JUST what audit officials can do in the face of suspected frauds can be a problem, as often they have few ways of demonstrate it even if they feel that it shows tell-tale indicators.

That demands thinking up other ways of testing the reports or data involved, where the use of artificial intelligence enables an auditor to pose and obtain answers to questions that would otherwise take long to figure out and find supportive data or evidence.

AI does not create data or databases but enables one to access such databases to compare with the data at hand. That is why there is plenty of point in an affirmation issued at a professional forum lately that internal auditors can make greater use of AI for effective performance.

An expert said that AI will also be deployed to address cases of digital frauds hounding the financial sector, including auditing. It is indeed hard to say if there were feelings of pros and cons among 500 or so participants associated with the accounting profession at the event.

The issue is whether using AI will solidify the work in question in a positive direction or infringe upon the experts’ liberties. There could be conceivably preliminary issues on the manner in which AI can be used specifically in accounting as well as in other areas.

Part of this could relate to legislation on evidence, as bringing up artificially generated or furnished ‘evidence’ could raise queries. This implies that using AI can only help an auditor or an investigator make sense out of the data provided by either asking auxiliary questions or demanding relevant data in a different direction.

It is apparent that external auditors can use AI with greater ease as they can demand data or documentation at will, where it seems relevant. Internal audits are by comparison somewhat constrained, as their purpose is to assist higher administrators to figure out the propriety of accounts or  balance sheets, procurement reports or any settlements that need to be checked for propriety.

The use of AI usually arises from seeming insufficiency of data to satisfy someone on specific issues. When it comes to actually pushing issues beyond the factual sums or data presented by those responsible, the reasons for so wishing stem not just from concerns of the auditor but chiefly have to conform to or elicit the interest of management while being validated.

That is why the stress being directed at the deployment of AI as among steps envisaged in equipping the profession with the right work format, adequate resources and visible recognition is of considerable importance.

It heightens the leverage that internal auditors will have on checking probity or propriety in payments, procurement, etc., by putting to use tools that can amplify a line of reasoning or argument with instant furnishing of the relevant data.

It is as if internal auditors were confined to raw materials provided by company officials or agents for them to compile reports, while with AI they can furnish complementary data to boost assessments.