The future of AI in accounting: Part 1 – What is AI?

human and robot hand

 "Thou shalt not make a machine in the likeness of a human mind.” Frank Herbert, “Dune”

As an accountant, you’ve likely heard about the general impact of technology on the accounting industry from firm leaders and publications. However, and more specifically, you may be wondering - how can accountants use artificial intelligence (AI) in their careers? 

Let’s start with an overview of AI. In recent years, rapid technological advancement has enabled neural networks, machine decision making and robotic “relationships” to evolve from science fiction fantasy into Wall Street monetization. AI is part of what is now called the Fourth Industrial Revolution, or the age where computers and computational systems both eliminate and create new jobs and industries across all sectors of work. So, what does the role of AI in accounting mean for your accounting career?

While some very repetitive and “typical” accounting tasks like bookkeeping and ledger entry may become automated, the good news is that the current and future impacts of the use of AI in accounting will likely lead to augmenting accountants’ current responsibilities rather than replacing them altogether. 

New, evolving accounting roles incorporate the use of AI tools, allowing accountants the opportunity to upskill their roles and provide a broader portfolio of services. Let’s take a look at your evolving role and what you can do personally to successfully prepare yourself for your career’s future. As the role of AI in accounting evolves, you’ll act as a trusted advisor who works alongside AI, rather than competing with it.

What is AI in accounting?

Very briefly, AI is a branch of computer science that develops computer programs with the capacity to analyze exorbitant amounts of data, employing defined rules, algorithms, and patterns to do so. Algorithms in math are processes used to solve a problem in a limited number of defined steps. AI algorithms are modeled after human decision-making and problem-solving processes. For example, AI-powered autonomous driving systems allow food delivery trucks to drive themselves, turn, park, obey the speed limit, change lanes, back up and, most importantly, deliver pizza.

The terms “automation,” “machine learning” and “machine intelligence” are often used interchangeably with “AI.” These terms are related, but each has a slightly different, narrower focus. The following definitions will help clarify their use as related to AI in accounting.

Automation is what happens when a human directs a machine to perform a task and has the machine execute the task successfully: think robotic manufacturing of cars.

Machine learning detects trends and patterns from data to draw conclusions. It becomes more efficient in determining your needs over time: think speech recognition that suggests restaurants for you.

Machine intelligence is a higher evolution than machine learning that goes further and codes in deductive logic. It adds other human-like intelligence layers that mimic learning, prioritizing and solving problems to tackle more complex issues: think online chatbots that solve IT issues or increase your credit limit.

Preparing for a successful future with AI in accounting and finance

With the advancement of AI-related software applications, there will be a huge impact on white-collar jobs, including accounting. Till Leopold, lead of the World Economic Forum’s Global Challenge Initiative on Employment, Skills and Human Capital, comments:

“We expect around 35% of skills will be different in the near future [due to AI].”

The Institute of Chartered Accountants in England and Wales

AI development and applications are already rapidly transforming accounting roles, and will continue to impact the accounting profession in both the near and far future. As a result, accountants will need to expand their skill sets and competencies to keep up, and will be expected to act as an advisor to clients regarding AI knowledge and AI-powered tools.

Becoming this trusted advisor consists of two broad requirements with respect to your personal development. First, you’ll need to learn how AI computing power is changing the way financial data is extracted, organized and reported. Second, you’ll need to develop certain soft skills in the context of AI, so that you can build trusting long-term client relationships to advise them on complex financial decisions. With that in mind, let’s explore how you can use various AI accounting impacts to stay ahead of the curve.

AI in accounting is transforming the financial landscape

The many AI-influenced changes to accounting fall into three main categories: data analytics, audit and financial processes.

Data processes + analytics: Big data is the first major change in the world of AI in accounting. In general, big data refers to migrating dispersed databases to a centralized location in the cloud combined with global, 24/7 high-speed internet access. Accountants will be expected to know where financial data is located and how to obtain it, which was previously thought of as the responsibility of clients and their information technology departments. Bookkeeping and manual data entry are the first wave of accounting activities to become automated, with data consolidated in an always accessible database so that it can be manipulated and analyzed.

Audit: Centralized access to vast amounts of data previously dispersed across individual spreadsheets, PCs, mainframes and servers will promote faster, more efficient client audits. Financial information will be readily accessible anytime, day or night. Thus, auditors will be expected to obtain, organize, synthesize and offer value-added analysis on how to conduct the best audit for a client with optimal financial outcomes.

Many auditors use data samples when conducting audits because extracting disparate amounts and types of data (for example, tax deductions, pricing, SKUs, inventory) can be too time-consuming. Now, consolidated databases (aka, big data) make it easy to audit an organization’s entire financial profile instead of just samples. This big-picture view allows accountants to analyze financial patterns and lower risk, as they can more easily flag mistakes and discrepancies.

Financial processes: The financial processes all companies need to conduct business including accounts payable and receivable, sales and sales forecasting and expense tracking and reporting. As a result of big data and streamlined auditing, accountants are able to execute predictive and prescriptive financial analytics for their clients, which can make their clients’ financial processes more efficient, accurate and profitable.

Predictive and prescriptive analytics are two overarching outcomes of AI in accounting. At a basic level, predictive analytics anticipates future outcomes – for example, forecasting sales and informing more accurate demand planning is just one way this type of analytics adds value.

Prescriptive analytics, in contrast, provides raw data to weigh one financial decision against another. This can inform clients on the exact materials and services they’ll need to improve, say, manufacturing output and increase sales. Accountants should be prepared to master both types of analytics to reap the benefits of AI in accounting and to remain future-focused.

All in all, learning about the use of AI in accounting and its impact on your role as an accountant can only serve you well, as the future of accounting continues to intertwine with AI and computer-driven processes. Upskilling in this area will be beneficial to your accounting career both immediately and in the long term.

Jumpstart your future-forward learning with some of Becker’s top AI in accounting CPE courses:

Keep reading the Becker accounting blog to learn about more important AI in accounting topics that all accountants and CPAs should be in the know of.

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