Introduction

We live in a complex world where we’ve accumulated huge amounts of knowledge. Knowing everything for a profession is getting harder and harder. We have better and better knowledge retrieval programs that let us look up information at our fingertips using natural language queries and Google-like searches. But in fields like medicine and law, sifting through all the results and sorting out what is relevant and important is getting harder and harder. Especially in medicine there is a lot of bogus and misleading information that can lead to disastrous results. This is a prime application area where Artificial Intelligence (AI) and Machine Learning are starting to show some real promise. We have applications like IBM’s Watson successfully diagnosing some quite rare conditions that have stumped doctors. We have systems like ROSS that provide AI solutions for law firms.

How about AIs supplementing Accountants? Accountants are very busy and in demand. All the baby boomers are retiring now and far more Accountants are retiring than are being replaced by young people entering the profession. For many businesses, getting professional business advice from Accountants is getting to be a major problem. This affects them properly meeting financial reporting requirements, legal regulatory compliance, and generally having a firm complete understanding on how their business is doing.

This article is going to look at how AI can help with this problem. We’ll look at the sort of things that AIs can be trained to do to help perform some of these functions. Of course, you will still need an Accountant to provide human oversight and to provide a sanity check, but if things are setup correctly to start with, it will save you a lot of time and money.

Interfaces

If you have an AI with Accounting knowledge, how can it help you? Let's look at a few ways that the AI system could interact with both the employees of the business as well as the Business Applications the business uses like their Accounting or CRM systems.

Chatbots

Chatbots are becoming more common; here you either type natural language queries to the AI or it has a voice recognition component that you can talk to. The query processor is connected to the AI and the AI is then connected to your company’s databases, as well as a wealth of professional information on the Internet. These AIs usually have multiple components for voice input, natural language processing, various business areas of expertise, and multiple ways of presenting results.

There have been some notable chatbot failures like Microsoft’s Twitter Chatbot, which quickly became a racist. But we are starting to see the start of some more successful implementations, like Sage’s Pegg or KLM’s Messenger Bot. Plus the general purpose bots like Alexa, Siri and Allo are getting rather good. There are also some really good toolkits, like Amazon Lex, available to develop chatbots so this becomes easier for more and more developers.

In-program Advice

There have been some terrible examples of in-product advice, such as the best forgotten Microsoft Clippy. But with advances in User-Centered Design, much less intrusive and subtle ways of helping users have emerged. Generally these require good content so what they present is actually useful, plus they have to be unobtrusive so they never interfere with someone doing their work, unless they want to pay attention to them. Then when they are used, they can offer to make changes automatically, provide more information or keep things to a simple one line tip.

If these help technologies are combined with an AI engine, they can then monitor what the user is doing and present application and context-based help. For instance, suggesting that perhaps a different G/L account should be used here for better Financial Reporting, suggesting that the sales taxes on an invoice should be different due to some local regulations, or making suggestions on additional items that should be added to an Accounting document.

These technologies allow the system to learn from how a company uses the product and make more useful suggestions, as well as having access to industry standards that can be incorporated to assist.

Offline Monitoring

In most larger businesses, the person using the Business Application isn’t the one that needs, or can use, an Accountant’s advice. Most data entry personnel have to follow corporate procedures and would get fired if they changed what they’ve been told to do, even if it’s wrong. Usually this has to be the CFO or someone senior in the Accounting department. In these cases, an AI can monitor what is going on in the business and make recommendations to the right person, perhaps seeing how G/L Accounts are being used and sending a recommendation for some changes to facilitate better Financial Reporting or regulatory compliance.

Care needs to be taken to keep this functionality clear of other unpopular productivity monitoring software that does things like record people’s keystrokes to monitor when they are working and how fast. Generally, this functionality has to stick to improving the business rather than be perceived as Big Brother snitching on everyone.

Summary

Most small business owners consider Accounting as a necessary evil that they are required to do to submit their corporate income tax. They do the minimum required and don’t pay much attention to the results. But as their company grows, their Accounting data can give them great insights to how their business is running. Managing Inventory, A/R, and A/P make huge differences to a company’s cash flow and profitability. Correctly and proactively handling regulatory compliance can be a huge time-saver and cost-saver in fines and lawsuits.

It used to be that sophisticated programs to handle these things required huge IT departments, millions of dollars invested in software, and really was only available to large corporations. With the current advances in AI and Machine Learning, many of these sophisticated functionalities can be integrated into the Business Applications used by all small and medium-sized businesses. In fact, in a few years this will be a mandatory feature that users expect in all the software they use.

Stephen Smith
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