AI Transformation Services

Where the technology actually applies

Adoption fails most often not because a tool is poor but because it was applied to the wrong process. We begin with the work itself — which tasks are high volume and rule-bound, which depend on judgement, and which carry the exposure that makes automation risky — and identify where the technology earns its place.

Readiness assessment

Before any tool is selected, an entity needs to know whether its data will support one. We assess the condition of the underlying records, the consistency of master data, the points at which information is re-keyed between systems, and the controls that would have to change.

• Review of data quality, structure and accessibility across finance systems
• Process mapping to identify candidates for automation and augmentation
• Assessment of existing controls and where automation would displace them
• Evaluation of the skills and supervision the change would require

Controlled adoption

We work with management to introduce capability in defined stages, each with a stated objective and a means of verifying it worked, rather than through a single large implementation whose effects cannot be isolated.

• Automation of reconciliations, matching and exception identification
• Continuous, full-population testing in place of periodic sampling
• Document extraction and classification within accounts payable and receivable
• Anomaly detection across transaction populations

AI governance

A system that produces output management relies on is a system that requires governance. We help boards and management put in place the framework that makes reliance defensible.

• Policy on permitted and prohibited uses, and who authorises each
• Data protection and confidentiality obligations, including under the Digital Personal Data Protection Act, 2023
• Terms on which data leaves the entity’s control, examined before adoption rather than after
• Human review requirements, and the record kept of that review
• Model and vendor change management, so results remain explicable over time

Audit and assurance implications

Where automated procedures contribute to a conclusion, the working papers must still evidence the basis of that conclusion. We advise on the documentation an automated process has to produce in order to be relied upon, and on how existing controls should be re-designed around it.

What does not change

Judgement, professional scepticism and responsibility for the opinion remain with the qualified professional. A system can flag an anomaly; whether that anomaly is an error, a control failure or a legitimate exception is a matter of judgement informed by knowledge of the business.