What Accountants Need to Know


Artificial Intelligence (Al) is transforming how we live and work. Intelligent virtual assistants on smartphones (e.g., Siri on Apple devices), facial recognition software on social media platforms (e.g., Facebook), and self-driving autonomous vehicles (e.g., Tesla) all utilize Al. Hospitals used Al in the battle against Covid-19. For example, Tampa General Hospital in Florida has deployed an Al system that performs facial thermal scans on patients entering the building to detect potential coronavirus symptoms such as sweat, discoloration, and fever (Wittbold et al., 2020). The convergence of big data analytics, advances in computing power, the Internet of Things (loT), and large scale investment by governments, universities, and high-tech organizations such as Google, Amazon, Microsoft, and IBM have accelerated the adoption of Al for consumers and businesses.

These cases are just a few examples of the digital transformation we are currently experiencing, an era described by Klaus Schwab, founder and executive chairman of the World Economic Forum, as “The Fourth Industrial Revolution”. Schwab notes that the current revolution is distinct from the previous three due to the velocity of technological change, the breadth and depth of these technologies, and its impact on entire systems (i.e„ countries, companies, industries, and society as a whole) (Schwab, 2017). Al is one of the key technologies driving this digital revolution.

So, what exactly is Al? Artificial intelligence is a computer program or software application that can imitate or simulate human behavior. Al applications are expected to automate a significant portion of the repetitive tasks performed by accountants, though the implications of this change for the accounting profession has divided scholars. Some critics speculate that sufficiently sophisticated Al will eliminate the need for accountants in the future. Others predict that the accounting profession will experience increased productivity and cost savings by incorporating Al technology. What is evident on both sides is that Al will have a significant impact on the accounting profession in the coming decades. As we will discuss throughout this book, and in more detail in Chapter 7, our view is that Al will not eliminate the need for accountants but empower them to deliver more accurate, timely, and forward-looking insights into the business(es). As part of the impending transformation of the profession, accountants will need to develop the skills necessary to provide mission-critical judgment and oversight of Al-enabled systems and processes in order for organizations to realize productivity gains and meet other objectives expected from Al. The purpose of this book is to provide accountants with a practical guide for identifying opportunities to implement artificial intelligence (Al) initiatives to increase productivity and profitability.

History of AI

Given the recent widespread media coverage on Al, the field of Al may seem like a new discipline. However, the roots of Al’s can be traced back to 1943 when neurophysiologist Warren McCulloch and logic expert Walter Pitts proposed the first model of artificial neurons (Russell & Norvig, 2010). The field of Al was established as an academic and research discipline when the first Al conference was organized at Dartmouth College in 1956 (Bringsjord & Govindarajulu, 2018). Today, Al is an interdisciplinary field of science, engineering, statistics, philosophy, neuroscience, psychology, computer engineering, and others.

History of Accountants Using Technology

Technology has always played an important role in accounting for business transactions through the ages - from the use of an abacus over 2,000 years ago (New York State Society of CPAs, 2015), to the purchase of a computer in 1955 exclusively for accounting purposes (Untapped Editorial Team, 2018), to the creation of electronic spreadsheets in the 1980s (Pepe, 2011). Al is the next significant technological advancement that will play an essential role in the accounting profession for years to come.

Overview of How Accountants Are Using AI

Accountants currently use Al in a variety of applications, from identifying high-risk transactions in audits to performing accounts payable processing tasks. As a result, Al is increasingly taking the place of human processing and decision-making, which will continue to have a transformative impact on business practices. Although Al adoption in the accounting profession is in its early stages, practitioners must understand the implications of this technology.

The adoption of Al has been on a steady rise in both public and corporate accounting. For example, EY1 uses Al drones to perform inventory counts with increased accuracy and efficiency. Deloitte2 uses a tool called “Argus” to extract critical accounting information from any type of electronic document to improve the quality and efficiency of an audit (Deloitte, 2015). In management accounting, Al is used to automatically code accounting entries, forecast revenues, and analyze unstructured data such as contracts and emails (ICAEW, 2017).

Going forward, it is even more exciting to think about how Al will be used in accounting. Imagine if you could ask an intelligent virtual assistant (such as Alexa or Siri) to analyze accounts payable for duplicate payments as part of your audit procedures. Technological advances in artificial intelligence could make this possible very soon. Researchers Burns and Igou (2019) suggest that accountants should consider using intelligent virtual assistants to interface with Al applications to perform audit analysis, data retrieval, spreadsheet creation, and data visualizations - all activated by human commands.

Human Intelligence versus Artificial Intelligence

For more than 2,000 years, philosophers have pondered questions such as “how does the human mind work?” and “can non-humans have minds?” (Negnevitsky, 2011, p. 1). The Merriam-Webster dictionary (2020) defines intelligence as follows:

  • 1 The ability to learn or understand or to deal with new or trying situations
  • 2 The ability to apply knowledge to manipulate one’s environment or to abstractly think as measured by objective criteria (such as tests)

For decades, scholars in the field of psychology have debated what constitutes human intelligence (Weiner & Freedheim, 2013). Some experts describe human intelligence as the capacity for “reasoning, problem solving and learning” (Colom et al., 2010). Additional common characteristics of human intelligence include logical thinking, spatial perception, and pattern recognition (Yao et al., 2018). Human intelligence also involves the ability to perceive, understand, and predict (Russell & Norvig, 2010) as well as the capacity for planning and adaptability (Siegel et al., 2003).

The goal of Al is to build machines that “can perform complex tasks as well as, or better than, humans. In order to perform those complex tasks, machines must be able to perceive, reason, learn, and communicate” (Siegel et al., 2003, p. 1). Achieving this goal has been the quest of computer scientists and engineers for more than half a decade. Computers are very good at performing specific tasks, such as complex math calculations, with speed and accuracy. Yet, today’s computers are not as good at performing tasks such as abstract reasoning, concept formulation, and strategic planning (Yao et al., 2018).

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