What AI Advancements Mean for Accountants
Artificial intelligence is transforming the roles of accounting and finance professionals — and that’s not bad.
Digital Exclusive - 2019
Artificial intelligence, or AI, is a buzzword in accounting and finance today. We constantly hear about the disruption it promises to bring to the profession and how the roles we play will all change sooner rather than later. But it’s also become harder to separate the hype from the helpful.
AI’s practical potential is truly rooted in very realistic notions. Put simply, AI is one of the most advanced concepts today. Its possibilities seem endless and the initial wave of academic research and early engagements and systems implementations in software and consumer electronics have evolved into real, practical methods and technologies that are positioned to continue changing the ways we work, interact, and make decisions — all while edging us closer to eliminating the risk of human error.
But AI isn’t really a new, disruptive technology. It’s spike in popularity and inclusion in the tech and gadgets we increasingly rely on makes it seem that way, but these are products of the aspirations of computer science pioneers since the early 1950s, and AI has simply evolved continuously since then. Today, AI is integrated within many aspects of our personal and professional lives without us always realizing it: Think of the customer service chatbots we increasingly interact with online, our personal assistants Alexa and Siri, the smart functions in our increasingly autonomous cars, phones, and more.
As AI continues to advance in our daily lives, it’s also being positioned to deliver an immense opportunity to accounting and finance professionals.
Erasing Human Error
While human intuition is its own cognitive wonder, it has its limits. The human brain is constantly bogged down by its own inconsistencies and biases, with things like availability bias and confirmation bias proving to be costly in decision making across industries of all kinds.
Here’s where there’s great promise; the advent of AI and machine learning is poised to assist human decision making rather than replace it — so throw out the fear of unemotional robots taking over the world (at least for now).
Machine learning is here to automate the mind-numbing, monotonous minutiae of number crunching and other redundant, time-consuming tasks accounting and finance professionals do on a day-to-day basis, which subsequently frees up time to focus on more lucrative advisory, analysis, strategy, business development, and client relations practices that require thoughtful human interaction and interpretation.
Machine learning has proven that organizing and parsing data is no longer a necessary task of the human brain. Machines have proven they can do it better, and if we let them spot the anomalies and patterns and provide us with insights, we’ll be better for it.
Essentially, machine learning is the application of statistical models and algorithms that mirror cognitive strengths like pattern recognition and contextual, specific learning. Its lack of fatigue or tiredness, complete lack of bias, adaptability in learning from complex and constantly changing patterns, and small margin of error makes it a technology that’s infinitely scalable in many industries, particularly those where parsing large data sets (like the tax code and financial statements) is common and critical.
In accounting, auditing, and finance, machine learning can easily offer professionals impeccable data-driven insights through its ability to be leveraged across both financial and non-financial data analysis.
However, there is a catch; machine learning algorithms and processes are only as intuitive and accurate as the data it learned from. Meaning, if the datasets inputted into these models are incomplete, insufficient, inaccurate, or somehow riddled with the user’s own biases, the insights the machine learning models spit back out will have the same issues — not helpful for an audit or contract review without proper intervention. So, here again is an example of how accounting and finance professionals simply cannot be replaced by AI or machine learning; rather, they will be there ensuring it is programmed correctly and learning and executing processes that meet the high standards and specific needs of the profession.
In addition, not every task is appropriate for AI just yet. While AI and machine learning have essentially endless potential, the current, practical realities for accounting and finance are that it only executes tasks with a high degree of repeatability or mathematical nature. The outputs of machine learning algorithms are even further limited in their predictive and suggestive nature.
So, what does this mean for accountants? It’s not human versus machine just yet. It’s not this way or that way. It’s not your job being taken away. Rather, the opportunity embedded in the current digital transformation of accounting and finance is allowing professionals and AI to work in unison to strengthen services and strategically tackle the tasks their cognitive engines are respectively geared for.
In other words, don’t fear the technologies we’ve been evolving with for decades; embrace them and employ them to be a future-ready accounting and finance professional.
Aman Mann is the CEO & co-founder of Procurify, a SaaS startup based in Vancouver, Canada that is helping organizations reinvent the way they track, manage, and control spending.