Importance of AI Governance Frameworks

Key Points

• A legal AI governance framework helps guide an organization’s development, use, and monitoring of AI systems to comply with legal, ethical, and best-practice standards.
• In the U.S., AI governance falls across multiple federal, state, and sectoral controls, including executive orders, agency guidance, and privacy laws.
• The five core principles to design your AI use around are fairness, transparency, accountability, privacy, and human oversight. 
• The NIST AI RMF is an independent, detailed framework that helps organizations govern, map, measure, and manage their needs and workflows. 
• Expect enforcement from the DOJ, FTC, EEOC, and states with particular scrutiny on deceptive AI claims, unfair practices, and discriminatory outcomes.
• Litigation services from U.S. Legal Support can help reduce law firm risk and keep work moving smoothly.

What Is a Legal AI Governance Framework?

A model AI governance framework provides a structured set of policies, legal standards, and oversight practices to guide the development, use, and monitoring of AI technologies. There are multiple sources of best-practice frameworks that can be customized and integrated for each organization, but they overlap with federal and state regulations that require attention. 

Law firms, corporate legal departments, alternative legal service providers (ALSPs), and legal‑tech vendors handling client data all need legal AI governance frameworks. These frameworks create safer AI use and defensible decisions that can hold up under audits and court scrutiny. 

Specifically, frameworks should cover: 

• Risk identification
• AI safeguards
• Ethical use
• Compliance alignment
• Life‑cycle controls 

Remember: AI can draft, not decide. Humans should always stay accountable and in the loop.

U.S. AI Governance: Federal Landscape 

Let’s start by breaking down key federal sources that have their hand in AI governance. Keep in mind that state-level AI action plans and considerations are also underway, particularly in high-regulation states. 

White House Executive Orders and AI Action Plan

At the White House level, executive orders (EOs) are the key tool used for governance. As of late 2025, the primary EO is President Trump’s Executive Order 14179, “Removing Barriers to American Leadership in Artificial Intelligence,” which declares the intent “to sustain and enhance America’s global AI dominance in order to promote human flourishing, economic competitiveness, and national security.”¹

It’s also important to understand how the executive landscape influences the country in terms of key appointments, public messaging, and decisions around funding, studies, and agency agendas. 

The presidential arm is involved in how AI development and use influences: 

• National security
• Agency oversight
• Civil‑rights safeguards
• Workforce measures and how they cascade to employers and vendors
• Unemployment rates
• Business impacts at a national level and in terms of international competition

In terms of implications for a firm’s legal operations, best practices start with careful tracking of actions and usage of AI systems, including: 

• Regular inventories of AI use
• Transparency of usage 
• Written policies
• Incident playbooks

OMB Guidance for Federal AI Use and Procurement

When it comes to taking a broad executive order—which can be as concise as one or two pages—and translating it to specifics at an organizational level, look to memos published by the White House Office of Management and Budget (OMB). These documents provide specific guidance to federal agencies on how to implement EOs and are typically analyzed by private entities to determine what elements are useful or relevant to them.²

In response to Executive Order 14179, there are two key OMB memos to review: M-25-21 on “Accelerating Federal Use of AI through Innovation, Governance, and Public Trust” and M-25-22 on “Driving Efficient Acquisition of Artificial Intelligence in Government.”^3,4

From these, the private sector borrows best practices related to: 

• AI inventories
• Risk categorization
• Procurement clauses 

In particular, consider mirroring: 

• Pre‑deployment impact reviews
• Ongoing testing
• Reporting lines

NIST AI Risk Management Framework (AI RMF)

The National Institute of Standards and Technology (NIST) provides a voluntary but widely employed AI Risk Management Framework that can be adapted by nearly any organization to govern the assessment, implementation, and full lifecycle use of AI. It’s available at no cost “to improve the ability to incorporate trustworthiness considerations into the design, development, use, and evaluation of AI products, services, and systems.”⁵

The NIST AI RMF includes four functional areas that connect to organizational needs and workflows. For law firms, consider: 

• Govern – Establish cross-functional internal governance to oversee accountability, compliance, security, and risk with formal decision-making and escalation procedures.
   
• Map – Create a living inventory of all AI usage (including third-party), such as document drafting, review, and analysis, legal research, client intake and communication, predictive modeling, and graphics and demonstratives creation. Assess each for data security, decision impact, regulatory requirements, and other risk factors to ensure AI systems operate responsibly.
  
• Measure – Make a plan to assess risks and outcomes through audits and stakeholder feedback pertaining to bias, unexplainability, manipulation potential, and transparency issues. These are particularly relevant to predictive analysis, document review, and any other areas that have a direct impact on decision-making.
  
• Manage – Implement controls to reduce risks, such as human oversight or checks and balances, access controls, staff training, and continuous monitoring for performance degradation or model drift. 

In summary, firms can consult the NIST AI RMF to structure risk controls and model testing plans as they implement AI at increasing levels.

OSTP AI Bill of Rights (Principles)

The White House Office of Science and Technology Policy (OSTP) released its Blueprint for an AI Bill of Rights in late 2022 to provide guidance on how to design and deploy AI and automation without trespassing against civil rights and democratic values.⁶ Its five core principles are: 

1. Safe and effective systems
2. Algorithmic discrimination protections
3. Data privacy
4. Notice and explanation
5. Human alternatives, considerations, and fallback

Legal firms might pay particular attention to embedding these principles in: 

• Client engagement letters
• Privilege protocols
• Disclosure templates

Agency Enforcement and Guidance: DOJ, FTC, EEOC

Federal guidance of AI practices will also come with enforcement of lawful requirements that replace past voluntary structures. The U.S. Department of Justice, Federal Trade Commission, and the Equal Employment Opportunity Commission all have active AI initiatives underway.^7,8,9

Expect scrutiny on: 

• Deceptive AI claims
• Unfair practices
• Discriminatory outcomes

Practical steps include: 

• Log model limitations
• Human overrides
• Complaint handling

U.S. Sectoral and Privacy Laws Implicated by AI

A number of sectors in the U.S. are leveraging and/or affected by AI use such that they’re receiving high scrutiny at both federal and state levels—particularly health care and finance. AI use is also being incorporated into current privacy laws, such as HIPAA:

• HIPAA and 42 CFR Part 2 – Look for PHI (protected health information) workflows with generative/summarization tools, definition of minimum‑necessary access, BAAs (Business Associate Agreements) with vendors, and redaction/segregation rules for medical records used in training/evaluation to be given attention under HIPAA and 42 CFR Part 2 privacy laws.
  
• GLBA (financial data) – Handling financial records in litigation support and vendor security and data‑sharing limits are key under the Gramm–Leach–Bliley Act (a.k.a., the Financial Services Modernization Act of 1999).
  
• FCRA (screening and credit‑adjacent data) – Consider when automated assessments may trigger FCRA (Fair Credit Reporting Act) duties, as well as dispute and adverse‑action flows.
  
• ADA and civil rights laws – Here, the focus is on safeguarding accessibility in AI-assisted tools and preventing discriminatory outcomes.
  
• COPPA and state consumer protection – Look for youth data flags and deceptive‑practices risk for AI claims in marketing to clients under the Children’s Online Privacy Protection Act of 1998 (COPPA) and individual state laws.

Core Principles and Components Common in U.S. Guidance 

Additionally, consider these practical interpretations of core principles and components that echo throughout regulatory guidance. 

• Fairness, transparency, accountability, privacy, human oversight – Translate these principles into policy statements, reviewer checklists, and disclosure templates.
  
• Legal/regulatory oversight and independent governance bodies – Create an AI committee covering legal, privacy, security, DEI, and operational needs with escalation authority and a regular meeting cadence.
  
• Public engagement and continuous evaluation – Obtain stakeholder input from clients and business units through feedback channels and periodic model and policy refreshes. 

Apply AI Governance Frameworks with Confidence

AI governance is a fast-developing reality that requires ongoing attention. To that end, it’s crucial to integrate a life‑cycle approach and keep the principles of fairness, transparency, accountability, privacy, and human oversight in mind. Consider a lightweight pilot on a single high‑impact workflow after an impact assessment, and measure KPIs for 90 days.

AI governance also extends to your vendor relationships. We invite you to explore how U.S. Legal Support leverages AI and data security throughout our comprehensive litigation support solutions. We are compliant with SOC 2 Type 2 and HIPAA guidelines, utilize end-to-end encryption and secure client portals, and follow the NIST Cybersecurity Framework.

Contact us today to learn more.

Sources: 

1. The White House. Removing Barriers To American Leadership In Artificial Intelligence. https://www.whitehouse.gov/presidential-actions/2025/01/removing-barriers-to-american-leadership-in-artificial-intelligence/
2. Epstein Becker & Green. New Federal Agency Policies and Protocols for Artificial Intelligence Utilization and Procurement Can Provide Useful Guidance for Private Entities. https://www.workforcebulletin.com/new-federal-agency-policies-and-protocols-for-artificial-intelligence-utilization-and-procurement-can-provide-useful-guidance-for-private-entities
3. The White House. M-25-21. Accelerating Federal Use of AI through Innovation, Governance, and Public Trust. https://www.whitehouse.gov/wp-content/uploads/2025/02/M-25-21-Accelerating-Federal-Use-of-AI-through-Innovation-Governance-and-Public-Trust.pdf
4. The White House. M-25-22: Driving Efficient Acquisition of Artificial Intelligence in Government. https://www.whitehouse.gov/wp-content/uploads/2025/02/M-25-22-Driving-Efficient-Acquisition-of-Artificial-Intelligence-in-Government.pdf
5. NIST. AI Risk Management Framework. https://www.nist.gov/itl/ai-risk-management-framework
6. Epstein Becker & Green. The White House Releases “Blueprint for an AI Bill of Rights: Making Automated Systems Work for the American People”. https://www.workforcebulletin.com/the-white-house-releases-blueprint-for-an-ai-bill-of-rights-making-automated-systems-work-for-the-american-people
7. FEDSCOOP. Department of Justice announces new AI initiative. https://fedscoop.com/justice-ai-doj-new-ai-initiative/
8. Federal Trade Commission. Artificial Intelligence Compliance Plan. https://www.ftc.gov/ai
9. EEOC. What is the EEOC’s role in AI? https://www.eeoc.gov/sites/default/files/2024-04/20240429_What%20is%20the%20EEOCs%20role%20in%20AI.pdf

Julie Feller

Julie Feller is the Vice President of Marketing at U.S. Legal Support where she leads innovative marketing initiatives. With a proven track record in the legal industry, Juie previously served at Abacus Data Systems (now Caret Legal) where she played a pivotal role in providing cutting-edge technology platforms and services to legal professionals nationwide.