The Practical Guide to Implementing AI in Indirect Tax: Frameworks, Use Cases, and Best Practices

• Understanding AI in Tax Compliance: The guide emphasizes the shift from deterministic logic to probabilistic reasoning in tax technology, highlighting the need for tax leaders to understand how AI can enhance compliance while also introducing new risks. It explains the importance of measuring compliance through broader coverage rather than aiming for perfection in individual transactions.
• Practical Framework for AI Deployment: A three-tier framework categorizes tax processes based on their suitability for AI: determinism-critical (precise tax determination), hybrid (regulatory monitoring), and AI-advantaged (anomaly detection and fraud identification). The guide also outlines the necessity for strong controls, including confidence scores, explainability, human oversight, and governance frameworks to ensure compliance and build trust in AI systems.
• Implementation Roadmap: The guide provides a step-by-step roadmap for tax leaders, from educating teams about deterministic versus probabilistic thinking to mapping processes, establishing thresholds, and monitoring performance. It stresses strategic deployment of AI, focusing on areas where it can enhance efficiency and accuracy without compromising compliance.

This guide is intended for tax leaders seeking a structured approach to integrating AI into their indirect tax operations responsibly and effectively.