Data cleansing and analytics
Generative AI (GenAI) could simplify data management for tax leaders. Large language models (LLMs) can sort, summarise and analyse large volumes of structured and unstructured data such as invoices, tax reports and customer records much faster than humans.
Using algorithms, businesses will be able to more easily gather and integrate data from different sources, formats and structures, as well as tag and categorise it by content.
AI will also be able to “cleanse” that information faster, finding and fixing flaws, inconsistencies and duplication, while using predictive modelling to fill in gaps and missing records.
All of this will make a company’s tax and finance data significantly more usable for decision-making. AI-powered analytics will also be able to find trends, correlations and patterns hidden inside datasets, helping organisations anticipate opportunities and risks and make more proactive decisions.
Compliance
Better control over data will also be key to helping tax and finance leaders reduce the compliance burden. Meeting tax laws and regulations is an ongoing challenge, particularly for businesses operating across borders, as rules continually change, and regulators demand more transparency and financial information from businesses.
AI could bring efficiencies by transforming and consolidating company data, improving the quality of queries from source systems and identifying data anomalies and areas of potential risk.
“In compliance, AI monitors large regulatory databases, identifying potential irregularities in real-time, which mitigates risks and ensures adherence to regulations,” says Bas Kooijman, CEO of asset manager DHF Capital.
Tax authorities will likely begin harnessing AI to analyse tax data and returns, which could mean more regular requests and specific questions for businesses. The urgency to keep pace will therefore increase.
Income tax and accounting
The accounting industry already uses AI to drive huge productivity gains by automating key tasks to free up time for higher-value work. This is especially vital as tax and finance leaders say effective management of departmental budgets will be their number one priority over the next three years, according to the EY 2024 Tax and Finance Operations survey.
Today, finance departments deploy GenAI in several ways, including automating mundane tasks such as data entry, processing invoices and generating financial reports.
The Big Four accounting firms are also employing AI at a more advanced level in areas such as document review, where it is used to evaluate large volumes of contracts to extract key information, and the auditing process, where it helps to manage regulatory risk. AI technology is also used for coding and document generation. Additionally, it can be deployed in tailor-made client-side solutions.
Promising results from pilot projects suggest that algorithms will go even further in automating common accounting tasks, although the technology is expected to work alongside rather than replace workers. That is because AI cannot currently be substituted for the judgement, scepticism or experience that humans bring to the equation.
Planning
AI’s forecasting models can help companies identify risks and long-term trends, enabling more informed decision-making and reducing uncertainty in tax planning. Businesses can input data – such as regulatory laws, company performance data and corporate strategy – into an AI model to proactively generate tax recommendations.
For example, the AI model might highlight a regulatory change in Spain that affects telecom companies. It might then suggest ways to manage the tax implications. Alternatively, a company may want to alter its tax strategy to free up more cash: the AI could offer a series of recommendations to achieve that goal.
By automating more tax planning decisions, businesses should be able to free up time for higher-value tasks.
