A paradigm shift: AI embedded in Tax

The fast-paced regulatory and economic environment today has been pushing tax teams of organizations to deliver accurate and timely strategic insights, in addition to mandatory tax reporting functions. This has triggered a paradigm shift, from the traditional focus on tax compliance and reporting across various laws and jurisdictions, to donning the mantle of a core contributor and of being involved in the strategic decision-making process of an organization.

Historically, tax teams focused on tax compliance and reporting, with the processes largely being manual. In this context, Revenue authorities have surprisingly been ahead of taxpayers in the implementation of technology in tax and have been the catalyst in adoption of tax technology by organizations. What started with use of limited technology for compliance and reporting to meet regulatory requirements, has now transformed into tax teams harnessing data and using artificial intelligence (AI) in their day-to-day functions.

This has changed the avatar of the Tax function, from being a ‘back office’ department to rapidly becoming a key element of strategic decision-making for an organization – right from introducing a new product, setting up a new line of business to acquisition of a target company.

Data lies at the core of tax processes – from GST and tax deduction at source / withholding tax, which are transaction taxes and are data-heavy, to complex tax calculations that rely on onerous data. The first stage of transformation was in moving from manual processes to the use of automation and technology; we are now in the second stage of transformation with AI being embedded into these tax processes.

AI models are being used by tax professionals to operate, deliver value, and to plan for the future. The use of AI enables tax teams to derive strategic insights, which make them a cogwheel in the organization. Some of the areas where AI has been playing a key role in tax, are discussed below.

• Data visualization

One of the base use cases of AI / analytics is sophisticated analysis of large sets of financial and tax data to generate detailed reports as well as dashboards, which enables management to understand the data in a meaningful way and obtain key insights from historical data. It is a key tool to identify what went wrong and what worked well to enable decision-making. This also forms a strong basis for predictive analysis.

• Predictive analysis

The use of AI enhances the ability of Tax teams to analyze vast amounts of data at lightning speed with accuracy, which enables predictive analysis. The use of AI helps to identify patterns and trends that may not be apparent to an individual – this enables Tax teams to garner insights from historical tax data, which in turn, is useful to identify any tax optimization opportunities. Predictive analysis also helps in tax forecasting and budgeting, including providing reliable estimates of tax liabilities to ensure that the business manages cash flows and avoids any under or over payment of taxes.

• Supply chain

While historically supply chain has always been considered as largely a logistics issue, organizations have realized that embedding taxes, especially GST, are a critical element in supply chain. The use of AI and large amounts of data, including tax data, help organizations to optimize taxes and / or to ensure that there is no or minimal leakage of tax. This contributes significantly to the organization’s effectiveness.

• Setting up of operations

The setting up of, say, a new manufacturing plant is a significant event in an organization’s calendar. Here again, tax plays a very important role in generating insights for decisions making –ranging from location of the plant, acquisition of machinery, to the setting up and operationalization of the plant. One such example is analyzing tax incentives in various states based on modeling of future operations to determine the quantum of incentives across locations.

• Scenario modeling

The use of AI driven data analytics supports scenario modeling significantly. The use of data helps Tax teams simulate the tax impact of different business decisions and predict the corresponding tax outcomes. As an example, a Tax team can predict the impact of any potential acquisition on the requirement to pay additional taxes under the Pillar 2 / GloBE rules. This is crucial for business to make informed decisions, particularly in uncertain economic climates, and achieve the best possible financial outcomes.

• Risk sensing

Risk management is something that organizations cannot afford to overlook, especially when it is related to tax regulations. The use of data, analytics and AI can help identify tax risks at an early stage, which enables organizations to take proactive actions. Such risks could be around cash flows and in blocking of funds or could relate to potential tax outflows requiring provisions and impacting profitability.

Beyond the above, an interesting use case of AI is developing in the tax world. One of the prominent ones is around analysing of tax implications on receipt of an invoice itself so that tax is appropriately captured and recorded. The next step in the process is data wrangling and reconciliation, which can ultimately lead to near real-time tax reporting.

This will be critical once the government introduces Standard Audit File for Tax (SAF-T) for both direct and indirect tax. SAF-T is an OECD initiative for standardization of tax reporting, that encompasses creation of a data file containing transactions in a prescribed format for Revenue authorities; this is a key element in real-time tax reporting.

The next big thing in the Tax world is the use of Generative AI (GenAI), which has transformed businesses, especially since ChatGPT took the world by storm. The use of GenAI has several use cases in tax. Some of the ‘basic’ ones include:

• Conversations with tax documents using chatbots
• Preparation of summaries of tax cases
• Extraction of data points from tax notices

While the above use cases will aid Tax teams, what will revolutionize tax work is the use of AI / GenAI for tax research. Tax research process is fairly cumbersome, involving long searches of tax documents, reading of multiple documents and judicial pronouncements to identify the relevant ones, etc. All of this generally takes hours or even days, even for experienced tax professionals. With the use of AI / GenAI, the search process can be sharpened significantly to bring in focussed and contextual search results, leading to reduction in time and efforts and in making the process less cumbersome.

Once the tax research is complete, the next step is to document the search results. This task can also be carried out with the help of GenAI. GenAI can help analyze, categorize and document the search results, transforming the way in which tax professionals operate.

The possibilities for the use of AI / GenAI in tax are multifold. These technologies can be used to, say, determine the Harmonized System of Nomenclature (HSN) of products and services for classification purposes. Another example could be in determining tax deduction at source / withholding tax for transactions with vendors. For an organization operating in multiple jurisdictions, AI / GenAI can provide real-time insights on the impact of changes or updates to tax regulations across several geographies.

Embedding AI / GenAI in tax is no longer optional—it is an imperative. As the technology matures, organizations, regardless of size, will have to embrace AI / GenAI to better position themselves to adapt to various regulatory changes, meet expectations of stakeholders, and drive sustainable growth for their organization. The future looks exciting and the possibilities, endless, especially with agentic AI on the horizon for tax.

By Pritin Kumar (Partner), Dishank Lotia (Associate Director) at Deloitte Touche Tohmatsu India LLP. The views expressed herein are personal.