Avoiding 'AI-Washing': Lessons from the SEC's First Marketing-Rule Enforcement Actions

The March 18, 2024 settlements with Delphia and Global Predictions sent a clear message to the financial services industry: the SEC isn't playing around when it comes to AI claims. These enforcement actions represent the first time regulators have specifically targeted "AI-washing" under the Marketing Rule, and they won't be the last. (White & Case LLP)

For marketing teams and compliance officers, these cases offer a roadmap of what not to do. But they also highlight something more important: the need for robust systems that can catch these issues before they become enforcement actions. The settlements show us exactly which Marketing Rule provisions are most vulnerable to AI-related violations and provide concrete lessons for building compliant marketing practices. (The Race to the Bottom)

The SEC's Opening Salvo: Delphia and Global Predictions

The March 2024 settlements weren't just routine enforcement actions. They marked the beginning of a broader regulatory crackdown on what the SEC calls "AI-washing" - the practice of making unfounded claims about artificial intelligence capabilities to attract investors. (White & Case LLP)

Delphia, a Toronto-based investment adviser, paid $225,000 to settle charges that it falsely advertised using AI to analyze client data and predict investment trends. The reality? The firm hadn't used any client data and hadn't created the algorithm it claimed to have developed. Global Predictions faced similar charges, settling for $175,000 after claiming to use AI and machine learning in ways that simply weren't true. (White & Case LLP)

These cases weren't about minor technical inaccuracies. They were about fundamental misrepresentations that violated core Marketing Rule principles. The SEC's enforcement approach shows they're treating AI claims with the same scrutiny they apply to performance claims and testimonials.

Which Marketing Rule Provisions Got Violated

The Delphia and Global Predictions cases highlight three critical areas where AI claims can trip up marketing teams under the SEC's Marketing Rule:

Substantiation Requirements

The Marketing Rule requires that all claims in advertisements be substantiated. This means you need reasonable basis for any statement about your AI capabilities before you make it public. (SEC Marketing Rule Compliance)

Delphia claimed to use "AI and machine learning to predict which companies and trends are about to move the markets." But when the SEC investigated, they found no evidence of such capabilities. The firm couldn't substantiate its claims because the technology simply didn't exist.

For marketing teams, this creates a clear requirement: every AI-related claim needs documentation. You can't just say you use AI for investment decisions if you're actually using traditional analysis methods. The substantiation standard applies whether you're talking about AI-powered research, algorithmic trading, or predictive analytics.

Testimonial and Endorsement Issues

While the Delphia and Global Predictions cases didn't specifically involve testimonials, the Marketing Rule's testimonial provisions create additional risks for AI claims. If you're using client testimonials that reference your AI capabilities, those testimonials need to reflect actual experiences with actual AI systems. (SEC Marketing Rule Compliance)

This becomes particularly tricky when clients might not fully understand the difference between AI-powered analysis and traditional quantitative methods. A testimonial praising your "AI-driven insights" could violate the Marketing Rule if those insights actually came from conventional research.

Hypothetical Performance Complications

The Marketing Rule allows hypothetical performance presentations under specific conditions, but AI claims can complicate these presentations significantly. If you're showing hypothetical returns based on AI-driven strategies, you need to be able to demonstrate that the AI system actually exists and works as described.

This is where many firms might stumble. It's tempting to show what your AI system "could" achieve, but the Marketing Rule requires that hypothetical performance be based on actual, implementable strategies.

Red Flags That Should Trigger Compliance Review

Based on the SEC's enforcement actions and broader regulatory trends, certain AI-related marketing claims should immediately trigger compliance review:

Claims About Data Usage: Any statement about analyzing client data, social media sentiment, or alternative data sources needs verification. The Delphia case shows that claiming to use data you don't actually access is a direct path to enforcement action.

Predictive Capabilities: Statements about predicting market movements, identifying trends, or forecasting performance require substantiation. You need to be able to demonstrate that your AI system actually makes these predictions and that they're based on legitimate methodologies.

Competitive Advantages: Claims that your AI gives you an edge over competitors need careful review. These statements often imply performance benefits that may require substantiation under the Marketing Rule's performance advertising provisions.

Technical Specifications: Detailed descriptions of AI algorithms, machine learning models, or data processing capabilities should be accurate and verifiable. The SEC's technical staff can and will investigate these claims.

The regulatory environment is evolving rapidly, and AI-washing has become a priority enforcement area. Recent Reuters coverage shows that regulators are expanding their crackdown beyond just investment advisers to include other financial services firms. (Reuters)

Building Compliant AI Marketing Practices

The enforcement actions provide clear guidance for building marketing practices that can withstand regulatory scrutiny. The key is creating systems that ensure accuracy before claims reach the public.

Documentation Requirements

Every AI-related marketing claim needs supporting documentation. This isn't just about having technical specifications - you need evidence that your AI systems work as advertised. Model documentation should include training data sources, performance metrics, and validation results. (Gravity AI)

For investment advisers, this documentation becomes part of your compliance record. The SEC will expect to see evidence that your AI claims are based on actual capabilities, not aspirational goals or development roadmaps.

Review Processes

Marketing materials containing AI claims need enhanced review processes. Technical teams should verify that claims accurately reflect system capabilities, while compliance teams should ensure Marketing Rule compliance. (Luthor)

This dual review is critical because AI claims often sit at the intersection of technical accuracy and regulatory compliance. A claim might be technically accurate but still violate Marketing Rule substantiation requirements if it's not properly documented.

Disclosure Strategies

Proper disclosure can help mitigate risks around AI claims. Clear explanations of how AI systems work, their limitations, and their role in investment processes can help ensure that marketing materials don't mislead investors.

But disclosure isn't a cure-all. The SEC's enforcement actions show that misleading claims can't be fixed with disclaimers. The underlying claims need to be accurate and substantiated.

Practical Tools for Marketing Teams

AI Claims Checklist

Before publishing any marketing material that mentions AI, machine learning, or algorithmic processes, marketing teams should verify:

• Accuracy: Does the AI system actually exist and function as described?

• Documentation: Is there sufficient technical documentation to support the claims?

• Substantiation: Can you provide evidence that the AI system delivers the claimed benefits?

• Limitations: Are any significant limitations or risks properly disclosed?

• Performance: If the claims imply performance benefits, are they properly substantiated under Marketing Rule requirements?

This checklist approach helps ensure that AI claims meet both technical accuracy and regulatory compliance standards.

Model Documentation Templates

Proper model documentation is essential for substantiating AI claims. Documentation should include system architecture, training methodologies, performance validation, and ongoing monitoring procedures. (Gravity AI)

For marketing purposes, this documentation needs to be accessible to compliance teams who may not have technical backgrounds. Clear explanations of what the AI system does, how it works, and what results it produces are essential.

Disclosure Language Samples

Effective disclosure language for AI-related marketing materials should be specific and clear. Generic statements about using "advanced technology" or "sophisticated algorithms" don't provide meaningful disclosure.

Instead, disclosures should explain the specific role of AI in investment processes, any limitations or risks, and how AI-generated insights are used in decision-making. This level of detail helps ensure that investors understand what they're actually getting.

The Broader Regulatory Trend

The SEC's enforcement actions are part of a broader regulatory focus on AI-washing across multiple industries. The FTC has also been active in this area, with recent actions against fintech companies for misleading AI claims. (Luthor)

This trend is accelerating in 2025, with regulators increasingly sophisticated in their ability to investigate AI claims. The technical staff at regulatory agencies now includes experts who can evaluate whether AI systems actually work as advertised.

For financial services firms, this means that AI claims will face the same level of scrutiny as performance claims and other regulated marketing content. The days of using AI buzzwords without substantiation are over.

Industry Impact and Future Enforcement

The Delphia and Global Predictions settlements represent just the beginning of SEC enforcement in this area. Industry observers expect more cases as regulators continue to investigate AI claims across the financial services sector. (The Race to the Bottom)

This enforcement trend has significant implications for how firms approach AI marketing. The safe approach is to treat AI claims with the same rigor applied to performance advertising - every claim needs substantiation, documentation, and careful compliance review.

The regulatory focus on AI-washing also reflects broader concerns about transparency in financial services. As AI becomes more prevalent in investment processes, regulators want to ensure that investors understand what they're actually getting when firms claim to use artificial intelligence.

Compliance Technology Solutions

The complexity of AI-related marketing compliance creates opportunities for technology solutions that can help firms manage these risks. Automated compliance review systems can flag potentially problematic AI claims before they reach the public. (Luthor)

These systems can integrate with existing marketing workflows to provide real-time compliance checking. By analyzing marketing content for AI-related claims and cross-referencing them against documented capabilities, compliance technology can help prevent the kind of violations that led to the Delphia and Global Predictions settlements.

The key is having systems that can understand both the technical aspects of AI claims and the regulatory requirements that apply to them. This dual capability is essential for effective compliance in the AI era.

Risk Management Strategies

Effective risk management for AI-related marketing requires a multi-layered approach. Technical validation ensures that AI claims are accurate, while compliance review ensures they meet regulatory requirements. (Luthor)

Documentation plays a critical role in this risk management framework. Proper documentation not only supports marketing claims but also provides evidence of good faith compliance efforts if regulatory questions arise.

Ongoing monitoring is also essential. AI systems evolve over time, and marketing claims need to be updated to reflect current capabilities. Regular reviews of AI-related marketing content help ensure continued accuracy and compliance.

Training and Education

The enforcement actions highlight the need for enhanced training around AI marketing compliance. Marketing teams need to understand not just what claims they can make, but how to properly substantiate and document those claims. (Luthor)

This training should cover both the technical aspects of AI systems and the regulatory requirements that apply to marketing them. Cross-functional training that brings together marketing, compliance, and technical teams can help ensure that everyone understands their role in maintaining compliant AI marketing practices.

Looking Forward: 2025 and Beyond

The regulatory landscape for AI marketing will continue to evolve throughout 2025 and beyond. Recent Reuters coverage suggests that enforcement actions will become more frequent and more sophisticated as regulators develop expertise in evaluating AI claims. (Reuters)

Firms that get ahead of this trend by implementing robust AI marketing compliance programs will be better positioned to avoid enforcement actions and maintain competitive advantages. The key is building systems that ensure accuracy and compliance from the ground up, rather than trying to retrofit compliance onto existing marketing practices.

The SEC's enforcement actions also signal that AI claims will be held to the same standards as other regulated marketing content. This means that the substantiation, documentation, and review processes that apply to performance claims and testimonials also apply to AI-related marketing content.

Final Thoughts

The SEC's enforcement actions against Delphia and Global Predictions mark a turning point in AI marketing compliance. These cases show that regulators are serious about preventing AI-washing and have the tools to investigate technical claims.

For marketing teams and compliance officers, the message is clear: AI claims need the same level of substantiation and documentation as any other regulated marketing content. The days of using AI buzzwords without backing them up are over.

The good news is that firms with legitimate AI capabilities can still market them effectively. The key is ensuring that marketing claims accurately reflect actual capabilities and are properly documented and substantiated.

As the regulatory environment continues to evolve, firms that invest in robust AI marketing compliance programs will be better positioned to avoid enforcement actions while still being able to communicate their technological advantages to clients and prospects.

If you're struggling to keep up with the evolving compliance requirements around AI marketing, you're not alone. The intersection of cutting-edge technology and complex regulations creates challenges that many firms find difficult to manage manually. That's where automated compliance solutions can make a real difference. At Luthor, we help RIAs and broker-dealers automatically review marketing assets for compliance issues, including AI-related claims that could trigger SEC enforcement. Our AI-powered platform can reduce the risk, effort, and time needed to tackle marketing compliance at scale, giving you confidence that your AI claims meet regulatory standards before they reach the public. Ready to see how automated compliance review can protect your firm from AI-washing violations? Request demo access to see how Luthor can help you stay ahead of the regulatory curve.

Frequently Asked Questions

What is AI-washing and why is the SEC targeting it?

AI-washing is a deceptive marketing tactic where companies exaggerate their AI capabilities or falsely claim to integrate AI into their decision-making processes. The SEC is targeting this practice because it misleads investors about a company's technological sophistication and investment strategies, violating securities laws designed to protect investors from false advertising.

What were the key violations in the Delphia and Global Predictions cases?

Delphia falsely advertised that it used AI to analyze client data and predict investment trends, when in reality it had not used any client data or created the claimed algorithm. Global Predictions similarly made misleading statements about their AI usage. Both firms violated the SEC's Marketing Rule by making false and misleading statements about their AI capabilities to attract investors.

How does the SEC's Marketing Rule apply to AI claims in investment advisory marketing?

The SEC's Marketing Rule, effective May 4, 2021, broadened the definition of 'advertisement' to include any communication offering investment advisory services. Under this rule, investment advisers must ensure all marketing communications, including AI-related claims, are truthful and not misleading. The rule requires substantiation of any performance claims or technological capabilities advertised to clients or prospects.

What compliance steps should RIAs take to avoid AI-washing violations?

RIAs should implement comprehensive AI policies covering data privacy, bias, transparency, and accountability. They must document all AI systems and capabilities accurately, ensure marketing claims can be substantiated with evidence, and regularly review marketing materials for compliance. As noted in compliance guidance, AI policies should be living documents that evolve with technology and regulatory requirements.

What are the red flags that indicate potential AI-washing in marketing materials?

Red flags include vague or unsubstantiated claims about AI capabilities, promises of superior performance based on AI without supporting data, marketing materials that overstate the role of AI in investment decisions, and claims about using client data or proprietary algorithms that don't actually exist. Any disconnect between marketed AI capabilities and actual technological infrastructure is a major warning sign.

How can investment advisers ensure their AI marketing claims are compliant and truthful?

Investment advisers should maintain detailed documentation of their AI systems and capabilities, regularly audit marketing materials against actual technological infrastructure, and implement robust compliance procedures. Truth in advertising principles require that all AI-related claims be accurate, substantiated, and not misleading to reasonable investors. Regular compliance training and legal review of marketing materials are essential safeguards.