AI – The new wave in accounting

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Artificial intelligence has been a hot topic in accounting for years. Reliance on data automation will only increase as the decade marches on. Firms that seek to remain a step ahead would be wise to reckon with AI today, no matter the scale on which they are able to do so. In order to do that though, it’s important to take pauses in the business to lift up at a higher level and determine the best path forward.

Before we begin exploring the state of AI in 2021 and beyond, let’s begin by defining what we mean when we say “AI.” AI is a broad category of technologies that covers a huge range of operations, but the definition provided by Britannica is a good starting point. They define AI as “the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.” Think of AI as the umbrella under which almost all of your automation technology lives. The field of AI encompasses subcategories like machine learning (ML), deep learning, native language processing, and computer vision.

We may also break down AI into “narrow AI” and “general AI.” In the accounting space, the possibility of general AI, an artificial intelligence that can comprehensively automate entire operations, is still a long way off. On the other hand, the applications for narrow AI, the ability of computers to perform specific tasks, are constantly increasing and becoming more sophisticated. It is in the arena of narrow AI where most firms can increase automation, improve efficiency, and free up time to spend on high-value advisory services.

Paving the way for an AI-powered future

At the largest firms, those with the resources to invest in large-scale AI adoption, it’s time to begin adopting systems that allow for the greatest harnessing of the technology. These days, technology and strategy must go hand in hand if you want to get the most from either. In fact, many large firms are beginning to alter their data collection systems in order to make them more amenable to machine learning, even if that comes at the expense of easy interpretation by humans. The richer the insights you can glean from your AI systems, the better of you will be, and providing machines with rich, usable data is a huge part of that.

In order to do this, it means creating a strategic vision of what you want to look like as a firm and how you want to work today and 5 years from now. You want to make sure it’s not just talk, but actionable strategic initiatives that the whole firm can get around and know how to align their personal objectives to. Leaders can begin by analyzing all of their decision-making in the context of its ability to dovetail with AI that today is manual or information that isn’t easily at their fingertips. Look to harmonize your systems and procedures in accordance with your technology that you currently have or that is available for your needs. One important thing to note on this topic is that very few firms, even those with plenty of capital for R&D, have opted to develop bespoke in-house systems. Even though this may seem like a competitive advantage, when utilizing software from companies that develop this technology and monitor it on a daily basis can simply be better at providing what you need because they are getting feedback from customers from all over and developing new features throughout the year. As such, shopping for solutions is often more prudent than developing them in-house.

Getting on board today

Of course, most firms won’t have the capability to adopt the very latest technology, but that doesn’t mean they can’t begin taking advantage of automation today. Odds are, you already rely on some form of AI to power portions of your business. Even better, you’re probably well equipped to adopt more uses. As the pandemic forced even the most old-school firms to transition to cloud-based operations. These platforms make leveraging AI easier than ever before.

A good exercise to determine where you have room for automation is to write out your processes for dealing with a client each month. After breaking them down step-by-step, look for the places where you rely on manual data entry or computation. Let’s say, for example, you want to automate payroll processes. You may decide to use an app to not only complete payroll, but allow you to forecast projections based on the app’s AI analysis of your data. Instead of having to crunch the numbers yourself to generate these forecasts, you can leave it up to sophisticated AI. The same can be done for a whole host of processes, both for client-facing and internal operations. Having advanced data of this kind doesn’t just free up time and energy; it also provides greater insights that allow you to do the other parts of your job better. In that sense, it’s a total win-win.

Embracing the AI wave

The most important advice I can give you about the ever-growing role of AI in accounting is to embrace it head on. The genie is out of the bottle and it’s not going back in. I’m not making a bold prediction when I say accounting will never return to a pre-AI environment. As scary as change may be, now is the time to pause, assess and embrace the AI you can use today and prepare for the applications you’ll be using tomorrow.