AI Governance Policy Starter Kit | J.H. Randolph & Co.

Template only — requires legal review. This document is a draft framework. It must be reviewed and approved by qualified legal counsel before adoption as organizational policy. Requirements vary by industry, jurisdiction, and AI system risk tier.

Official sources

Use NIST and IRS source material when adapting AI governance controls for payroll.

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Section 1

Purpose and Overview

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1.1 Purpose

This policy establishes the governance framework for the deployment, use, and oversight of artificial intelligence (AI) systems within [Organization Name]'s payroll and human capital management operations. It is designed to ensure that AI tools used in payroll processing are deployed responsibly, transparently, and in compliance with applicable laws including the Internal Revenue Code, the Fair Labor Standards Act, and relevant state employment laws.

1.2 Policy Statement

No AI system shall autonomously make, execute, or finalize any payroll action that has regulatory, tax, or wage liability implications without documented human authorization. The employer retains full legal responsibility for all payroll outputs regardless of the AI tools used in their production.

1.3 Framework Alignment

This policy is aligned to the NIST AI Risk Management Framework (NIST AI RMF 1.0, January 2023), specifically the GOVERN function. It should be read in conjunction with the organization's existing information security policy, data privacy policy, and employment practices policy.

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Section 2

Scope and Applicability

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This policy applies to:

All AI and machine learning tools used in or connected to payroll processing, tax withholding calculation, time and attendance analysis, garnishment processing, or benefits administration
Generative AI tools (including LLMs) used to draft payroll policies, respond to employee inquiries about pay, or interpret regulatory requirements
Third-party AI vendors whose systems produce outputs that influence payroll decisions
All employees, contractors, and vendors who operate, configure, or receive output from covered AI systems

This policy does not apply to standard rule-based automation (e.g., if/then logic in payroll calculation engines without adaptive learning) unless such systems are marketed as AI or machine learning.

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Section 3

Definitions

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AI System

Any machine-based system that, given a set of objectives, makes predictions, recommendations, or decisions influencing real or virtual environments. Includes machine learning, deep learning, natural language processing, and generative AI.

Responsible Person

The named individual accountable for the outcomes of a specific AI-influenced payroll decision. For purposes of IRC §6672 TFRP analysis, this designation does not limit IRS authority to assess additional responsible persons.

AI-Influenced Decision

Any payroll action where an AI system's output was used as a basis for the action, even if a human reviewed and approved the AI output.

Human-in-the-Loop (HITL)

A control requiring a qualified human to review, approve, and document authorization before an AI-influenced decision is executed.

Trust Fund Taxes

Withheld employee income taxes and employee FICA contributions held in trust by the employer for remittance to the IRS. Misapplication of AI to withholding calculations creates direct IRC §6672 exposure.

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Section 4

Liability Ownership Matrix

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AI Function	Responsible Owner	Deputy	Regulatory Exposure
Tax withholding calculation accuracy	[Payroll Director]	[Payroll Manager]	IRC §6656 (FTD); §6672 (TFRP)
W-2 data accuracy	[Payroll Director]	[Tax Manager]	IRC §6721 (information return penalties)
Garnishment calculation	[Payroll Manager]	[Payroll Analyst]	15 USC §1673 (CCPA); state contempt risk
Direct deposit fraud detection	[Payroll Manager]	[IT Security]	NACHA rules; employer liability for fraud losses
AI vendor selection & oversight	[CFO / VP HR]	[IT Director]	Vendor liability gaps; third-party tax liability
AI incident response	[Payroll Director]	[Legal / Compliance]	All employment tax statutes
Policy maintenance & annual review	[CHRO / CFO]	[Legal Counsel]	Governance failure risk

Liability does not transfer to AI vendors. Even if an AI vendor's system produces an incorrect withholding calculation, the employer owes the under-withheld tax to the IRS. Indemnification clauses in vendor agreements are a secondary recovery mechanism — they do not protect against IRS FTD penalties or TFRP personal liability.

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Section 5

Permitted AI Use Cases

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Use Case	HITL Required?	Audit Trail Required?	Approval Authority
Payroll anomaly detection (flagging)	Yes — human reviews all flags	Yes	Payroll Manager
W-4 guidance chatbot (advisory)	Yes — disclaimer required; no tax advice	Yes	Payroll Director
Tax withholding calculation support	Yes — mandatory human sign-off before confirmation	Yes — immutable	Payroll Director
Predictive year-end W-2 accuracy review	Yes	Yes	Payroll Director
Direct deposit fraud scoring	Yes — human reviews blocked transactions same day	Yes	Payroll Manager
Generative AI for policy drafting	Yes — legal review required before publication	Yes	Legal Counsel

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Section 6

Prohibited AI Uses in Payroll

Hard Limits›

The following uses of AI in payroll are prohibited without explicit written approval from [CFO/Legal Counsel]:

Autonomous payroll confirmation — No AI system may confirm a payroll run without documented human authorization
Autonomous EFTPS deposit initiation — Tax deposits must be initiated by an authorized human
Autonomous W-4 modification — No AI system may change an employee's federal or state tax withholding elections without employee initiation and human review
Autonomous direct deposit routing changes — AI may flag suspicious changes but may not approve or block without human authorization
Autonomous garnishment calculation without validation — All garnishment calculations must be reviewed by a qualified payroll professional
Processing SSNs or full account numbers as AI model inputs — PII must be masked or tokenized before input to any AI or LLM system
Using AI outputs as tax advice to employees — All AI-generated responses to employee tax questions must include a disclaimer and referral to qualified tax counsel

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Section 7

Data Governance Controls for AI Inputs

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Social Security Numbers must be masked or tokenized before input to any AI or machine learning model
Bank account numbers and routing numbers are prohibited as AI model inputs
Full date of birth may only be used as an AI input where specifically required for age-based calculations (e.g., GTL imputed income); must be masked otherwise
All AI vendors processing payroll-related data must execute a Data Processing Agreement (DPA) meeting applicable privacy law requirements before data is shared
AI training data derived from payroll records must be de-identified in compliance with applicable privacy laws
Data minimization principle: only the minimum data required for the AI function may be provided to the AI system

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Section 8

Audit Trail Requirements

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Every AI-influenced payroll decision must generate an audit trail record containing:

Date and time of AI output generation (timestamp)
Identity of the AI system/model and version used
The inputs provided to the AI system (excluding PII as above)
The AI-generated output or recommendation
Identity of the human reviewer/authorizer
Date and time of human authorization
Whether the human accepted, modified, or rejected the AI output — and the rationale if modified or rejected

Retention period. AI audit trail records related to payroll must be retained for a minimum of 4 years per IRS record retention requirements (IRC §6001), extended to 7 years where substantial understatement risk exists. Records related to garnishment decisions must be retained for the duration of the order plus applicable statute of limitations.

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Section 9

Incident Response Procedure

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Priority	Trigger	Response SLA	Required Notifications
P1	AI causes incorrect tax deposit; employees receive incorrect net pay affecting 5+ employees	Immediate — same business day	Payroll Director, CFO, Legal Counsel, Tax counsel
P2	AI anomaly detection failure; AI-influenced W-2 errors discovered post-distribution	Within 4 business hours	Payroll Director, IT, Legal
P3	AI model drift detected; vendor reports model update affecting payroll outputs	Within 24 hours	Payroll Director, IT, AI Vendor
P4	Individual false positive/negative in anomaly detection; no material impact	Next business day	Payroll analyst; log for monthly review

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Section 10

AI Vendor Management Requirements

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Before any AI vendor may process payroll-related data or influence payroll decisions, the following must be completed:

Completion of the AI Vendor Due Diligence Questionnaire (see companion resource)
Execution of a Data Processing Agreement (DPA) covering PII handling, sub-processor disclosure, and breach notification
Liability allocation clause in the vendor contract — vendor acknowledges employer retains IRS tax liability and indemnification terms are clearly defined
Audit trail access — vendor must provide access to decision logs upon request
Model change notification — vendor must provide 30 days advance notice of any model updates that could affect payroll outputs
Annual review of vendor compliance with this policy

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Section 11

Policy Review and Maintenance

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This policy shall be reviewed at a minimum annually, and immediately upon:

Deployment of any new AI system in payroll operations
A P1 or P2 AI incident
Publication of new IRS or DOL guidance directly applicable to AI in payroll
Material change in applicable AI governance regulations (federal or applicable state)

Version	Effective date	Summary of changes	Approved by
1.0	[Insert]	Initial release	[Name / Title]