How Machine Learning is Disrupting Accounting

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Will Bible
Audit Partner
Deloitte
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In the accounting, audit, and compliance professions, Artificial Intelligence(AI) is already beginning to automate labor-intensive tasks, such as data entry or combing through manual documents.

For example, accounting and audit professionals may deploy AI to extract information from invoices or purchase orders to enter into accounting and auditing systems, freeing up hours in the day to perform more robust analytics on the outputs of the system. Taking advantage of AI could enable accounting, audit, and compliance departments to analyze significant amounts of data, and deliver more analysis and insight as a part of their roles.

In fact, AI has been making our lives easier for longer than we may realize. Your smartphone, your car, your bank, and the devices in your house may use AI on a daily basis to predict your preferences or anticipate your actions.

AI is the discipline of training machines to make human-like decisions and perform “smart” tasks that normally require human intelligence. The recent interest in AI has been fueled by a trifecta of advances in machine learning techniques, ever-increasing data availability and continued acceleration in computer processing. AI developers have created applications that can augment human performance, automate complex processes, and simulate human engagement to increasingly sophisticated levels.

Data is a big opportunity…and challenge for AI

AI is only as intelligent as the data that feeds it. To deliver on the potential of AI, machines “learn” from large repositories of information. The process of training a machine requires brute force computation – the equivalent of a teacher correcting students “yes” or “no” as they try to answer questions in rapid fire, until they have (almost) perfectly memorized all the answers to the questions. 

While data is empowering AI and machine learning at scale, getting access to quality data sets to solve specific business problems remains a huge challenge. Unstructured data – whether it’s text, images, or audio – must be digitized and transformed into a source of “ground truth” before AI-powered solutions can be created. This data wrangling exercise can be daunting for many organizations.

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