Artificial Intelligence and Automation in Accounting: How to be Prepared
Artificial Intelligence (AI) is becoming a part of our reality at an astonishing speed. For the many who are less tech savvy, AI is still a thing of the future. We are interacting with AI technologies everyday, often unknowingly. From Alexa, Tesla, smartphones and Google search engine to ATMs, AI technologies are ubiquitous in our daily lives.
AI is also changing how we work. In a recent online article, Deloitte stated “AI technology will exert an enormous impact on economic development and the nature of work. It will also radically reshape the competitive dynamics of many industries”. When it comes to describing the state of accounting, the future tense in that statement needs to be revised. AI has arrived in accounting and is already changing this profession. Accounting firms are racing to adopt AI technologies to stay competitive. All of the Big Four public accounting firms have adopted AI technologies in their services and products.
What is Artificial Intelligence exactly?
Britannica defines Artificial Intelligence as, “the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.” The ultimate goal of Artificial Intelligence is to simulate human intelligence in reasoning, generalizing, learning from past experiences and adapting to a new environment.
There are two broad categories of AI: Narrow AI and General AI. Narrow AI is designed for accomplishing a specific task. As brilliantly showcased in the story of AlphaGo, which defeated the world’s No. 1 Go player at the time, some Narrow AI technologies now exceed human intelligence in specific tasks. Current AI technologies such as computer vision, natural language processing and voice recognition, which have been widely adopted in various industries, are narrow AI.
General AI has more resemblance to human intelligence in that it is expected to be able to learn anything and potentially do anything. Some of us may utter a sigh of temporary relief that General AI is still out of reach for practical applications at the moment.
At present, the main engine that propels AI technologies forward is breakthroughs in Machine Learning algorithms, especially in Deep Learning. As a result, the term AI is often used interchangeably with Machine Learning or Deep Learning in the mass media. The goals of AI are expansive and far reaching given the fact that scientists have not yet fully understood the complexities of what AI is trying to emulate, the inner workings of the human mind and human intelligence. Deep Learning is presently one of the most effective tools to achieve some of the goals of AI.
Deep Learning has the capacity to sift through a large amount of complex data, learn its features and patterns, and then apply the knowledge gained to make intelligent decisions about new data or predicting future trends.
AI is a significant upgrade from automation driven by conventional computer software in that it is able to self-teach, evolve and adapt to its environment without human intervention. Unlike conventional computer software, AI is flexible enough to work with fuzzy data such as facial expressions and hand written notes.
How AI technologies are affecting automation in accounting now?
At present, AI is capable of replacing a large portion of work traditionally done by a bookkeeper. On the auditing side, automatic anomaly detection as well as automatic report generation is already a reality. With the help of big data and deep learning, AI is able to dig deeper into data, produce better business insights and provide more accurate forecasts.
Intelligent virtual assistant and chatbot
Lex, the technology behind Alexa, Amazon’s voice activated home assistant, is used in accounting and other business settings to perform simple tasks such as scheduling meetings, creating to do lists, and querying existing databases. The AI technologies involved include voice recognition and natural language processing (NLP). Another widely adopted application of NLP is using chatbot to answer simple inquiries from clients.
Automatic data entry and document processing
With Optical Character Recognition (OCR) and NLP technologies, invoices, contracts or documents can be “read” by computer, and dollar amounts can be automatically entered into the correct accounts. Human error in manual data entry can now be largely avoided. The repetitive and error prone process such as data entry and matching documents can be performed digitally.
Automatic report generation
Aided by Natural Language Generation (NLG) technology, accounting reports can now be generated automatically. NLG can translate data and charts into language that can easily be understood by humans; it can also personalize a report for a specific customer. According to an article on Forbes.com, Commerzbank in Germany now uses AI to produce equity research reports. The technology has taken over 75% of the work that was performed by a human equity analyst.
Automatic detection of anomalies in auditing
Traditionally, auditing is an expensive and time consuming process. Therefore, an audit’s scope relies on sampling. With the help of AI, continuous auditing on a large dataset is becoming feasible. Rather than being at the downstream of accounting and only looking at a subset of accounting data, the auditing process can be active continuously alongside the accounting practices, examining the entire data set and discovering errors and anomalies as they occur.
Improved business insight and forecasting
Using AI powered data analytics software, companies can analyze large amounts of accounting data at unprecedented speed. Because of AI’s unique abilities to recognize patterns and predict trends from large data sets, business executives can make wiser decisions about business process optimisation and strategic planning.
What does the future of accounting look like?
As the accounting profession is constrained by long established procedures, rules and regulations, the adoption of AI technology in this field is likely to happen gradually. However, there is little doubt that AI will deeply affect this field in the following ways:
- The entry level repetitive accounting tasks such as data entry and compliance will soon be taken over by AI powered automation.
- Informed by the deeper insight from data brought by AI technologies, the role of accountants will increasingly shift towards business advisory.
- The restructuring of current accounting practices will be necessary as a result of the adoption of AI technologies.
- The curriculums for accounting students need to be overhauled to reflect the new realities of AI and automation.
- The changes in government accounting regulations are necessary to answer the challenges brought by AI and automation.
There are still many roadblocks to overcome before wider adoption of AI in accounting. The foremost concerns are security and privacy of data and the transparency of complex AI algorithms.
How to be prepared
Although AI application in accounting is still at an early stage, it is starting to reap substantive benefit in improving efficiency and reducing cost. To stay competitive, accounting firms need to be proactive in navigating the wave of change. The best strategy is to act now and start small at first, be open to changes and evolve as the technology matures. For public accounting firms, it is especially important in getting the buy-in from your clients at the very beginning of AI technology adoption. The study conducted by Partnership on AI has shown the clients are more inclined to accept complex new technologies such as AI, if they are involved at an early stage when the changes are small and relatively easy to manage.
As an accounting professional, to be prepared for the new challenges, you need to move up the accounting value chain and acquire a deep understanding of AI technologies. Rather than allowing AI algorithms to function in a blackbox, decisions or judgements coming from AI are likely to require human supervision and scrutiny. This will be an impossible task even for experienced accountants, if they are not well versed in AI technologies.
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