Practical Guidelines for Using AI in Marketing
austin carrollAI has made it incredibly easy to create marketing. A campaign brief can become a dozen headlines. A rough idea can become a polished email. A product description can turn into social posts, ads, and landing page copy in minutes.
The speed is useful. But it also makes it easier to publish something nobody has properly questioned.
AI does not know your customers the way your team does. It does not understand your brand, internal policies, or the context behind a campaign. And it does not take responsibility when an incorrect claim, confidential detail, or undisclosed relationship makes it into the final version.
That responsibility still belongs to people.
For marketing teams using AI regularly, a few clear rules can make that responsibility easier to manage.
1. Keep A Human In The Approval Loop
AI can draft, summarize, brainstorm, rewrite, analyze, and create variations. It should not get the final say.
Every piece of AI-assisted marketing needs human review before it reaches an audience, particularly when it includes factual claims, customer information, regulated topics, product capabilities, or representations about results.
The rule: AI can contribute to the work. A human approves the work.
2. Verify Before You Amplify
AI can make an unsupported claim sound completely credible. A statistic can be wrong. A customer result can be exaggerated. A regulatory reference can be outdated.
The FTC says advertising claims must be truthful, non-deceptive, and supported by evidence. AI-generated content should not become a shortcut around substantiation.
Before publishing, verify:
Statistics and research findings
Product capabilities
Customer results and testimonials
Quotes and attributed statements
Regulatory or legal references
Performance or outcome claims
The rule: If we can't substantiate it, we don't publish it.
3. Protect What Goes Into The Prompt
The output is not the only thing marketers need to think about. The information going into an AI tool matters too.
Marketing teams work with customer information, campaign plans, unpublished launches, financial information, credentials, and other restricted material that should not be casually pasted into a prompt.
Before using an AI tool, know what information you are providing, how the tool handles it, and whether its use has been approved.
The rule: Know what you're putting into an AI tool before you put it there.
4. Make The Marketing Sound Like Us
AI can produce copy that is polished, grammatically correct, and remarkably forgettable.
Your team's experience, opinions, stories, humor, specificity, and point of view are what give marketing a recognizable voice. AI can help you get there faster, but it should not flatten those things out.
Cut the filler. Rewrite the obvious. Add the details only someone close to the customer would know. Say something worth saying.
It's free to be fun, but with guardrails.
The rule: AI can help us find the words. It shouldn't erase our personality.
5. Know When Transparency Is Required
"AI-generated" is not automatically a disclosure requirement for every piece of marketing created with AI.
Whether disclosure is required can depend on how AI was used, what the content represents, where it is published, and which rules apply.
For example, Article 50 of the EU AI Act includes transparency obligations for certain AI-generated or manipulated content, including deepfakes and certain AI-generated or manipulated text concerning matters of public interest.
The rule: Know when disclosure applies, and make it clear.
6. Disclose Paid Relationships
AI can make influencer campaigns, sponsored content, affiliate marketing, and brand partnerships easier to scale. It can also make it easier to overlook disclosures.
The FTC identifies payments, employment relationships, family relationships, and free or discounted products or services as examples of material connections that may require disclosure.
The disclosure should be clear and conspicuous. Audiences should not have to investigate the relationship themselves.
The rule: If there's a material connection, don't make the audience guess.
What This Means For Marketing Teams
An AI policy does not need to be a 30-page document nobody reads. It needs to give marketers clear answers to the questions they face during everyday work:
Who reviews this before it goes live?
Can we prove the claims we're making?
Is the information we're putting into the tool appropriate to share?
Does this still sound like our brand?
Does this content require transparency?
Does anyone involved have a relationship that needs to be disclosed?
The goal is not to make marketers afraid of AI. It is to make the boundaries clear enough that teams can use it confidently.
AI is another tool in the marketer's toolkit. It can help teams move faster, explore more ideas, and improve the work.
But the claims, creativity, context, and content that ultimately reach an audience still need people behind them.
Better marketing does not mean putting more of the process in AI's hands. It means knowing where AI helps, where humans need to step in, and who remains accountable when the work goes live.
This framework is practical guidance for marketing teams, not legal advice. Requirements vary by jurisdiction, industry, platform, and use case.