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Tax Tech & Innovation

Embracing AI in tax & accounting: 3 considerations for getting started

Nadya Britton  Enterprise Content Manager for Tax and Accounting at Thomson Reuters Institute

· 5 minute read

Nadya Britton  Enterprise Content Manager for Tax and Accounting at Thomson Reuters Institute

· 5 minute read

Tax & accounting professionals need to learn the basic steps of how to get started with AI in tax, by focusing on understanding AI, streamlining data processes, and preparing their data for AI integration

In an era where technology continues to evolve at what feels like an unimaginable pace, artificial intelligence (AI) has emerged as a transformative tool across almost all industries, including tax & accounting. The integration of AI into tax processes not only promises to enhance efficiency but also to provide deeper insights and improve accuracy. However, the journey to effectively leveraging AI and especially generative AI (GenAI) in the tax profession can appear daunting for many.

Step 1: Understanding AI and GenAI

Launched in late-2022, GenAI became the most talked about revolutionizing software throughout 2023. Although previous iterations of simple AI had been in place in our personal and business lives tangentially, the introduction of GenAI to the mainstream brought more advance used of AI into focus. For tax departments and professionals, the awareness of AI in their work process, if it existed at all before, was negligible — and for anyone who clicked on any article with AI in its title, both AI and GenAI seemed to be presented as a savior and boogieman of all types of professionals.

For tax departments and tax professionals, understanding how AI and GenAI will increase and, in many cases, solve for challenges that the tax profession faces, such as the pressures of hiring and retaining top talent, departments and firms being under-resourced, and keeping up with compliance. For understanding AI and GenAI in the context of tax workflow, it is necessary to understand what these advanced technologies can do and what problems it can solve in tax & accounting work — and just as importantly, what they can’t do and what problems they can’t solve.

Among tax firms and corporate tax departments, AI is already being used for a variety of tasks, such as automating data entry and classifying tax documents. With GenAI, these tasks can be expanded upon, to include, for example, assisting with predicting tax liabilities and providing decision support for tax planning.

Tax professionals seeking to better understand what AI and GenAI can look like for the work they do should look for resources tailored specifically to the use of AI in finance or tax, as these will provide the most relevant insights.

Step 2: The quality of the data

Before AI and GenAI can be effectively implemented, tax professionals and team leaders must consider the state of their organization’s data. How has it been managed, or not managed? Where is it stored? How is it accessed? And finally, what is the quality of that data?

The data with which most in-house tax departments works comes from various sources within the organization, including financial statements, invoices, receipts, and payroll records. After getting a grasp on the data that is available, it is then necessary to streamline it.

Streamlining data processes by increasing automation and then leveraging that through integrating systems, such as using an enterprise resource planning (ERP) program, can be extremely beneficial. If an ERP or something similar exists within the company (almost every company utilizes at least one program of this type), tax teams should investigate how the tax department may access and be incorporated into it. Use of this process would allow for data to flow smoothly between systems without the need for manual intervention, and also reducing errors and saving time.

Step 3: Getting data AI-ready

Whatever route is undertaken to start a tax department’s AI and GenAI technology enablement journey, one thing is clear: the AI systems require secure, standardized, and clean data to function properly. Garbage in, garbage out is a common adage in data science, and its emphasis on the importance of data quality is especially apt here. Inaccurate or inconsistent data can lead to incorrect AI outputs, which can be costly both reputationally and financially.

To get an organization’s data AI-ready, start by implementing data-cleaning practices to remove errors and inconsistencies. This may involve standardizing data formats, correcting inaccuracies, and de-duplicating records. It’s also important to establish data governance policies to maintain data quality over time.

Data security is another critical aspect of preparing data for AI. Tax data is sensitive and must be handled with the utmost care to comply with regulations such as the General Data Protection Regulation (GDPR) and the Sarbanes-Oxley Act (SOX). Ensure that the AI systems have robust security measures in place to protect against data breaches and unauthorized access.

Embarking on the journey of integrating AI into tax processes is a strategic move that can yield significant benefits. By educating the internal tax team and outside tax professionals on AI and GenAI, streamlining data processes, and ensuring any data to be used is AI-ready, tax professionals and tax departments can set the foundation for a successful AI implementation within their tax work. Remember, the field of AI and GenAI is continually evolving, so maintaining a culture of learning and adaptability is essential to staying ahead in the game.