Many (probably most) consumers associate artificial intelligence (AI) with ChatGPT—and rightly so. ChatGPT and other such generative engines are, in fact, examples of AI at work. But there is a lot more to AI adoption than just ChatGPT.
Right now, the bottom line is that no one knows how AI will affect our lives and careers in the next six months, much less over the next decade. OpenAI, the creator of ChatGPT, has stated publicly that it is proceeding cautiously with its own technology. And last year, some of the greatest luminaries in the technology industry signed a petition expressing something resembling fear of AI, asking developers of the technology to pause big AI experiments.
Consider the first paragraph of the petition: “AI systems with human-competitive intelligence can pose profound risks to society and humanity… As stated in the widely-endorsed Asilomar AI Principles, Advanced AI could represent a profound change in the history of life on Earth, and should be planned for and managed with commensurate care and resources. Unfortunately, this level of planning and management is not happening, even though recent months have seen AI labs locked in an out-of-control race to develop and deploy ever more powerful digital minds that no one—not even their creators—can understand, predict, or reliably control.”
Not exactly comforting, is it? So, if AI is going to destroy all of humanity in the long term, it’ll surely take your accounting jobs in the short term, right? Probably not. But accountants do need to know what AI is and what they can do with it.
What is artificial intelligence?
What exactly is AI, anyway? Experts have written books and other long volumes about AI, but this explanation will be simple and relatively brief. The most concise and accurate definition of AI is probably this one from McKinsey and Company: “Artificial intelligence is a machine’s ability to perform some cognitive functions we usually associate with human minds.”
Simple, right? And maybe a little dystopian. But AI is also nothing new. The phrase itself has existed since 1956, and research into what is now known as AI goes back as far as 1943. One key point to understand is that AI is a concept that has several components. In very broad strokes, they include a few basic concepts.
Machine learning
Often confused with AI itself, machine learning is actually a subfield of AI. Machine learning uses data to detect patterns and then makes predictions based on those patterns. Your Netflix suggestions are the result of machine learning. So are predictive texts and chatbots, for better or worse.
Machine learning works without any input from a human, which separates it from generative AI tools such as ChatGPT that respond to users’ prompts. Deep learning is a more advanced version of machine learning that mimics neurons in the brain.
Natural language processing
This technology allows devices and applications to understand what you’re saying to them and respond, whether you’re speaking or typing. If you have Siri or Alexa, natural language processing enables “her” to process and respond to your questions. It’s also essentially the technology your digital assistant uses to boil down a massive amount of data into one simple answer. ChatGPT uses natural language processing, too, to understand and respond to queries.
Large language models
Large language models (LLMs) are the hot new technology that powers apps such as ChatGPT. It’s essentially, from which it evolved. LLMs add context to responses. They can process massive amounts of data almost instantly and return a result that goes beyond a simple answer. Alexa might not be able to write you a synopsis of the Cuban Missile Crisis in seconds, but ChatGPT can using LLMs.
AI adoption remains almost entirely unpredictable
You’ve been using AI components for years without even thinking about it. Text-to-speech software has existed for decades. Cars, and not the self-driving kind, have incorporated elements of AI for more than a decade. And you probably talk to a digital assistant like Siri or Alexa every day.
But now AI is reaching a tipping point, with generative tools and advancements that have brought it closer to thinking—or even out-thinking—a human being. And nobody knows how far AI will go or how quickly. Any predictions or forecasts at this point are pure speculation.
The cautionary tale of self-driving cars
Look at, for instance, the hype around autonomous vehicles, more commonly known as self-driving cars, which rely heavily on AI. Wild predictions from tech CEOs and other luminaries in the mid-2010s suggested that self-driving cars would dominate American highways by 2020. Lyft’s then-CEO said in 2016 that the majority of trips on his ride-sharing service would be driverless by 2021.
Needless to say, that has not happened. In fact, the National Highway Transportation Safety Administration says that true self-driving cars aren’t commercially available at all, a stance some automakers might debate. There are a lot of reasons why autonomous cars haven’t come roaring off the assembly line. Some of those reasons are market-driven, but others are related to technology.
For instance, driverless cars are basically ChatGPT with an engine. And just as ChatGPT can occasionally spit out nonsense or incorrect information, autonomous cars can go haywire every now and then. While an incorrect citation in a white paper might not be a disaster, an autonomous car freaking out most certainly can be.
Accountants and AI adoption
The widespread confusion surrounding AI has seeped into the accounting profession. A recent Rightworks survey found that almost 70% of accountants consider themselves only slightly knowledgeable or not knowledgeable at all about AI. Only 11% of respondents said they were actively using AI, while 35% have no plans to use it.
In a recent Thomson Reuters survey, the number of respondents not planning to adopt ChatGPT was even higher, at 56%. And yet there is some optimism about AI in the profession. In a Karbon survey, 54% of accountants surveyed said they believed a firm’s value would drop if it didn’t use AI, and two-thirds said AI can create a competitive advantage. There’s no consensus about AI in accounting, just as there isn’t one among consumers in general.
There is, of course, fear in virtually every profession that AI will replace people. It’s not unfounded: Resume Builder found that 37% of companies using AI said the technology replaced people in 2023, and 44% said AI will lead to layoffs in 2024.
There is fear among accountants, too—which could be one reason why so many firms are avoiding AI altogether. But accountants shouldn’t worry about their jobs, at least for now. And they probably shouldn’t for years to come. AI can still respond with bad information, after all, and accounting is not a mistake-tolerant business.
What accountants can do with artificial intelligence
Another guard against AI taking over the profession is that accountants earn their living as trusted advisors to clients, not number crunchers. Firms that want to grow and succeed are accomplishing those goals by offering new and expanded advisory services—a job AI certainly cannot handle alone, although it can help.
AI isn’t an all-conquering behemoth yet. For now, and for the foreseeable future, it’s a powerful tool that accountants can use to do their jobs more efficiently. AI offers a whole new way to interact with data. Instead of scrolling through links in a search engine, you receive a direct answer in an immediately usable format. Then, you can use your judgment as to what you take from AI and what you don’t.
How to get to know AI
The best way to get to know an AI tool is to use it. Experiment by asking accounting questions. For instance, have an AI tool create an introductory email to a client and see how you like the result. Then, ask some questions related to tax policy or business practice and evaluate the answer.
You might find that AI can give you a great jumping-off point for developing new ideas for client service and advisory offerings. With AI adoption, your firm can move more quickly than those that don’t use the technology. Plus, you might stumble upon ideas and strategies you wouldn’t necessarily have come up with yourself—and that your competitors without AI might never come up with at all. Plus, you can handle mundane chores almost instantaneously—writing introductory emails to clients or letters asking for documents. And this can save you more time.
Spark gives your firm a starting place for AI adoption
Your best bet for getting started with AI is Spark from Rightworks. Built specifically for the accounting profession and infused with Rightworks’ decades of experience in accounting, Spark is an AI engine similar to—but more secure than—ChatGPT. In addition to being safer than ChatGPT, Spark is more likely to return accurate information—although no AI engine is perfect or completely secure.
Spark is a great way for accounting professionals to get into AI, in part because it’s so easy to use. Pre-built prompts give accountants a jumping-off point into using the tool to do their jobs better. Spark also includes assistants that offer virtual expertise in various roles, including firm owner, client relations, human resources and marketing. You can create your own custom assistants as well.
The future of both AI and AI adoption is unpredictable. But in the present, accountants have no reason to fear the technology—and it’s likely they never will.
Instead of running from AI, embrace it. Learn about it. Try it. Used well, AI is something you can tame, not something that tames you.
Get started with AI for accounting today. Check out Spark.