The global regulatory environment is undergoing a profound transformation. Measures such as the OECD’s Pillar Two, the European Union’s Corporate Sustainability Reporting Directive (CSRD), and a growing number of local initiatives are reshaping how companies must collect, process, and disclose information. For multinational organizations, this creates a reality in which reporting obligations are expanding, data requirements are intensifying, and the risks of inconsistency or non-compliance are growing. At the same time, tax, finance, and sustainability teams increasingly find themselves working with overlapping datasets, making coordination and reliability more important than ever before.

Against this backdrop, the traditional reliance on manual processes—often driven by Excel spreadsheets—is proving inadequate. Manual approaches struggle to cope with the fragmented nature of global data flows, the sheer volume of information, and the precision required to reconcile reporting across jurisdictions. The result is inefficiency, heightened compliance risk, and a missed opportunity to turn data into meaningful insights.

This article was written by Mario van den Broek ([email protected]) and Iman Zalinyan ([email protected]). Mario and Iman are consultants with RSM Netherlands Business Consulting, focusing on supply chain management.  

The shift towards automation

Automation has become the essential response to these challenges. Technology-enabled solutions can extract and validate data from multiple systems, ranging from ERP and finance platforms to external sources, and consolidate this into a single source of truth. They can perform the complex calculations required under Pillar Two with a level of accuracy that manual methods cannot match. They also generate mandatory reports, such as the GloBE Information Return, while maintaining a transparent audit trail that strengthens governance and facilitates dialogue with tax authorities.

The value of automation, however, extends far beyond compliance. What makes this shift transformative is the convergence of fiscal, supply chain, and sustainability obligations. Increasingly, the same information that is required for tax reporting is also needed for sustainability disclosures. The location of production facilities, the structure of legal entities, and the flow of goods and services through global supply chains determine not only effective tax rates but also carbon footprints and environmental exposures. An integrated software platform enables the elimination of duplication, enhances consistency, and fosters a holistic perspective that connects tax, finance, and sustainability reporting.

The role of Artificial Intelligence

Artificial Intelligence is accelerating this convergence. AI-enabled analytics can identify anomalies in tax data, predict risks, and simulate the impact of regulatory changes before they materialize. In supply chain management, AI can optimize routes and sourcing decisions by weighing costs, carbon emissions, and tax exposure in real-time. In sustainability reporting, machine learning can process vast amounts of supplier data, detect inconsistencies, and calculate emissions across Scope 1, 2, and 3 categories with far greater speed and reliability than traditional methods. The integration of AI transforms automation from a passive tool for compliance into an active driver of strategy, capable of not only highlighting what has happened but also predicting what is likely to happen next.

This shift is already reshaping how companies make decisions. Supply chain optimization, for example, is no longer assessed solely on logistics efficiency. With AI-powered tools, companies can evaluate whether relocating production reduces emissions, lowers effective tax burdens, and improves long-term resilience. Similarly, sustainability compliance is evolving beyond mandatory reporting. Automated and AI-supported systems enable organizations to anticipate the financial impact of carbon taxes or environmental levies and to incorporate these considerations into strategic planning.

Strategic implications for global organizations  

For global organizations, the implications are profound. Automation reduces dependence on manual processes, creating efficiency and freeing resources for higher-value tasks. It strengthens risk management by ensuring accuracy, minimizing human error, and providing an auditable trail of decisions. When combined with AI, it also delivers foresight—helping organizations anticipate risks, simulate scenarios, and align business strategies across tax, finance, and ESG dimensions. Most importantly, it ensures alignment between compliance requirements and broader corporate objectives, enabling decision-makers to evaluate financial, environmental, and reputational impacts in an integrated manner. By building this digital infrastructure now, companies prepare themselves for the next wave of regulation while simultaneously equipping themselves with tools that enhance competitiveness.

Forward Thinking  

The convergence of tax, supply chain, and sustainability is not a passing trend but a defining characteristic of today’s business environment. Companies that persist with manual processes will remain reactive, constantly scrambling to keep pace with evolving demands. Those that invest in automation and AI position themselves differently: not only compliant but strategically empowered, using their regulatory data as a foundation for better decisions and long-term value creation.

Automation and AI are no longer optional technology projects. They are cornerstones of corporate transformation. They represent the bridge between compliance and competitiveness, enabling organizations to respond effectively to immediate regulatory pressures while unlocking opportunities for efficiency, resilience, and growth. For companies navigating this complex convergence, the question is no longer whether to embrace automation and AI. The real question is how quickly they can integrate these tools into the heart of their operations.

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