# Addressing AI Risks in Tax Administration for Sustainable Governance

> This framework highlights the critical balance between the opportunities AI presents and the inherent risks in tax administration, emphasizing the need for a structured approach to ensure responsible adoption.

**Source**: thetaxadviser.com | **Published**: 2026-08-31 | **Type**: article

## Key Facts

- Tax authorities face high-stakes AI risks; misalignment can lead to legal and financial harm.
- AI's potential in tax is vast; 20 risk areas highlight critical governance needs for adoption.
- Erosion of human expertise is a vulnerability; reliance on AI could weaken institutional capacity.
- Client trust may erode if AI errors occur; transparency in AI use is crucial for firm reputation.
- Regulatory noncompliance risks increase with AI; firms must ensure adherence to professional standards.

## Summary

A recent article outlines a critical framework for the responsible use of artificial intelligence (AI) in tax administration and preparation, developed by a former IRS commissioner. This framework is essential as it addresses the significant risks associated with AI implementation in a sector that is inherently complex and high-stakes. As organizations increasingly adopt AI to enhance productivity and efficiency, the need for a structured approach to mitigate potential pitfalls becomes paramount.

The tax sector is uniquely positioned for AI integration due to its reliance on deterministic logic, extensive historical data, and a well-defined regulatory framework. However, the risks associated with AI in this domain are profound. Missteps can lead to legal repercussions and financial losses at scale, underscoring the necessity for a robust risk management strategy. The article emphasizes a common sentiment among tax professionals: while there is recognition of AI's transformative potential, there is also uncertainty regarding the associated risks and the questions that need to be addressed for responsible adoption.

To facilitate better governance, the article proposes two distinct risk registers—one for tax authorities and another for tax preparers. Each register categorizes risks into specific areas, allowing organizations to systematically identify, assess, and mitigate potential issues. For tax authorities, the risks include information integrity, fairness, security, and institutional capacity. For tax preparers, risks cover technical failures, legal liabilities, and the erosion of client trust. This dual approach not only aids in understanding the risks but also provides a framework for developing best practices and sharing insights across the tax community.

The proposed risk framework is grounded in established risk management principles, such as the COSO Enterprise Risk Management model, and is designed to evolve as the AI landscape changes. The framework encourages organizations to define risks, assign controls, and create indicators for ongoing assessment. This proactive stance is critical as it allows tax authorities and preparers to navigate the complexities of AI deployment while safeguarding against potential failures.

One of the key insights from the framework is the recognition that risks often present simultaneously and can be interdependent. For instance, enhancing transparency in AI systems can reduce explainability risks but may simultaneously increase vulnerability to adversarial manipulation. This nuanced understanding of risk dynamics is essential for effective governance and highlights the need for a tiered approach to risk prioritization.

The implications for market participants are significant. As tax authorities and preparers adopt these frameworks, they will likely foster a more responsible and informed approach to AI integration. This could lead to increased public trust in tax systems and improved compliance rates, as stakeholders feel more secure in the integrity of AI-driven processes. Moreover, organizations that successfully implement these frameworks may gain a competitive edge by demonstrating their commitment to responsible AI use.

Looking ahead, the establishment of these risk frameworks signals a shift in the tax landscape, where AI can be leveraged not just for efficiency but also for enhanced accountability. As the tax community continues to grapple with the complexities of AI, those organizations that prioritize robust risk management will be better positioned to navigate the challenges and capitalize on the opportunities presented by this transformative technology. The evolving regulatory environment and public scrutiny will further necessitate that tax professionals remain vigilant and adaptive in their AI strategies, ensuring that both innovation and responsibility go hand in hand.

## Entities

- **Products**: AI products
- **Technologies**: artificial intelligence, machine learning, natural-language processing
- **People**: former IRS commissioner
- **Organizations**: IRS, IBM Center for the Business of Government

## Key Concepts

AI risk framework, tax administration, risk registers, responsible AI adoption, information integrity, fairness and legitimacy, security and data, institutional capacity

## Definitions

- **AI risk framework**: A structured approach to identify, assess, and manage risks associated with the deployment of artificial intelligence in specific domains.
- **risk register**: A tool that lists potential risks along with their descriptions, controls, and indicators to help organizations manage risk effectively.
- **hallucination**: A phenomenon where AI generates confident but factually incorrect outputs.
- **over-trust**: The tendency of users to treat AI outputs as authoritative without sufficient human verification.
- **client trust erosion**: The loss of confidence clients have in a service provider, often due to undisclosed use of AI or errors stemming from AI outputs.

## Use Cases

- audit selection tools
- pattern detection
- machine-learning-driven screening
- chatbots for tax inquiries
- AI-assisted tax preparation
- risk assessment for AI deployment

## Frequently Asked Questions

**What is the purpose of the AI risk framework in tax administration?**

The AI risk framework aims to help tax authorities and preparers identify and manage risks associated with AI deployment, ensuring responsible adoption and minimizing potential legal and financial harms.

**How does the risk register assist organizations?**

The risk register provides a structured list of risks, their definitions, and controls, enabling organizations to assess their readiness for AI adoption and conduct due diligence on AI products.

**What are some key risks identified for tax authorities?**

Key risks include information integrity issues like hallucination and drift, fairness concerns such as audit targeting, and security risks like data leakage and adversarial manipulation.

**Why is it important to prioritize risks in AI deployment?**

Prioritizing risks ensures that organizations address the most critical issues before deployment, which helps prevent significant legal and operational consequences associated with AI failures.

**What challenges do tax preparers face with AI use?**

Tax preparers face challenges such as malpractice exposure, client trust erosion, and the risk of relying too heavily on AI outputs without adequate verification, which can lead to downstream errors.

## Links

- [Read on Welcome.AI](https://welcome.ai/content/addressing-ai-risks-in-tax-administration-for-sustainable-governance)
- [Original source](https://www.thetaxadviser.com/issues/2026/aug/a-risk-framework-for-ai-use-in-tax-administration-and-preparation/)

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Source: Welcome.AI | https://welcome.ai/content/addressing-ai-risks-in-tax-administration-for-sustainable-governance