Digital goes international: From manual repetition to AI-enabled compliance

For decades, tax compliance was a labour-intensive exercise. It’s important to note that these established processes often resulted in accurate and timely filings, and value-added strategic work still took place. Finance and tax teams, however, wrestled with a deluge of transactional data, often residing in disparate systems or captured within vast Excel workbooks.

This traditional approach was typically characterised by:

• Manual data extraction and entry, with information from invoices, receipts and ledger accounts manually extracted, reconciled and re-entered into spreadsheets or basic compliance tools. This was not only tedious but also susceptible to human error
• Spreadsheet dependency, with Excel as the primary tool for calculations and reporting. While flexible, complex models were prone to formula errors and version control issues, making audit trails cumbersome
• Disparate systems and data silos so that data often needed to be manually aggregated from multiple sources, leading to inconsistencies and no single source of truth

This old norm was marked by inefficiency and a constant drain on resources, making it difficult to keep pace with changing demands.

This traditional model was not inherently flawed, but its sustainability is now being tested. The growing pressure for more data from tax authorities and the increasing volume of regulation mean the old ways of doing things are often no longer scalable. Many teams today find themselves in a hybrid state – partially digital, partially manual, and aspiring to greater automation.

The last few years have seen an acceleration in the digitalisation of tax, driven by technology and a significant push from tax authorities worldwide. This is a direct response to global mandates demanding greater transparency and real-time data. We are now in a period of transition, where many organisations operate a hybrid model of manual and digital processes.

Key regulatory drivers forcing this evolution include:

• The Standard Audit File for Tax (SAF-T), an international standard for the electronic exchange of accounting data, requiring companies to provide detailed records in a structured XML format
• E-invoicing and continuous transaction controls (CTCs) mandates requiring the digital exchange of invoices, often in real-time, with the tax authority, shifting compliance from a periodic to a continuous process
• Global reporting frameworks, with new OECD-led initiatives increasing the data burden beyond indirect taxes. Pillar 2 requires large multinationals to perform complex calculations to ensure a 15% minimum tax is paid in every jurisdiction, demanding extensive data gathering and reporting through a GloBE Information Return (GIR). At the same time, the Crypto-Asset Reporting Framework (CARF) and updates to the Common Reporting Standard (CRS 2.0) are expanding automatic information exchange to cover digital assets and new forms of e-money, requiring service providers to collect and report vast amounts of user transaction data

These mandates compel businesses to enhance their internal data management, mirroring the increased use of data science by tax authorities, who are leveraging technology to find anomalies in the data they receive.

Integrating AI and machine learning (ML) is the new frontier in compliance’s digital development. This technology is poised to redefine how tax teams operate, shifting their focus from data processing to higher-value strategic activities.

One of the most promising applications is in the analysis of nominal ledger data, which is foundational for everything from VAT returns to calculating corporate tax provisions. Generative AI can transform this:

• Automating anomaly detection through AI trained to learn normal patterns in transactional data. It can then scan all transactions to flag unusual entries that might indicate errors or misclassifications relevant for tax purposes
• Generating contextual insights, with AI providing narrative explanations for flagged anomalies by pulling related documents and historical data, significantly reducing investigation time
• Automating reconciliation and categorisation of large datasets and transactions, speeding up financial close processes

The trajectory towards greater automation is clear, but it is wise to approach timelines with caution. Experience shows that technological adoption in the corporate world can be slow. Publications as early as 1999 discussed the imminent rise of “internet-hosted” tax software. Two decades later, many major software firms are still working to fully achieve this vision.

With that caveat in mind, here is an aspirational view of the next decade:

• In the next two years, we anticipate wider adoption of AI for routine tasks like data validation and basic anomaly detection. The focus will be on improving data quality, as AI is only as good as the data it consumes. More countries are likely to expand e-invoicing and real-time reporting mandates
• In the next five years, the trend suggests a move toward predictive compliance, where AI can anticipate potential issues before they arise. Tax processes will likely become more seamlessly integrated into core business systems, embedding compliance into daily operations
• In the next ten years, it is conceivable that routine tax compliance will be almost entirely automated, with human oversight reserved for complex exceptions and strategic planning. Businesses may have a near real-time global view of their tax positions, and the tax professional’s role will have fully evolved into that of a data-fluent strategist and AI ethicist

The journey from manual-heavy tax compliance to an AI-powered future is a fundamental redefinition of the tax function. The days of painstakingly sifting through nominal ledgers in isolated spreadsheets are ending.

For businesses, embracing this transformation is essential for managing the escalating complexity of global tax regulations, mitigating risk and freeing up valuable resources.

For tax professionals, it presents an opportunity to evolve from transactional duties to become indispensable strategic advisors. Those who adapt proactively, invest in digital tools and cultivate data-driven skillsets will not only survive but thrive in this new era of tax compliance.