Audit Tips

AI is not a technology of the future, it’s everywhere already

Every day, announcements are made about the use of AI in new areas. For example:

• self-driving cars
• online search engines
• customized online purchases
• product customization by news and entertainment companies
• government weather forecasts
• virtual assistants on personal devices.

Many of these AI-driven innovations are now familiar to many consumers and are becoming run-of-the-mill technologies in various industries, while others are still in their infancy and very far from being proven, mainstream technologies. Auditors should stay informed of new AI developments and follow the adoption of AI applications in the public sector.

AI is not one but many technologies

AI capabilities have diversified in recent years and can now be applied to various tasks. They encompass diverse technologies such as robotics, expert systems, natural language processing and predictive analytics. The most promising technologies for auditors are image recognition, speech recognition, and machine learning.

Image recognition can automate many tedious audit tasks

Image recognition is possible because AI can process video and digital images mathematically and identify patterns emerging from the data. It can do inventory counts using a video camera attached to drones, identify and locate items, and even report on their condition. Such video analytics can be performed very efficiently, reviewing hours of recordings in a few minutes.

Speech recognition will change the way auditors do interviews

Speech recognition aims to leverage streamed or recorded audio such as voice mails, phone calls, conference calls, interviews, management presentations, and recording of management or board of directors’ meetings. Speech recognition software “understands” and analyzes grammatical and semantical language structures, taking into account accents, errors, and background noise. A promising audit application is the ability to accurately transcribe verbal recordings of interviews and testimonies, thus efficiently generating reliable transcripts of conference calls or interviews.

Machine learning can magnify the analytical capacity of auditors

Machine learning uses algorithmic models to perform complex data analysis on large datasets without specific instructions. It is programmed to iteratively process the data and build mathematical models, in order to identify patterns and make predictions. Applications using this technology are emerging in the audit profession. For example, software that can read complex contracts, identify key terms, and correlate with transactions could identify patterns and instances of non-compliance.

Auditors need to upgrade their skills to master AI

To audit and use AI, auditors will need the technical knowledge and tools to assess this technology and its impact on the economy, efficiency, and effectiveness of auditees. Therefore, auditors will have to hone and perfect skills they already have while acquiring new ones. The most relevant skills needed are:

• Understanding the strengths and limitations of AI technology. For example, it will be necessary to grasp the ramification of AI applications on an auditee’s operations.
• Understanding and integrating data. AI will magnify the need for the audit skills required to perform data analytics.
• Performing reasoned analysis. The gradual automation of mechanical tasks will allow humans to focus on analysis – this will highlight the human capacity to sift information intuitively.

AI can be biased

AI is based on code and is bound to reflect and even amplify the biases of coders. Concerns about AI biases are both a risk to auditees and a constraint on the use of AI in audits. Therefore, auditors could provide an essential safeguard against the negative effects of these biases by being wary of their impact on their work. To make the identification of bias easier, efforts are ongoing to try to identify, trace, and document the decision-making process of AI using deep learning – this will create an audit trail that can be reviewed and analyzed.

AI will not replace auditors, but it will make them more effective

AI shines especially well when undertaking tedious tasks. The audit profession entails a number of “low-hanging fruits” in this respect: contract reviews, inventories, compliance reviews of transactions, and so on. AI can do all that better than humans. It is faster, efficient, and accurate, and can often review 100% of transactions (as opposed to only testing a sample). This can enhance and extend the role of humans, not eliminate it, because it will free auditors to focus on value-added tasks. Humans are still better than computers at telling the story behind the data and at making qualitative judgments that add value for auditees.