Artificial intelligence (AI) is constantly evolving, with new breakthroughs like Agentic AI empowering accounting and tax professionals to work smarter, automate complex tasks, and grow.
In the Wolter Kluwer Future Ready Accountant Report, we see that 27% of firms are already using AI tools as part of their workflow, and another 22% plan to do so within the next year. It’s already making a big difference in the firms embracing AI.
Understanding AI and its role in accounting
Artificial intelligence is ushering in a new era for tax, accounting, and audit professionals, one where humans and technology work together to deliver deeper insights, better client experiences, and more meaningful work. Rather than simply automating routine tasks, the latest advancements, including agentic AI, are enabling professionals to collaborate with intelligent systems that adapt, learn, and assist in complex decision-making.
To take full advantage of these opportunities, it’s essential to understand what AI is—and how it’s redefining the future of the profession.
What is AI?
In broad terms, AI is technology that helps computers gather information and find solutions in ways that imitate human thinking. AI uses data to learn – the more data it has, 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, large language models, and agentic AI. 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™ Audit 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 recently become one of the most talked-about examples of generative AI, 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.
GenAI has grown consistently in its sophistication and output. Recent advances make results more realistic, higher quality, and more human-like.
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.
Some AI systems now use retrieval-augmented generation (RAG), which combines the power of LLMs with real-time data retrieval. This enables AI to search trusted sources for up-to-date or domain-specific information before generating a response. Small language models (SLMs) are also becoming popular for their efficiency and performance in niche tasks. They require less computing power and can be fine-tuned for specialized workflows, making them a practical option for firms with specific needs.
Agentic AI
The result? AI transforms from being a support tool to a collaborative approach to serving clients. Firms that adopt Agentic AI gain the capacity to provide smarter, faster, and more tailored services, positioning themselves ahead in a competitive market.
How AI is already making an impact in tax and accounting
Advancements in machine learning and generative AI are impacting the tax and accounting industry in profound ways. Key areas of focus include:
- Tax research
- Streamlining data entry
- Identifying tax advisory opportunities
- Strengthening customer relationships
- Improving retention and recruiting
Streamline 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.
Streamlining data entry and document review
Tax and accounting professionals are inundated with vast amounts of client data ranging from general ledgers, journal entries, employee records, and banking records to unsorted digital and physical “shoeboxes” of supporting documents. Gone are the days when entry-level CPAs must spend hours of their time manually sorting, cleaning, entering, and reviewing client information before the tax return or audit can be started.
Artificial intelligence technology, like computer vision and machine learning, now makes it possible to automate the data ingestion process, saving professionals hundreds of task hours every year. In minutes, AI-powered document processing technology can scan even the lowest quality, unstructured documents and then extract, identify, organize, and import the data into the relevant forms within the tax, accounting, or audit solution. AI is also able to flag data or fields that may need additional human verification.
The ability to automate the handling of client files and data entry has made the concept of the no-touch tax return possible. Within the scope of an audit, AI can instantly match and link source
Identify tax advisory opportunities
49% of high-growth firms are more likely to offer advisory services as a core offering.
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.
Strengthen customer relationships
AI enables firms to offer proactive and personalized services while spending less time managing accounts and correspondence. Conversational AI tools, like chatbots and virtual assistants, can guide clients to the answers they need faster, whether they’re asking about filing deadlines, account information, or specific tax scenarios. AI can also automate the creation of personalized communications, such as client letters that explain complex tax issues in clear, simple language. This allows professionals to focus on higher-value client interactions while still delivering timely, tailored insights.
Improving retention and recruiting
The accounting profession's global talent gap is affecting firms of all sizes, with small, midsize, and large firms all identifying retention and recruitment as their biggest challenge. By automating time-consuming tasks such as data entry, document management, and reporting, AI frees up professionals to engage in more strategic activities that require their expertise. This shift from tedious to engaging work contributes to a better work-life balance and greater feelings of fulfillment and purpose. It can also be a remedy to reduce burnout and turnover.
This integration of advanced technology is helping shift the perception of the industry and attracting tech-savvy professionals.
Challenges and concerns with AI in accounting
While AI has many advantages, it also presents concerns specific to the accounting industry. Firms should develop policies around the use, review, and editing of content that AI creates to ensure that the information is accurate and relevant.
There’s work to do here. Our analysis shows that only 25% of firms have a formal policy for AI usage and management. Of those that do, 84% of professionals say they feel positive about adopting AI. At firms without AI policies, only 44% feel that way.
Formal policies help safeguard your data and encourage adoption by team members.
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.
Security is non-negotiable and requires adopting zero-trust security frameworks and established data governance and privacy policies.
One concern is how LLMs may inadvertently retain, reproduce, or infer confidential information from training data. “Walled gardens” isolate firm data from broader AI training pools. These controlled environments help ensure that AI tools can access necessary data for insights without compromising privacy or regulatory compliance.
Wolters Kluwer trains AI systems on closed, proprietary data to ensure outputs are accurate and compliant with professional and regulatory standards. These controlled models also allow for better tracking of how AI makes decisions, producing greater transparency in automated systems.
Accuracy
The accuracy of AI-generated information is another concern. Generative AI cannot guarantee the perfect accuracy of the content it creates. Many public generative AI solutions, like ChatGPT, generate outputs based on patterns in the data on which they were trained. This has led to some very public examples of generative-AI-created content containing made up, or hallucinated, information. While models are improving constantly, you cannot afford even small inaccuracies.
Wolters Kluwer trains generative AI systems on closed data sources to ensure the accuracy of outputs and builds in guardrails to eliminate hallucinated responses. Our solutions also have built-in auditing, transparency, and citations.
Embracing AI to add value
More than half of firms expect the emergence of AI and GenAI to have the greatest impact on the profession.
Applying AI can unlock the door to working smarter and accurately, 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 isn’t replacing accounting professionals. It’s empowering them. By leveraging AI tools, firms can streamline routine tasks, free up time for higher-value work, and spend more time with clients. When professionals and AI work in tandem, the result is a more strategic, efficient practice that elevates the professional role and delivers an enhanced experience for clients.
