s operations.

This enhanced data analytics capability allows auditors to make more informed decisions and provide valuable recommendations to improve internal controls and operational efficiency.

Illustrations of these include natural language processing (NLP) tools which are used to analyse and understand unstructured data, such as audit reports, emails, and textual data from system logs.

NLP techniques, including text mining, sentiment analysis, and topic modelling, help auditors extract insights, identify patterns, and assess the tone and context of communication within an organisation.

Real-time monitoring and risk assessment

AI facilitates real-time monitoring of transactions, activities, and system logs, enabling auditors to proactively identify irregularities or potential fraud.

Through machine learning algorithms, AI can continuously assess risks and flag unusual activities, thereby minimising the likelihood of fraudulent behaviour going undetected. This real-time risk assessment empowers organisations to mitigate potential threats promptly and uphold the integrity of their information systems.

By analysing historical data, AI tools can identify risk factors, predict future risks, and prioritise audit efforts accordingly.

This enables auditors to focus on high-risk areas and allocate resources more effectively, improving the overall efficiency of the auditing process.

Predictive analysis for future trends

By leveraging AI, auditors can harness the power of predictive analysis to anticipate future trends and risks within the organisation’s information systems.

Machine learning algorithms can analyse historical data to forecast potential vulnerabilities, compliance issues, or operational inefficiencies.

This proactive approach enables auditors to address potential challenges pre-emptively and implement strategies to fortify the organisation’s information systems against emerging threats, this includes predictive analytics tools.

Automation of routine tasks

AI has the capability to automate routine auditing tasks, such as data extraction, validation, and report generation. This automation liberates auditors from repetitive manual tasks, allowing them to focus on more strategic and valueadded activities.

Furthermore, AI-driven automation minimises the margin for human error, ensuring greater accuracy and consistency in auditing processes.

Examples of such systems include robotic process automation tools which automate repetitive tasks, such as data extraction, data validation, and report generation.

Continuous monitoring and compliance adherence

Traditional auditing methods often involve periodic assessments, leaving gaps in identifying risks and non-compliance between audit cycles.

AI facilitates continuous monitoring of information systems, enabling auditors to maintain a real-time understanding of the organisation’s adherence to regulatory requirements and internal policies.

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Lorraine Candice Chakuzira is an information systems auditor and writes in her personal capacity. She can be contacted on http:// linkedin.com/in/lorraine-candicechakuzira-09626a149. She writes here in his personal capacity.