The dichotomy of digital technology for indirect tax

The march of technology is constant

Today’s rapidly advancing digital tax technologies continue to evolve into an ever more precise and powerful toolset for automating, improving, and generally transforming the way organizations manage the indirect tax process.

Tax professionals may use tools like robotic process automation (RPA), artificial intelligence (AI), and machine learning to better manage a host of indirect tax processes—from sales tax reconciliation to exemption certificate and tax credit management.

But there’s another side to digital technology’s impact on indirect tax: the technology itself is increasingly becoming a focus of indirect tax—including sales tax—from a growing number of state tax regimes.

Think of it as two different lenses on the same digital landscape. The first lens, digitization of the indirect tax lifecycle, behaves like a laser—innovative, focused, and precise, with efficient and predictable results. The second lens, indirect taxation of digital technology, acts like a prism producing uncertain, complex, and rapidly evolving taxability challenges.

How digital technologies are transforming indirect tax management

In recent years, digital technology has made a pronounced impact on the traditional challenges of indirect tax management including improving: difficult manual processes; data accuracy; data reconciliation; and provision and compliance process integration. Digital technology has also helped tax practitioners stay ahead of challenges arising from today’s increasingly complex indirect tax environment. These complexities include increasing volumes of data from multiple sources, the accelerating speed of rule changes and variability in how states adopt them, and the need for tax professionals to serve as business advisors by providing better strategic insights using modern analytics and modeling capabilities.

Fortunately, tax departments can use evolving digital technologies in more strategic ways to bring greater precision to indirect tax management in the form of more accurate data and faster, more efficient processes.

• RPA is a powerful digital technology that works in conjunction with other tax technologies like extract, transform, load (ETL), data wrangling, and analytics to streamline a host of indirect tax management processes. Using this combined toolset, for example, tax professionals can run consistent analytics on a set of data, period over period, to understand trends and improve process controls and transparency.
• Extract, transform, load (ETL) and data wrangling tools automate and streamline indirect tax data extraction, quality checks, validations, and preparation. These technologies work together with RPA to automate the process of pulling data from an ERP system and a wide range of other data sources directly into the indirect tax workflow. These tools can also simplify ERP and tax engine system maintenance by automatically running checks and providing alerts about when to perform support tasks—increasing system accuracy and decreasing risk.
• Optical character recognition (OCR) is an example of a technology that has evolved through integration with newer technologies and data processing techniques to become an even more sophisticated tool for improving indirect tax processes. OCR now leverages tools like machine learning to improve accuracy in extracting data from invoices, receipts, and other tax documents, allowing this data to enrich other data sets and be used within indirect tax management systems, which can substantially reduce errors and save considerable time.
• AI and machine learning tools have garnered increasing attention for their ability to sift through vast amounts of data at remarkable speeds and come up with valuable insights that build on previous analyses. Many tax professionals are using these tools in the indirect tax process to automate data trend analysis and anomaly detection, as well as to create system pointers for more efficient exemption certificate and tax credit management, among other applications.
• Dashboards and analytics. Data analytics tools enable tax professionals to perform sophisticated analyses on indirect tax data to deliver strategic insights to business leaders. Dashboards enable users to visualize data graphically for faster and easier trend analysis. These tools also shift the focus of trends and insights from a historic viewpoint to a prospective or future-looking viewpoint by running increasingly sophisticated predictive modeling scenarios that produce actionable insights.
• Indirect tax compliance software. These software tools can streamline goods and services tax (GST), sales tax, excise tax, and value-added tax (VAT) compliance with automated tools and real-time rates. They can also integrate provision and compliance and improve audit support and process scalability by providing data reconciliation, adjustment, and reporting capabilities.

Preparing for increasing indirect taxation of digital technology

The same digitization trends that are simplifying and improving the indirect tax life cycle may also be prompting states to change the products and services that they consider taxable. Historically, states have imposed sales tax on the sale of tangible personal property and a limited number of enumerated services. However, as digital technology and automation continue to expand, more jurisdictions are imposing sales tax—including digital advertising sales tax and data processing services tax—on technology-based products and services, creating challenges around indirect tax characterization, sourcing, and taxability on a jurisdiction-by-jurisdiction basis.

Digital goods like music, movies, eBooks, and online magazines are considered tangible personal property in many jurisdictions and are therefore may be taxable in those jurisdictions. Other digital products and services, such as apps or in-app purchases and gaming, can be even more unclear from a sales tax perspective.

Another complex area is digital business services, including data processing, digital code (including APIs), digital advertising services, e-mail tracking services, and cloud-based "as a service” products where the true object of the transaction may be unclear. In these scenarios, it can be difficult to determine the proper characterization of these services for sales tax purposes, and the interpretation of the true object of the transaction could vary by state.

Consider two examples of how states have recently applied sales tax to digital technology—one taxable and one not taxable.

Reconciling the dichotomy of digitization for indirect tax

The precision, clarity, and efficiency enabled by indirect tax digital technology may help tax departments better manage the uncertain and fast-moving environment of state governments imposing indirect tax on digital technology. For example, tax departments can use AI, ETL, analytics, and dashboards to monitor and track if and how SaaS is taxed in each state. When analyzing invoices, tax professionals can use this guidance to understand how to characterize and determine taxability of SaaS products.

¹ Texas Court of Appeals, Hegar v. Black, Mann, & Graham LLP; No. 03-20-00391-CV; No. D-1-GN-19-001725)
² In the Matter of the Petition of Yesware Inc., DTA No. 829638, (N.Y. Div. Tax. App. Sept. 29, 2022)

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