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Updated for 2025 · Covers TRAIGA, EU AI Act & NIST AI RMF

The Complete AI Compliance Checklist for 2025

A practical, regulation-mapped checklist covering all 7 governance domains drawn from TRAIGA, the EU AI Act, NIST AI RMF, ISO 42001, and state AI laws. Use it to review your program, close gaps, and generate documentation automatically with Risk Meridian.

56 checklist items🗂7 governance domains⚖️6 regulations covered🤖Auto-tracked in Risk Meridian

Why AI Compliance Can't Be Improvised

Regulatory enforcement is accelerating. Organizations that treat AI compliance as an afterthought face escalating legal, financial, and reputational consequences.

€35M

Max EU AI Act penalty

or 7% of global annual turnover for prohibited-AI violations

2026

TRAIGA takes effect

In force January 1, 2026; enforced by the Texas Attorney General after a 60-day cure period

73%

of auditors cite documentation gaps

as the #1 reason AI governance programs fail regulatory review

faster with a platform

vs. building and maintaining compliance documentation manually

The 7-Domain AI Compliance Checklist

Every item maps to one or more AI governance frameworks. Items marked ★ Required are mandatory under at least one of those frameworks for high-risk systems (for example, the EU AI Act); under TRAIGA — an intent-based law — most are best practice that strengthen your defensibility.

01

AI System Inventory

Document every AI system your organization develops, deploys, or uses in consequential decisions.

TRAIGAEU AI ActNIST AI RMF
  • Maintain a centralized register of all AI systemsRequired
  • Document the purpose and use case of each systemRequired
  • Record the vendor, developer, and deployment dateRequired
  • Classify each system by risk level (Low / Moderate / High)Required
  • Identify which decisions each system influencesRequired
  • Document data sources and training datasetsRequired
  • Track system version history and change logBest practice
  • Link each system to relevant regulatory obligationsBest practice
6 required items · 2 best-practice items
02

Risk Assessment

Evaluate the potential harms, biases, and failure modes of each AI system before and after deployment.

TRAIGAEU AI ActNIST AI RMFISO 42001
  • Complete a pre-deployment risk assessment for every high-risk AI systemRequired
  • Assess potential for discriminatory or biased outputsRequired
  • Evaluate data privacy and security risksRequired
  • Document residual risks and mitigation controlsRequired
  • Assign risk owners for each identified riskRequired
  • Schedule periodic risk reassessments (at least annually)Required
  • Perform impact assessments when systems are significantly updatedBest practice
  • Document third-party and vendor AI riskBest practice
6 required items · 2 best-practice items
03

Governance Controls

Implement policies, procedures, and technical safeguards that govern how AI systems operate.

TRAIGAEU AI ActNIST AI RMFISO 42001
  • Establish a written AI governance policyRequired
  • Assign accountability for each AI systemRequired
  • Implement human oversight mechanisms for high-risk decisionsRequired
  • Create override and intervention proceduresRequired
  • Define acceptable use policies for AI toolsRequired
  • Conduct regular staff training on AI governance obligationsRequired
  • Set up access controls for AI system configurationBest practice
  • Establish a model validation and testing protocolBest practice
6 required items · 2 best-practice items
04

Transparency & Disclosure

Notify individuals when AI influences decisions that affect them and document your AI use publicly.

TRAIGAEU AI ActCalifornia AI
  • Publish a public AI use disclosure on your websiteRequired
  • Notify individuals when AI is used in consequential decisionsRequired
  • Provide plain-language explanations of AI decision factorsRequired
  • Offer a process for individuals to appeal AI-influenced decisionsRequired
  • Disclose AI use in hiring, lending, and healthcare contextsRequired
  • Maintain up-to-date disclosures when AI systems changeRequired
  • Publish a board-level AI governance statementBest practice
  • Disclose AI training data sources on requestBest practice
6 required items · 2 best-practice items
05

Incident Management

Log, investigate, and remediate AI failures, unexpected outputs, and adverse events.

TRAIGAEU AI ActNIST AI RMF
  • Maintain a formal AI incident logRequired
  • Define incident severity classification criteriaRequired
  • Establish escalation paths for high-severity incidentsRequired
  • Conduct root-cause analysis on all significant incidentsRequired
  • Implement corrective actions and track to closureRequired
  • Report serious incidents to relevant regulators where requiredRequired
  • Share learnings across the organizationBest practice
  • Track near-misses in addition to actual incidentsBest practice
6 required items · 2 best-practice items
06

Documentation & Audit Trail

Maintain records that demonstrate compliance — the foundation of any regulatory audit.

TRAIGAEU AI ActNIST AI RMFISO 42001
  • Retain risk assessment records for at least 3 yearsRequired
  • Keep audit trails of AI system changes and updatesRequired
  • Document board and executive sign-offs on AI governanceRequired
  • Store evidence of employee training completionsRequired
  • Maintain vendor contracts and third-party AI agreementsRequired
  • Produce compliance reports on a defined scheduleRequired
  • Generate board-ready AI governance summary reportsBest practice
  • Prepare for regulatory audits with pre-built evidence packagesBest practice
6 required items · 2 best-practice items
07

Ongoing Monitoring

Continuously track AI system performance, drift, and compliance posture after deployment.

TRAIGAEU AI ActNIST AI RMF
  • Monitor AI system outputs for accuracy and bias driftRequired
  • Track control completion rates and overdue itemsRequired
  • Review and update the AI risk register at least annuallyRequired
  • Measure and report governance maturity score over timeRequired
  • Conduct periodic internal audits of the AI governance programRequired
  • Stay current on regulatory changes and update controls accordinglyRequired
  • Benchmark against peer organizations and industry standardsBest practice
  • Report governance metrics to board or audit committeeBest practice
6 required items · 2 best-practice items

Stop tracking this in a spreadsheet.

Risk Meridian automatically creates these checklist items for every AI system you add, assigns owners, tracks due dates, and generates review-ready evidence — all mapped to the frameworks that apply to you.

Start Tracking Now

Regulations Covered by This Checklist

Each checklist item is tagged to the specific law or framework that mandates it.

TRAIGA7 domains →

Texas Responsible AI Governance Act

State law that prohibits specific intentional harmful uses of AI (enforced by the Texas Attorney General) and requires AI-use disclosure by government entities and healthcare providers. A documented governance program is best practice for demonstrating good-faith compliance.

EU AI Act7 domains →

EU Artificial Intelligence Act

The world's first comprehensive AI law, creating four risk tiers with binding obligations for high-risk AI systems including documentation, testing, human oversight, and transparency requirements.

NIST AI RMF6 domains →

NIST AI Risk Management Framework

Voluntary federal framework organizing AI risk management into four functions: Govern, Map, Measure, Manage. Increasingly referenced in government contracts and sector-specific regulation.

ISO 420013 domains →

ISO/IEC 42001

The international standard for AI management systems. Certifiable by accredited auditors. Provides a structured framework for integrating AI governance into existing management systems.

California AI1 domains →

California AI Transparency Act

California's disclosure requirements for automated decision-making, AI in employment, and consumer-facing AI interactions.

Colorado AI3 domains →

Colorado Artificial Intelligence Act

Revised — law in flux. Colorado's original AI Act (SB 24-205) was replaced by SB 189, which narrows it to a disclosure/transparency (ADMT) framework effective January 1, 2027 and removes the impact-assessment and duty-of-care provisions. We are monitoring as it stabilizes.

How Risk Meridian Automates This Entire Checklist

Instead of manually tracking 56 checklist items across a spreadsheet, Risk Meridian creates, assigns, and monitors every control for you — automatically, as you build your AI inventory.

Try Risk Meridian
  1. 1

    Add your AI systems

    Import or manually add every AI system your organization uses. Risk Meridian classifies risk levels automatically based on use case and decision type.

    See AI System Inventory →
  2. 2

    Controls are created automatically

    Based on each system's risk level and applicable regulations, Risk Meridian generates the exact compliance controls from this checklist — pre-mapped to TRAIGA, EU AI Act, and NIST AI RMF.

    Learn about Controls →
  3. 3

    Assign owners and track progress

    Assign controls to team members, set due dates, and track completion. Overdue items are flagged automatically. Your governance maturity score updates in real time.

    See the Dashboard →
  4. 4

    Generate review-ready reports

    Produce a compliance report, disclosure document, or board AI governance summary in one click. Every report is backed by the evidence your team has collected.

    See Reports →

Frequently Asked Questions

What is an AI compliance checklist?
An AI compliance checklist is a structured list of requirements and best practices that help your organization support compliance with AI regulations and frameworks such as the Texas Responsible AI Governance Act (TRAIGA), EU AI Act, NIST AI RMF, and ISO 42001. It covers areas including AI system inventory, risk assessment, governance controls, transparency disclosures, incident management, documentation, and ongoing monitoring. A compliance checklist helps you identify gaps, assign ownership, and track progress toward a defensible AI governance program.
Does TRAIGA apply to my organization?
TRAIGA applies to organizations that develop or deploy AI in Texas, but it is not a general 'consequential decisions' compliance regime. It is an intent-based law: it prohibits specific intentional harmful uses of AI (for example, intentional unlawful discrimination against a protected class) and is enforced exclusively by the Texas Attorney General after a 60-day cure period — there is no private right of action. It does not require private deployers to maintain an inventory, run risk assessments, or publish disclosures; those are best practices. Government entities and healthcare providers do have specific AI-use disclosure duties.
How long does it take to complete an AI compliance checklist?
Timeline depends on the size of your AI portfolio and the maturity of your existing governance program. Organizations starting from scratch typically take 4–12 weeks to complete an initial compliance assessment and build foundational documentation. Using a purpose-built platform like Risk Meridian can reduce this to as little as 1–2 weeks by automating risk classification, generating policy templates, and auto-creating governance controls based on your AI system inventory.
What happens if we fail an AI compliance audit?
Consequences vary by regulation. Under TRAIGA, enforcement is exclusive to the Texas Attorney General, following a 60-day cure period, with civil penalties that scale from roughly $10,000–$12,000 for curable violations up to $80,000–$200,000 for uncurable ones (and $2,000–$40,000 per day for continuing violations); there is no private right of action. Under the EU AI Act, penalties for the most serious violations can reach €35 million or 7% of global annual turnover. Beyond legal penalties, regulatory findings are often public and can damage customer trust. The best defense is a documented, auditable governance program.
Can I use a spreadsheet for AI compliance tracking?
Spreadsheets can work for very small AI portfolios, but they break down quickly. They lack audit trails, version control, role-based access, automated reminders for overdue controls, and the ability to generate regulatory-formatted reports. As your AI footprint grows and regulations multiply, spreadsheet-based tracking creates significant audit risk. Purpose-built AI governance platforms like Risk Meridian provide the documentation depth, access controls, and reporting capabilities that regulators expect.
Does this checklist cover the EU AI Act?
Yes. The checklist covers all seven governance categories required by the EU AI Act for high-risk AI systems: risk management (Category 02), data governance, technical documentation (Category 06), transparency and user information (Category 04), human oversight (Category 03), accuracy and robustness monitoring (Category 07), and incident reporting (Category 05). Risk Meridian maps each control to the specific EU AI Act article it satisfies, making cross-regulation compliance straightforward.
How does Risk Meridian help with this checklist?
Risk Meridian automatically creates governance controls based on your AI system inventory and risk level. When you add an AI system and classify it as high-risk, the platform generates the relevant set of checklist items, assigns owners, sets due dates, and tracks completion. You can generate review-ready compliance reports, disclosure documents, and board reports in minutes. The platform maps every control to the framework it supports — TRAIGA, EU AI Act, NIST AI RMF, ISO 42001, and more.

Ready to check off every item?

Risk Meridian generates and tracks all 56 checklist items automatically. Most teams complete their first AI compliance assessment in under 2 hours.