Free preview. This lesson is part of a paid course that earns the ETA Specialist: AI for Marketing and Sales credential. About this course
Brand, accuracy, customer data and the law
In this lesson you'll
- Name the four ground rules for AI in marketing and sales
- Explain what the FTC's rule on fake reviews and testimonials means for AI-generated content
- Sort customer data into OK, ask first and never for your AI tools
Welcome
Welcome to AI for Marketing and Sales from the Enterprise Technology Association (ETA). Marketing and sales were among the first functions to use AI at scale, because so much of the work is research, writing and personalization. That also makes them the place where AI mistakes go public fastest. This course assumes you've completed Level 1: Foundations of the ETA Certified AI Empowered Professional.
- Step 1: Assess
Is this a good task for AI, and what's at stake?
- Step 2: Direct
Brief the AI clearly: goal, context, constraints, done criteria.
- Step 3: Assure
Check the output before you rely on it.
- Step 4: Protect
Keep people, data and your organization safe.
- Step 5: Tune
Iterate, then save what works for next time.
Use the steps in order on every task, and loop back to Tune when results fall short.
The four ground rules
- Brand. Everything that goes out sounds like your organization and keeps its promises. AI drafts; a person who knows the brand approves.
- Accuracy. Every claim about your product, price, results or competitors is true and supported. AI tools invent plausible details: features you don't have, statistics no one measured, quotes no one said.
- Customer data. Customer and prospect data goes only into tools your policy approves, for purposes people would expect.
- Honesty with people. Don't deceive people about who they're dealing with or what others think of you.
What the law already says
You don't need new AI laws to get in trouble with AI in marketing. Existing rules apply.
- Truth in advertising. In the US, the FTC Act bars deceptive claims. A false claim is false whether a person or an AI wrote it.
- Fake reviews and testimonials. The FTC's rule on consumer reviews and testimonials, in effect since October 21, 2024, bans creating, buying or spreading fake reviews and testimonials, including ones that misrepresent that the reviewer exists, which covers AI-generated reviews. It also restricts undisclosed insider reviews and buying positive reviews.
- Email and calls. CAN-SPAM sets rules for commercial email, such as honest subject lines and a working opt-out. The FCC has ruled that AI-generated voices count as "artificial" voices under the Telephone Consumer Protection Act, so robocall consent rules apply to AI voice calls.
- Privacy laws. State privacy laws, and laws in other countries where you market, limit how personal data can be used. Your legal team knows which apply.
This is a summary, not legal advice. When in doubt, ask legal or compliance.
Customer data in AI tools
Passwords, access codes, security keys and other credentials
- Personal information
Social Security numbers, birth dates, home addresses, personal phone numbers
- Health information
Diagnoses, medical leave details, patient records
- Financial account details
Bank and card numbers, individual pay records
- Student records
Grades, discipline and other student information
- Confidential business and client information
Unreleased results, pricing, contracts, legal matters, anything under a confidentiality agreement
Some organizations approve specific tools for some of this data. That decision belongs to your organization, not to you. If you're unsure, treat it as off-limits and ask. You rarely need real details: redact, substitute or generalize.
| Usually OK in an approved tool | Ask first | Never |
|---|---|---|
| Public company information, your published content, anonymized campaign results | Named contacts and their emails, CRM notes, call recordings | Payment card data, account numbers, health or financial details about individuals, data your privacy notice didn't cover |
Workplace example: a regional home builder
The marketing coordinator asked an AI tool to "write 10 customer testimonials for our new website." It produced warm, specific quotes from homeowners who didn't exist. She caught it, deleted them, and instead asked five real buyers for permission to quote them. The AI then helped edit the real quotes for length, with each buyer approving the final wording.
Try it
Write your team's ground rules in your approved AI tool, then check them yourself:
Goal: Draft a one-page list of AI ground rules for our [marketing / sales] team.
Context: We sell [product or service] to [audience]. We use [tools].
Audience: Our team, mixed experience with AI.
Constraints: Cover brand approval, claim accuracy, customer data (OK / ask first / never), and honesty (no fake reviews or testimonials, honest outreach). Don't state legal requirements as certain; say "confirm with legal."
Format: Four headings, 3 to 5 bullets each.
Done criteria: Fits on one page; every rule is something a person can check.Share the draft with your manager or legal contact before using it.
Key takeaways
- Four ground rules: brand, accuracy, customer data and honesty with people.
- Existing rules on deceptive claims, fake reviews, email and calls apply to AI-generated work.
- Sort customer data into OK, ask first and never, and follow your policy and legal team.
Sources