by Daniel Chandler, Tax Associate

Artificial Intelligence (AI) is emerging as the most disruptive technology of our time, and it is transforming the way businesses do their accounting. AI accelerates processes and allows for more advanced analysis and projections.

AI has the capability to categorize and summarize large volumes of financial data, which produces more accurate financial statements and trial balances, and faster financial analysis. AI can also analyze client patterns to provide powerful insights into improving customer experiences and predicting future customer behavior and market trends. In the accounting process, AI can help internal auditors and accountants prepare and review a business’s financial reporting documents.

How does AI work?

AI is a machine or program that performs tasks which require a human level of thinking. AI can automate some basic business processes as well as boost work speed, accuracy, and efficiency. AI “learns” a variety of skills including problem solving, language and image recognition, making predictions, and content creation. During the “learning” process, AI is given large amounts of data to analyze and adjust coding of the AI until it performs the way it’s intended. Afterwards, AI may need to be fine-tuned to better fit the real data it will be using.

AI systems use algorithms to analyze large amounts of data. An algorithm is a process, or a set of instructions or rules, used to solve specific problems or to perform calculations. A common example of an algorithm is an if/then statement, such as “If the weather is cold, then I will wear a coat.” Even simple rule-based algorithms can create a lot of impact for a business. Two of the more commonly-used AI systems are Machine Learning and Natural Language Processing.

Machine Learning (ML) focuses on developing and using complex algorithms and models to allow a computer system to perform tasks without direct programming. The goal is for machines to learn patterns and make decisions based on the data provided. ML algorithms are often used in larger and more complex AI models.

Natural Language Processing (NLP) enables machines to understand and interpret human language. NLP summarizes texts, generates new text, translates languages, and performs voice recognition and sentiment analysis. NLP algorithms use complex formulas to train computers to understand natural languages, helping machines comprehend spoken words or text.

Businesses can access AI in a variety of ways, including through a website or mobile app such as ChatGPT or DeepL, which offers a subscription to use their services commercially. Other providers, like Microsoft Azure, offer AI services through websites, software, and apps.

How can AI help businesses?

AI can make the preparation of financial statements and reporting documentation faster, more efficient, and more accurate. It can also provide critical insight into a business’s industry, which can guide a company as it pursues a more strategic position for growth and development.

Common business functions where businesses can benefit from AI include:

Customer Relations: AI enables personalized customer experiences by analyzing customer preference and behavior to produce customized marketing, recommendations, and tailored customer service. By analyzing customer feedback and reviews, AI helps a business understand its customers’ needs and wants. This can lead to better service strategies or product development. AI in customer service also provides customers with quick answers to their questions without having to be in direct contact with a company employee. Most business chat bots and self-service systems use ML and NLP AI to communicate and assist customers in real time.

Predictive Analytics, Forecasting, and Budgeting: AI can analyze and predict market trends and customer behavior – important elements for budgeting for future needs, meeting market demands, and limiting the risk of stockouts or overstocked inventories.

Automating Manual Tasks: AI automates data entry-related tasks by identifying, categorizing, and transferring information from various sources into a single data management system. AI can also streamline repetitive tasks, such as resume screening, generating recruitment material, payroll processing, invoicing, creating sales or marketing campaigns, and preparing financial statements.

Fraud Detection: AI algorithms can analyze large sets of financial data and identify potential areas of risk or irregularities which may be hard to identify manually. The sources of the suspicious data can be identified by AI.

Research, Review, and Compliance: AI can perform research into relevant laws, both domestically and internationally. This includes tax laws, financial reporting requirements, product safety laws and or employment laws. The information gathered by AI is then useful in strategic planning for expansion into new markets or industries, or to review both internal documentation and policy (such as contracts) that an organization may be involved with. AI can provide critical insight into making sure an organization is compliant with the law and can identify areas of potential concerns, including any unfavorable terms or issues that may be overlooked by a manual review.

Potential Areas of Concern

While AI has many advantages, it also presents concerns regarding security, accuracy, and bias.

Data security: Keeping client, employee, and proprietary data and processes secure is crucial for any business. To keep data safe, businesses should maintain ongoing security measures throughout the entire process of selecting and implementing an AI system. Some AI systems store information in a cloud, either maintained by the AI provider or by a third party hired by a provider.

Accuracy: Generative AI cannot guarantee the accuracy of the content it creates. Many public AI solutions, like ChatGPT, generate outputs based on patterns in the data they were trained on. This can lead to misleading or false information, which may result in misrepresentation of a company’s financial position and issues of non-compliance with reporting requirements. It is imperative for any organization to review the data its AI software is using to make sure the information is accurate and up to date.

Bias: Bias in AI generally refers to the type of data put into the system or the methods in which the system is asked to analyze. Restricting data or limiting the way an AI is allowed to analyze the data may lead to bias in outcomes, which could create inaccurate predictions and information. Restricting data refers to allowing only partial data to be accessed, either by removing fields, lines, or timeframes from the data. Limiting the way AI is allowed to analyze data simply means restricting what forms of calculations or logical steps an AI can take as it analyzes the data.

Embracing AI

The value in AI lies not in replacing human workers with machines, but in using technology to automate and accelerate routine analysis and processes that used to be done manually. It enables an organization to focus its analysis and projections on the most important areas of its company and industry. Learning how to leverage AI tools can help businesses deliver value with speed and confidence. When humans and AI are aligned to support each other, everyone can work more strategically, benefiting both themselves and their clients.