Artificial Intelligence: Has It Come to Accounting?

​Have you noticed that your accounting or banking firms are letting artificial intelligence get involved in some heavy lifting? Many companies are seeing that AI should be worked into their overall strategies, putting money aside for innovation.

AI is geared to take over repetitive, time-consuming and redundant tasks and free finance professionals to do higher-level and more lucrative analysis and counseling for clients.

Automation, minibots, machine learning and adaptive intelligence are becoming part of finance teams. Machine learning and AI applications continue to increase and impact accounting and finance responsibilities, allowing for more productivity and proficiency of humans, handling more clients and delivering more value—insights rather than just crunched numbers.

Financial leaders who embrace change are gaining expertise to make the applications more valuable in future business process transformations. Already, there are AI-powered invoice management systems making invoice processing more streamlined. Soon, AI may be part of your accounts payable and accounts receivable systems.

Supplier onboarding with machines vets new suppliers by checking their credit scores or tax information and setting them up in the system without human involvement. How about procurement and purchasing processes? They are filled with paperwork and use different systems and files that aren't compatible. Procurement systems eventually will be paperless, with robots tracking price changes among suppliers.

The accountants and auditors and the brokers and bankers aren't going away anytime soon. But you'll eventually start seeing financial institutions contracting with specialized technology companies or building their own departments. AI enables computers to perform decision-based tasks previously left to humans. Machine-based learning gets better at analysis the more it's used. Speech-based technology understands a variety of voices and languages.

AI today digests and analyzes large volumes of data at speeds well beyond what people can do. The more analytic and decision-oriented computations still require humans. At some firms, for example, auditors access AI tools with natural language-processing capabilities to interpret thousands of contracts and deeds, extracting key terms and compiling and analyzing information to perform risk assessments.

In other developments, data science teams are tackling complex billing problems in the health care industry. Machine-based learning allows the firm to sift through enormous, but disparate, billing systems to flag accounts with time-consuming and costly complexities in claim processing and reimbursement.

Health care firms and hospital clients use new technologies to deal with complicated cases instead of waiting for problems to happen, saving clients hundreds of man-hours.

Auditors will be able to conduct accurate assessments of real estate holdings and analyze thousands of contracts for risk management. Auditors' professional skepticism allows them to spot when analyses are off and to deal with exceptions.

The technology will become more widely available in the coming years, as common as the internet is now. Machines will be working alongside accountants and bankers in the future, but this doesn't mean people will disappear: Indeed, they'll have even more time to work with business managers, individuals and families, providing the emotional intelligence no machine can replace.