More than most other industries, accounting hasn’t seen much innovation since the creation of double-entry bookkeeping - a process of recording both profits and losses - and considered one of the greatest advances in the history of business and commerce.
That was over 500 years ago!
However, the good news is that applying AI and machine learning technologies to bookkeeping, is becoming a reality with most of the major accounting software vendors (Intuit, OneUp, Sage, and Xero) currently offering capabilities to automate data entry, reconciliations and sometimes more.
In our upcoming research report on the future of accounting, we expect that by 2020, accounting tasks - but also tax, payroll, audits, banking… - will be fully automated using AI-based technologies, which will disrupt the accounting industry in a way it never was for the last 500 years, bringing both huge opportunities and serious challenges.
Artificial intelligence will not eliminate accountants
“Having machines to do all these tedious and repetitive tasks could sound scary for many accountants because they are also very time-consuming and thus very lucrative,” explained Stephanie Weil, CEO of Accounteam, a Silicon Valley-based accounting firm. “However, if the AI system is well configured, it can eliminate accounting errors that are generally hard to find and thereby reduce our liability and allows us to move to a more advisory role.”
In an upcoming research study, we also tested the automation capabilities of 4 of the most popular AI-enabled cloud-accounting solutions available in the market today (OneUp, QuickBooks Online, SageOne, and Xero) and rank them against our Accounting Automation Index (AAI) which evaluates the accuracy of their AI engines to automatically recognize transactions coming in from bank feeds and generate the correct accounting without any user intervention.
OneUp proved to be the most effective with an Automation Index rate of 95% after 5 months of use, followed by QuickBooks Online (77%), Xero (38%) and SageOne (30%).
Despite being very promising, the accuracy of the machine learning algorithms used in most of today's solutions still needs to significantly improve in efficiency to avoid accounting errors and really fulfill their promise of automation.
Author: Jean Baptiste is a Vice-President and Principal Analyst at Atherton Research, a global technology intelligence firm helping clients deliver successful go-to-market strategies.