woman with brown glasses staring at code screen with the reflection hitting her glasses, Q3 2021, TAA NA US - Preparer
Tax & AccountingJanuary 22, 2024

The power of AI: What accounting and tax professionals need to know

Artificial intelligence (AI) is constantly evolving, and keeping up with the latest advancements is key for accounting and tax professionals to work smarter and gain a competitive edge.

Equip yourself with a basic knowledge of AI and what it means for tax, accounting and auditing professionals to help you maximize the opportunities AI can offer your business.

Understanding AI and its role in accounting

Today, artificial intelligence is transforming the way tax and accounting professionals do their work. Rapid advancements in AI are making it easier than ever for accounting firms to speed up routine tasks, analyze massive amounts of financial data, spot patterns and anomalies, reduce human error, and keep up with changing laws and regulations.

Here’s an overview of how AI works and why it matters in accounting.

What is AI?

In broad terms, AI is technology that helps computers gather information and figure out solutions in ways that imitate human thinking. AI uses data to learn – the greater the data, the “smarter” the AI.

At work, AI can automate basic business processes, boosting speed, ensuring accuracy and reducing costs. When employees can use AI tools to help streamline their workflow and complete time-consuming tasks, they’re more productive and efficient.

AI can “learn” different skills, like how to make predictions, create new content, and communicate conversationally. Artificial Intelligence is an umbrella term that covers a wide range of AI subsets and approaches, including machine learning, generative AI, and large language models. Let’s dive into how these different types of AI work, so you can implement them to benefit your firm.

Machine Learning

Machine learning is a subset of AI that systems use to analyze enormous amounts of data to learn to spot patterns, make recommendations and flag possible errors. Data enables machine learning to perform tasks without explicit programming instructions, enabling accurate predictions and decisions based on statistics and complex algorithms. Examples of machine learning in everyday technology include recommendation systems within Netflix, virtual assistants like Siri, or navigation apps that predict traffic conditions and suggest optimal routes. 

Wolters Kluwer leverages machine learning as part of the CCH Axcess™ Engagement suite to automatically group accounts based on historical grouping data when importing a trial balance. 

Generative AI

When AI uses patterns in data to create something new, this is called Generative AI. A variety of data types can “train” generative AI to create realistic images, sounds, software code, text, or other media. ChatGPT has become one of the most talked about examples of generative AI in recently years, but generative AI technology has been around for many years. It is used in many customer service chatbots and within photo editing software to remove people or objects from images based on context. Early in 2023, several significant enhancements to generative AI technology were announced resulting in a more realistic, higher quality, human-like outputs.

Large Language Models

For text-based tools like chatbots, generative AI builds on large language models (LLMs), a type of AI that learns from enormous volumes of text. LLMs compare billions of words and phrases to allow computers to understand text-based questions and generate responses. ChatGPT is a powerful LLM that gathers input to generate human-like text responses.

How AI is changing the game for the tax and accounting industry

Advancements in machine learning and generative AI are revolutionary for the tax and accounting industry. 

Here are some ways accounting firms can use AI today and in the future.

Streamlining research on tax codes and accounting standards

AI can help accounting firms improve their research process to deliver more accurate and useful information. It can bring tax research directly into the workflow, provide anticipatory prompts based on client data and changing regulations, and reduce the time needed to conduct the research, verify the sources, and understand the implications. Once the information is gathered, AI can help summarize the research and draft customer-focused messaging that explains the implications of the research related to every customer’s specific tax situation.

Identifying tax advisory opportunities

By identifying which clients are impacted by triggered tax events, AI can help firms proactively reach out to clients and secure additional opportunities to provide value and boost revenue for the firm. AI can explain tax changes in plain language and create tailored client communications based on the tax event and client data to proactively alert clients to potential issues.

Strengthening customer relationships

AI helps firms offer proactive and personalized services while spending less time managing accounts and correspondence. From chatbots engaging prospective clients by providing instant answers to questions about the firm or clients’ account or tax scenarios, to automatically generating client letters with simple explanations of complex tax situations, AI can help firms provide customer-focused insights and timely personalized recommendations.

Optimizing firm management and operations

Firms can use AI to access intelligent insights to improve internal processes, productivity, and profitability. AI can track firm-wide metrics over time, isolating trends and identifying opportunities to optimize client relationships, staff assignments, scheduling and resource allocation, billing and invoicing. It can save firms time by generating meeting transcripts and drafting internal messaging like company policies and firm-wide communications. AI can also help with customer service and marketing by providing specific customer metrics on tax savings, penalty avoidance, and other concrete advantages of working with the firm, writing client communications, and creating marketing content like blogs, newsletters and social media posts.

Challenges and concerns with AI in accounting

While AI has many advantages, it also presents concerns specific to the accounting industry.

Data security

Keeping client and firm information secure is crucial, so while firms build up their capacity to use AI tools, they must incorporate ongoing security measures throughout the entire process of building and launching AI solutions to keep data safe, maintain privacy and avoid misuse of information.


Accuracy of AI-generated information is another concern. Generative AI cannot guarantee perfect accuracy of the content it creates. Many public generative AI solutions, like ChatGPT, generate outputs based on patterns in the data they were trained on. This has led to some very public examples of generative-AI-created content containing made up, or hallucinated, information. Firms should develop policies around the use, review and editing of content that AI creates to ensure that the information is accurate and relevant. Solutions providers like Wolters Kluwer, especially in industries that hinge on data accuracy such as tax and accounting, legal or healthcare, are training generative AI systems on closed data sources to ensure the accuracy of outputs and building in guardrails to eliminate hallucinated responses.  


Inaccuracies can have impacts beyond damage to the accountant’s professional reputation. As generative AI systems are implemented to make decisions in tax and accounting software, inaccurate or unfair outputs may cause faulty financial reporting, potentially leading to serious financial and legal consequences and opening firms to potential liability issues. Auditing and transparency mechanisms (such as citations) should be built into software to track decisions made by generative AI. 


Algorithmic bias may result in unfair outcomes, affecting certain individuals, businesses or situations unevenly with unforeseen ethical and legal implications. Efforts must be made to identify and reduce biases in training data, algorithm design, and decision-making processes.

The responsibility for overcoming challenges of accuracy, bias and liability lies both with the solutions provider and the professional using the software. Wolters Kluwer is committed to the development of responsible AI that is based on a foundation of trust, transparency and responsibility, as stated in our Artificial Intelligence Principles

The tax and accounting professional also has a duty to apply their skills and judgement to best serve their clients. AI may not capture every nuance of the complex needs of individual clients, and it cannot replace the partnership and personal touch a human advisor can provide. AI has unlocked new levels of efficiency, but outputs should be reviewed for accuracy.

Embracing AI to add value

Applying AI can unlock the door to working smarter, not harder, accurately and quickly completing tedious tasks and allowing tax and accounting professionals to use their time on bigger and better things, like strategy, collaboration, relationship management, technology, innovation and growth. 

AI can also change the landscape for accounting as a profession, reducing the time spent on mundane or repetitive tasks while lowering the likelihood of human error. This can potentially allow accounting and tax professionals to focus on the more human side of their work -- higher value thought processes and more nuanced decision making. A shift from drudgery to energizing work can contribute to better work-life balance and greater feelings of fulfillment and purpose.

While AI is changing how accounting professionals do their jobs, it can’t replace them. Learning how to leverage AI tools can help firms deliver value with speed and confidence. When humans and AI are aligned to support each other, firms can work more strategically, benefiting both themselves and their customers.

Back To Top