The Revolutionary Impact of Intelligent Automation for Accounting

Think of an accountant’s work like a pyramid. At the bottom sit all the manual, time-draining tasks involved in collecting and processing data. At the top are the insights and analytics that can inform business decisions. The problem? “Too many accountants have to spend too much of their time on the bottom of the pyramid,” said Rob Zwiebach, vice president, product management and financials management, Workday, said at Workday Rising Europe.

The ability to flip the script—or, better yet, the pyramid—is just one reason that today’s finance leaders see potential in AI. A Deloitte report found that CFOs are especially eager to gain three benefits from AI:

• Reduced costs

• Improved customer and client experience

• Increased margins, efficiencies, and/or productivity

At Workday Rising Europe, Alex Young, master data and change manager, Just Eat Takeaway (JET), and Rob Zwiebach, vice president, product management and financial management, Workday, discussed how AI and intelligent automation are transforming the accounting function and allowing finance teams to deliver the insights their organisations need.

Solving the Talent Shortage by Busting Drudgery

Accounting is reeling from a scarcity of talent. About three-quarters of the certified public accountant workforce reached retirement age in 2020, and not enough young people are lining up to fill their shoes, Zwiebach said. 

“People are not coming out of college and going into this field the way they have in the past, and we think the reason for that, rightly or wrongly, is that there is a perception that these types of jobs involve a lot of drudgery,” he said. 

Young echoed that sentiment of struggling to hire accountants for the finance team at JET, a Netherlands-based online food ordering and delivery company with about 15,000 global employees and $5.6 billion in annual revenue. That’s a real problem for the organisation since accountants aren’t just crunching numbers they’re also acting as business analysts and partners. But with a shortage of accounts, “we find they’ve been reduced to a keep-the-lights-on role,” Young  said.

AI promises to turn around both the perception and the reality of accountants’ work. “Let machines do the drudgery, and let people do the more interesting, value-added tasks,” Zwiebach explained. 

For instance, journal entries and expense reports once entailed loads of manual tasks to ensure accurate recordkeeping. That’s no longer necessary. Platforms equipped with machine learning (ML) capabilities can quickly analyse accounting entries and flag anomalies based on patterns of past journal entries and related transactions. Solutions like Workday Expenses then alert users about potentially misclassified or erroneous journal entries that require adjustments, explain why those entries were flagged, and make insight-rich recommendations for the needed corrections.

Accountants then have a straightforward decision to make: Accept the entry as is, or correct it. With each user response, the AI solution gets smarter. 

“The system learns from that human feedback,” Zwiebach said. “It is true machine learning. And rather than a person having to slog through massive amounts of data, the system provides a guided experience to what most likely needs human intervention.”

Realising Time Savings and Efficiencies

AI can make quick work of the manual, repetitive, and often error-prone tasks that historically have been placed in accountants’ laps. As a result, the technology frees up accountants to focus on the analytical work that not only gives them greater satisfaction but also allows them to become true strategic partners to the business.

Take the case of one of the manual-heavy accounting processes: supplier invoicing. Usually this process involves, at best, email attachments, and at worse, snail mail. By using a financial management platform that automates this process, users can simply email an invoice directly to the platform. The system then scans the invoices, parses out the various elements such as the vendor’s name and the invoice amount, and flags any missing data by leveraging ML to analyse past invoices. All without human intervention.

“Ultimately, our goal in 2024 is to get to truly touchless invoice processing for PO-matched invoices,” Zwiebach said.

Time savings will be a boon for JET. “It takes us two weeks to close our books, so it feels like we’re constantly in closing,” Young said. “Saving time is mission-critical for us.”

One way that JET now saves time is by using Workday Accounting Center to ingest business events and external data and transform them into detailed accounting data. In the past, JET finance teams had to download data from a third-party supplier, perform calculations in spreadsheets to create journal entries, and then load those entries into its accounting system. Now, all that data goes directly into its financial management platform. 

“The Accounting Center now does all the work, which saves two of our people several hours every month-end close,” Young said.

Making the Most of Data

Accounting and AI have something in common: They both rely on data—massive amounts of reliable data. But to get the data they need, accountants have long depended on manual processes—including plenty of spreadsheets—that can easily introduce errors. AI mitigates that risk. 

“Intelligent automation puts in place controls that help the CFO’s office feel assured so they know their data is correct,” Zwiebach said.

Along with operational efficiency, data-driven insights ranks as the top driver for AI adoption in the finance function, according to a Workday survey of 2,355 global senior business executives. 

“The user experience should be more about consuming insights from the system and managing exceptions and approvals—and much less about just keying in data,” Zwiebach added.

In the not-too-distant future, Zwiebach shared, the capabilities of intelligent automation will quickly expand. For example, with a financial management platform that can harness the power of a large language model, accountants will be able to automatically generate dunning letters—collection notices sent to customers alerting them to overdue payments. Instead of having to create these letters from scratch every single time, employees will simply answer a few prompts—such as the tone they want to strike—to generate the letter.

“With traditional processes, accounting professionals have to spend a significant amount of their time on data collection and processing,” Zwiebach said. “Our goal is to leverage intelligent automation to help them invert the pyramid and spend their time on insight and action.”