## How AI Can Help Both Tax Collectors and Taxpayers

_IMF Blog, February 25, 2025_

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**Canonical URL:** [How AI Can Help Both Tax Collectors and Taxpayers](https://www.imf.org/en/blogs/articles/2025/02/25/how-ai-can-help-both-the-taxman-and-the-taxpayer)

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## Bibliographic details
- Authors: Thomas Cantens, Herve Tourpe
- Published: February 25, 2025

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### Overview
- New generative AI tools can redefine the relationship between governments and citizens, but strong leadership and safeguards are fundamental.
- Authors: Thomas Cantens, Herve Tourpe
- Date: February 25, 2025
- Generative artificial intelligence (GenAI) goes beyond simple automation by understanding and producing human language, opening possibilities for both internal administration support and external taxpayer interaction.
- Early GenAI applications have focused on improving communication with taxpayers; most efforts by tax authorities remain at an early, experimental stage.

### What’s new with GenAI?
- Distinction from existing AI:
  - Most current systems used by tax and customs authorities are predictive and built for a single function, analyzing structured data to produce outputs such as risk scores.
  - GenAI is a generalist system that understands almost all forms of information and is designed to interact with humans in any language.
- Capabilities:
  - Drafting letters, providing interactive guidance about tax regulations, assisting officers in investigations.
  - Can be trained with legal texts, tax codes, operating procedures, and internal guidelines to create a dynamic system for both civil servants and taxpayers.

### Transforming the State–Society Relationship
- Internal effects:
  - GenAI can help tax and customs officials focus on analytical and judgment-based roles, enabling them to become oversight specialists and increasing productivity.
- External effects:
  - GenAI can reduce the knowledge gap between administrations and taxpayers by aiding interpretation of complex provisions, navigating laws, identifying deductions, and auto-filling forms.
  - Human-like interactions can personalize taxpayer service, as illustrated by:
    - Singapore: a virtual assistant answers tax questions in multiple languages and has cut call-center inquiries by half.
    - Korea: an AI guide helps citizens file and pay taxes.
    - France: AI can analyze incoming emails and propose draft responses for civil servants to validate.
- Opportunities for low-income countries:
  - GenAI offers a path to drive organizational reforms and leapfrog into modern systems.
  - Example: Madagascar’s customs authority intends to use GenAI to improve risk management, combat fraud and increase revenue, using data accumulated over 10 years to train its system.
- Civic engagement:
  - Citizens’ organizations, academics, and political parties can use GenAI to examine proposed reforms, compare scenarios, and engage in deeper policy debates, potentially increasing trust and making taxation feel more like a shared responsibility.

### Preconditions for success and challenges
- Data and knowledge requirements:
  - Effective knowledge management is essential; revenue authorities must identify accurate, relevant, and suitable documents from extensive laws, regulations, case records, and operational manuals.
  - Scattered archives and incomplete digitization can hamper training efforts.
- Human oversight and workforce readiness:
  - A human must determine which documents are appropriate for training.
  - Employees need training to interpret, correct, and complement GenAI outputs.
  - Policymakers must ensure that errors are reported and addressed promptly.
- Risks to trust and necessary safeguards:
  - Issues include data quality, ethics, privacy concerns, and hallucinations (i.e., incorrect results).
  - Results must be explainable and perceived as fair.
  - Sensitive queries may need routing to human agents (as in Korea) to preserve confidentiality and oversight.

### Policy recommendations and governance considerations
- Leadership and governance:
  - Strong leadership and ethical policy frameworks are fundamental to shaping GenAI properly in revenue administration.
- Data governance and privacy:
  - Vigilant oversight of data quality, privacy, and accuracy is required to reinforce — not erode — trust.
- Operational safeguards:
  - Design systems so particularly sensitive matters are handled by humans.
  - Implement procedures to report and fix errors promptly.
- Capacity building:
  - Train staff to use GenAI outputs critically and to manage the systems’ knowledge bases.
- Inclusive deployment:
  - Use GenAI to lower administrative hurdles, clarify tax obligations, and invite broader participation in policy debates while maintaining legal and ethical standards.

*IMF Blog post: "How AI Can Help Both Tax Collectors and Taxpayers" — Thomas Cantens and Herve Tourpe, February 25, 2025.*

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_Source: https://www.imf.org/en/blogs/articles/2025/02/25/how-ai-can-help-both-the-taxman-and-the-taxpayer_