FTC AI Guidelines

FTC AI enforcement readiness

The FTC applies existing consumer protection laws to AI systems with increasing scrutiny. From truth in advertising to algorithmic fairness and children's privacy, we help you navigate FTC expectations and build evidence of responsible AI practices.

What are FTC AI Guidelines?

The Federal Trade Commission (FTC) does not have standalone AI-specific regulations. Instead, it applies existing consumer protection laws to AI systems, including FTC Act Section 5 (unfair or deceptive practices), COPPA (children's privacy), Equal Credit Opportunity Act, and Fair Credit Reporting Act.

Why this matters now: The FTC has dramatically increased AI enforcement with settlements totaling over $5 billion and technology bans. Commissioners have stated AI is a top enforcement priority, particularly for deceptive claims, algorithmic bias, and privacy violations.

Enforcement-based

No pre-approval required, but violations carry steep penalties

Evidence-focused

Substantiation of claims and documentation of compliance efforts

See the official FTC AI hub for guidance and enforcement actions.

Who needs FTC compliance?

AI product companies

Making performance or capability claims in advertising

Financial services

Using AI for credit, lending, or insurance decisions

E-commerce platforms

AI-powered pricing, recommendations, or targeting

Healthcare providers

AI diagnostic tools or patient risk assessment

Employers and HR tech

AI hiring, screening, or workforce management systems

Consumer apps

Serving children or collecting user data for AI training

How VerifyWise supports FTC compliance

Purpose-built capabilities that address FTC enforcement priorities

AI claims documentation and substantiation

Document all AI capability claims with supporting evidence and performance data. The platform maintains an audit trail of claims made in marketing materials and links them to technical validation, ensuring FTC substantiation requirements are met.

Addresses: FTC Act Section 5: Substantiation, truth in advertising

Algorithmic bias monitoring and fairness testing

Implement continuous monitoring for algorithmic discrimination across protected characteristics. The platform tracks fairness metrics, demographic parity, and disparate impact aligned with FTC enforcement expectations and Equal Credit Opportunity Act requirements.

Addresses: ECOA, Fair Credit Reporting Act: Algorithmic fairness, bias prevention

Data privacy controls and consent management

Establish data minimization practices, consent workflows, and privacy controls for AI training and deployment. The platform documents data collection purposes, retention periods, and user consent aligned with FTC privacy expectations.

Addresses: FTC privacy enforcement: Data security, consent, minimization

Dark pattern detection and prevention

Identify and eliminate deceptive design patterns in AI-powered interfaces. The platform tracks user experience decisions, disclosure implementations, and choice architecture to prevent manipulative practices the FTC targets.

Addresses: FTC Act Section 5: Deception, unfair practices prevention

Children's privacy and COPPA compliance

Implement specialized controls for AI systems that may interact with children under 13. The platform documents age verification mechanisms, parental consent workflows, and data handling practices required under COPPA.

Addresses: COPPA: Parental consent, age verification, data restrictions

Enforcement action readiness and incident response

Maintain comprehensive documentation of AI governance decisions, risk assessments, and compliance efforts. The platform generates evidence packages for FTC inquiries and tracks corrective action implementation.

Addresses: FTC investigations: Documentation, remediation tracking

All compliance activities are timestamped and tracked with assigned owners. This creates a defensible audit trail showing proactive compliance efforts rather than reactive responses to FTC inquiries.

Complete FTC compliance area coverage

VerifyWise addresses all major FTC enforcement priorities for AI systems

18

FTC enforcement categories

18

Categories with dedicated tooling

100%

Coverage across all priority areas

Truth in AI advertising5/5

Claims verification, substantiation, marketing oversight

Algorithmic fairness4/4

Bias detection, discrimination prevention, equal treatment

Data privacy & security6/6

Data minimization, consent, security controls, breach response

Dark patterns prevention3/3

Deceptive design, manipulation tactics, transparency

Built for FTC enforcement readiness

Claims substantiation

Document evidence for every AI performance claim before publication

Bias detection workflows

Continuous monitoring for algorithmic discrimination and disparate impact

COPPA compliance

Age verification, parental consent, and children's data handling controls

Multi-framework mapping

Crosswalk to NIST AI RMF, EU AI Act, and CCPA requirements

Five key FTC AI enforcement areas

Understanding where the FTC focuses its AI-related enforcement actions

Deceptive AI claims

False or unsubstantiated claims about AI capabilities, performance, or benefits in advertising and marketing.

Common violations

  • Exaggerated AI capability claims without evidence
  • Claims of human-like performance when inaccurate
  • Misleading statements about AI training data or methods
  • False claims about AI decision accuracy or reliability
  • Undisclosed AI limitations or failure modes

FTC requires reasonable basis for all performance claims

Algorithmic bias and discrimination

AI systems that produce discriminatory outcomes or disparate impact on protected groups.

Common violations

  • Discriminatory outcomes in credit decisions
  • Biased hiring or employment algorithms
  • Unfair pricing or service access based on protected characteristics
  • Tenant screening with disparate impact
  • Healthcare or insurance algorithms with bias

ECOA and FCRA apply to algorithmic decisions

Data privacy and security

Inadequate protection of consumer data used in AI training, deployment, or surveillance.

Common violations

  • Excessive data collection for AI training
  • Inadequate security for AI training datasets
  • Unauthorized AI-powered surveillance
  • Failure to honor data deletion requests
  • Deceptive data collection practices

Data minimization and security by design required

Dark patterns and manipulation

AI-powered interfaces designed to manipulate, deceive, or coerce consumer decisions.

Common violations

  • Manipulative choice architecture
  • Deceptive default settings in AI systems
  • Hidden costs or subscription traps
  • Confusing cancellation flows
  • Exploitative targeting of vulnerable populations

Interface design must not deceive or manipulate

Children's privacy (COPPA)

AI systems that collect or use data from children under 13 without proper safeguards.

Common violations

  • AI data collection from children without parental consent
  • Inadequate age verification mechanisms
  • Behavioral profiling of children
  • Targeted advertising to children
  • Failure to delete children's data upon request

COPPA requires verifiable parental consent

FTC enforcement actions and precedents

Recent AI-related settlements and consent orders demonstrate FTC priorities

CompanyYearViolationPenaltyKey takeaway
Weight Watchers (Kurbo app)2024Illegal collection and sharing of children's health data$1.5 millionFTC alleged the Kurbo weight loss app collected personal information from children under 13 without proper parental consent, violating COPPA.
Amazon Ring2023Inadequate AI surveillance video security$5.8 millionFTC charged Ring with privacy violations including allowing employees and contractors unrestricted access to customers' AI-powered surveillance video.
Amazon Alexa2023COPPA violations in voice data retention$25 millionFTC alleged Amazon kept children's Alexa voice recordings indefinitely and undermined parents' deletion requests, violating COPPA.
Rite Aid2023Facial recognition with insufficient safeguards5-year ban + compliance monitoringFTC prohibited Rite Aid from using facial recognition technology for five years after alleged deployment without reasonable safeguards against harm.
Twitter (X)2022Deceptive use of security data for advertising$150 millionFTC alleged Twitter deceptively used phone numbers and email addresses collected for security purposes to target advertising.
Facebook/Meta2019 (ongoing)Privacy violations, algorithmic discrimination$5 billion + ongoing oversightFTC consent order includes requirements for algorithmic accountability and privacy assessments for new AI products.

Pattern: The FTC is increasing enforcement frequency and penalty amounts for AI-related violations. Beyond monetary penalties, the FTC now imposes technology bans, ongoing monitoring, and algorithmic auditing requirements.

Source: FTC enforcement database

20-week FTC compliance roadmap

A practical path to enforcement readiness with clear milestones

Phase 1Weeks 1-4

Claims audit and substantiation

  • Audit all AI-related marketing claims
  • Document technical substantiation for each claim
  • Identify unsubstantiated or exaggerated claims
  • Implement claims review process
Phase 2Weeks 5-10

Algorithmic fairness assessment

  • Identify AI systems with consumer impact
  • Implement bias detection and fairness testing
  • Document demographic parity metrics
  • Establish disparate impact monitoring
Phase 3Weeks 11-16

Privacy and security controls

  • Implement data minimization practices
  • Establish consent management workflows
  • Deploy security controls for AI training data
  • Create data retention and deletion procedures
Phase 4Weeks 17-20

Dark patterns prevention and COPPA

  • Audit user interfaces for manipulative design
  • Implement age verification for child-facing AI
  • Establish parental consent workflows
  • Deploy continuous compliance monitoring
Penalty structure

FTC AI enforcement penalties

The FTC has authority to impose significant civil penalties, injunctive relief, and technology bans for AI violations

FTC Act Section 5

Civil penalties

Up to $50,120 per violation per day

Penalties for deceptive or unfair practices, including false AI claims and dark patterns

COPPA violations

Civil penalties

Up to $51,744 per violation

Penalties for each violation of children's privacy rules in AI systems

Consent order violations

Civil penalties

Up to $50,120 per violation

Additional penalties for violating FTC consent orders or settlements

Algorithmic discrimination

Injunctive relief + damages

Variable (can exceed $100M)

ECOA and FCRA violations in AI lending, credit, or employment decisions

Beyond monetary penalties: The FTC can ban specific technologies (e.g., Rite Aid's 5-year facial recognition ban), require algorithmic audits, impose ongoing monitoring, and mandate data deletion.

Each violation can be counted separately, leading to penalties far exceeding base amounts.

Policy templates

FTC-aligned AI governance policies

Access ready-to-use policy templates addressing FTC enforcement priorities, from claims substantiation to COPPA compliance

Truth in advertising

  • • AI Claims Substantiation Policy
  • • Marketing Review Procedures
  • • Performance Testing Standards
  • • Disclosure Requirements
  • • Limitations Communication
  • + 3 more policies

Algorithmic fairness

  • • Bias Detection & Testing Policy
  • • Disparate Impact Monitoring
  • • Fairness Metrics Standards
  • • ECOA Compliance Procedures
  • • FCRA AI Decision Requirements
  • + 4 more policies

Privacy & COPPA

  • • COPPA Compliance Policy
  • • Age Verification Standards
  • • Parental Consent Workflows
  • • Data Minimization Policy
  • • Privacy by Design Standards
  • + 5 more policies

Frequently asked questions

Common questions about FTC AI enforcement and compliance

The FTC does not have standalone AI-specific regulations. Instead, it applies existing laws like FTC Act Section 5 (prohibiting unfair or deceptive practices), COPPA, Equal Credit Opportunity Act, and Fair Credit Reporting Act to AI systems. The FTC has issued guidance through blog posts, enforcement actions, and policy statements.
FTC Act Section 5 prohibits 'unfair or deceptive acts or practices' in commerce. This applies to AI in multiple ways: false or unsubstantiated claims about AI capabilities, deceptive marketing about AI features, dark patterns in AI-powered interfaces, and unfair practices like discriminatory algorithms or inadequate data security. The FTC has broad authority to pursue companies whose AI practices harm consumers.
The FTC requires companies to have a 'reasonable basis' for all performance claims before making them. For AI systems, this means possessing competent and reliable evidence (testing data, validation studies, benchmarks) that supports claims about accuracy, performance, or capabilities. The level of substantiation depends on the specificity of the claim and the potential consequences of the AI decision.
Penalties vary by violation type. FTC Act Section 5 violations can result in up to $50,120 per violation per day. COPPA violations carry penalties up to $51,744 per violation. Recent settlements range from $1.5 million (Weight Watchers/Kurbo) to $5 billion (Facebook/Meta). The FTC can also impose injunctive relief, including bans on using certain technologies (e.g., Rite Aid's 5-year facial recognition ban).
The FTC uses existing anti-discrimination laws like the Equal Credit Opportunity Act (ECOA) and Fair Credit Reporting Act (FCRA) to pursue algorithmic bias in credit, lending, employment, and housing. The FTC focuses on disparate impact (outcomes that disproportionately harm protected groups) even without discriminatory intent. Companies must test for bias, monitor for disparate impact, and be prepared to explain and justify algorithmic decisions. See the FTC's report on algorithmic harms.
Dark patterns are design tricks that manipulate users into making decisions they wouldn't otherwise make. In AI systems, this includes manipulative choice architecture, deceptive defaults, hidden costs, confusing cancellation flows, or exploitative targeting. The FTC treats dark patterns as deceptive practices under Section 5 and has brought enforcement actions against companies using manipulative interface designs.
COPPA (Children's Online Privacy Protection Act) requires verifiable parental consent before collecting personal information from children under 13. For AI systems, this means: implementing robust age verification, obtaining parental consent before collecting data for AI training, avoiding behavioral profiling of children, restricting targeted advertising, and honoring deletion requests. Recent enforcement includes Amazon Alexa ($25M) and Weight Watchers Kurbo ($1.5M).
The FTC expects companies to follow privacy by design principles: collect only data necessary for the stated purpose (data minimization), implement reasonable security measures for AI training datasets, obtain meaningful consent for data collection, honor deletion and access requests, avoid deceptive data practices, and conduct privacy assessments before launching new AI products. The Facebook/Meta consent order requires privacy impact assessments for new AI features.
Maintain documentation for each AI claim: technical validation and testing data, performance benchmarks and metrics, limitations and failure modes, data sources and methodology, ongoing monitoring results, and records of claim reviews. This evidence should exist before making claims (not created after FTC inquiry). VerifyWise helps maintain this audit trail with timestamps and approvals.
FTC investigations typically start with a Civil Investigative Demand (CID) requesting documents, data, and testimony. The FTC examines marketing claims, AI system documentation, fairness testing, privacy practices, and consumer complaints. Investigations can result in: no action, voluntary compliance agreement, consent order with penalties and monitoring, or litigation. Strong documentation of compliance efforts and good faith risk management can influence outcomes.
The EU AI Act is a comprehensive regulatory framework with ex-ante requirements (compliance before deployment). FTC enforcement is ex-post (action after harm occurs) using existing consumer protection laws. Both focus on algorithmic fairness, transparency, and consumer protection, but through different mechanisms. Organizations operating globally need both FTC compliance readiness and EU AI Act conformity.
Yes, VerifyWise provides tools specifically for FTC enforcement readiness: claims documentation and substantiation tracking, algorithmic bias detection and fairness monitoring, data privacy controls and consent management, dark pattern auditing capabilities, COPPA compliance workflows, and evidence packages for FTC inquiries. The platform also maps to other frameworks like NIST AI RMF and EU AI Act for comprehensive governance.

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Build defensible evidence of responsible AI practices with our comprehensive compliance platform.

FTC AI Guidelines Compliance Guide | VerifyWise