Marketing moves fast, andthe legal review process often struggles to keep up. Now, AI-generated creative, influencer campaigns, auto-renewal offers, and multi-state launches continue to make everyday marketing work even more complex. And it’s up to in-house legal and compliance teams to keep pace without becoming the bottleneck that slows every campaign down.
In a recent Axiom webinar moderated by Scott Smith of Penbury Consulting, Andra Dallas, Senior Counsel at PayPal, and Cory Krasnoff, Senior Counsel and Head of Delivery & Platform for Consumer | Consumer, Marketing & Commercial Legal at Uber, shared how their teams are approaching AI marketing compliance in practice. Their advice for other legal professionals? Let AI absorb the rote work so lawyers can concentrate on the judgment work that AI can't do, because that's where legal earns its seat at the table.
The strongest marketing teams build legal strategy into campaigns before launch—not after.
What Is AI Marketing Compliance?
AI marketing compliance is the process of ensuring that AI-generated and AI-assisted marketing materials meet the same legal and regulatory requirements that apply to any consumer-facing content: truthful claims, proper disclosures, cleared intellectual property, and adherence to industry-specific rules. When webinar attendees were polled about whether their organizations have a formal legal review process for AI-generated marketing content, the results were telling. Most respondents said they either have no formal process yet or are still working on building one.
That gap matters because the volume of AI-driven content is growing faster than most compliance teams can review it manually.
Does AI-Generated Marketing Content Actually Create New Legal Risks?
Here, Cory offered a useful reframe. At Uber, his team has moved away from treating AI as a fundamentally new paradigm that makes content inherently riskier.
“At the end of the day, it's just a technological tool, at least right now,” he shared. AI-supported tools have existed in marketing production for years. The underlying compliance risks, he pointed out, haven't really changed. If you ask an AI model to generate an image, the IP considerations are the same ones that always applied when a designer pulled a photo from a Google search. “You told AI to generate an image that looks as close as possible to an Andy Warhol, and if the output actually does, you may have a copyright infringement on your hands. But is that really all that different? No. It's just the application using this particular tool.”
The practical takeaway is that legal teams don't need a boil-the-ocean approach to AI for marketing. They need to adapt existing risk frameworks to new tools, then focus their attention where AI genuinely changes the math, which is speed and volume. Organizations building these frameworks may also benefit from experienced artificial intelligence lawyers who can support AI compliance programs, regulatory assessments, data governance, and IP reviews.
For regulated industries, the stakes run higher. Andra noted that in financial services, content touching credit products, banking, or crypto carries regulatory mandates around disclosures, and those requirements follow the content whether a human or an AI-powered tool produced it. Fitting a lengthy regulatory disclosure into a short vertical video someone watches on a phone takes creativity and a lawyer who knows the product inside and out.
The Legal Team's AI Marketing Compliance Checklist
Drawing on what both panelists described, here's how a legal team can structure its approach to AI-generated marketing materials:
1. Codify your high-risk categories
Cory’s team maintains a defined list of high-risk subject areas (roughly eight or nine categories) that is transparent to the business. Content touching those areas, such as regulated products or vulnerable populations, automatically requires human review. Everything else can move faster.
2. Streamline the rote work
Repetitive, low-risk, black-and-white review tasks are strong candidates for AI. Andra pointed to site checking as an example of tedious yes-or-no work where AI tools perform well today, freeing attorneys for the calls that actually require judgment.
3. Build self-help tools for the business
Cory encourages legal teams to build shared gems, GPTs, or AI agents trained on legal's defined parameters, sources of truth, and guideline documents. A well-built agent can flag potential compliance issues in a draft, tell the marketer which items will require a conversation with legal, and suggest ways to de-risk the content so they can keep moving. As he put it, “it's not that hard to build one, and the business will notice the speed.”
4. Reserve human judgment for what matters
Manual review isn't going away. Andra was candid that AI can't yet replicate how marketing lawyers think, particularly around risk acceptance. A risk that legal accepted for a money transfer campaign might be unacceptable for a cryptocurrency campaign, and unless every one of those judgment calls is documented, an AI model has no way to learn the distinction. High-stakes content still requires human review. And it probably will for a long time.
5. Keep responsibility lanes clear with agencies and vendors
When content comes from agencies, production partners, or influencers, Krasnoff stressed knowing who is responsible for which clearances. The company owns risk related to how its own products and services are described. The production partner owns run-of-the-mill creative clearances like third-party imagery and sound. Keeping those lanes clear tells your team what to focus on, and vetting the partner's own legal support tells you how much confidence to have.
6. Document everything in one system
Andra was emphatic on this point: “Don't just review things by email. Don't just review things by Slack. There has to be a system in place for review.” Requests will arrive by every channel imaginable, but directing them into a single system creates the audit trails you'll need when litigation or a regulator comes calling. AI can help here, too. Tools like Copilot or Gemini can organize requests flowing in from scattered sources to support triage in real time.
7. Get in the room early
The webinar's second poll question asked attendees to name their biggest marketing compliance challenges, and the runaway winner was getting marketing to bring legal in early enough. Both panelists agreed the fix is relational. “Good marketing teams are built by good legal partners,” Andra shared. Krasnoff recounted advice from a former general counsel: “If you're really good at digging your clients out of holes at the last minute, they will be happy to buy you a bigger shovel.” Earning a seat at the table early, and approaching every review as a path to “yes” beats shoveling every time.
Evolving Laws and Regulations
The regulatory environment around marketing compliance keeps shifting. Cory describes it as a push and pull between federal enforcement priorities, which can change cycle to cycle, and state regulators moving to fill any gaps. For legal teams, that means the specific regulatory requirements worth watching change constantly even when the fundamentals don't. Andra offered a similar prescription: Do your homework, follow what the FTC and other regulators are actually flagging, and keep your ear to the ground with industry peers. AI can speed up that research, but the conclusions still need checking.
As regulations evolve faster, specialized legal talent becomes even more valuable.
Common AI Marketing Compliance Mistakes
A few missteps came up repeatedly in the conversation. Treating AI-generated content as an entirely new risk universe leads teams to over-engineer processes instead of adapting frameworks that already work. Bringing too legal a perspective—one that isn't grounded in the business's actual risk profile—erodes trust and makes marketing route around you. Assuming legal knowledge transfers cleanly across industries ignores how much regulated sectors differ. Reviewing content ad hoc across scattered channels leaves you with no record to stand on later. And babysitting the business backfires. Cory’s closing advice was ultimately to treat clients like grown-ups, set clear parameters, and empower them to move within those guardrails.
FAQ
What is AI marketing compliance?
AI marketing compliance is the practice of ensuring AI-generated and AI-assisted marketing content meets applicable legal and regulatory requirements, including truthful claims, required disclosures, and IP clearances.
What is AI-generated marketing content?
AI-generated marketing content is marketing materials such as images, video, and copy produced with generative AI tools, whether created entirely by AI or with AI assistance during production.
Does AI-generated marketing content need to be disclosed?
Disclosure obligations depend on context and industry. Regulated sectors like financial services may carry specific mandates, and influencer content must still disclose material connections under FTC rules regardless of how it was produced.
What laws apply to AI-generated marketing content?
Largely the same ones that govern all marketing: FTC truth-in-advertising rules, IP and copyright law, industry-specific regulations, and a patchwork of state requirements that continues to evolve.
How should legal teams review AI-generated marketing content?
Triage by risk. Route low-risk content through self-help tools and streamlined review, and reserve manual review by attorneys for content touching defined high-risk categories.
What should an AI marketing content policy include?
A strong AI policy includes codified high-risk categories requiring human review, clear responsibility lanes for agencies and vendors, guidance for how the business uses AI tools, and a single documented review system that creates an audit trail.