Marketing was one of the first functions to adopt generative AI widely, and one of the first to discover its pitfalls. Teams that treat AI as a volume machine often end up with generic content that performs poorly. Teams that use it to research faster, test more ideas and personalize at scale see real gains.
Updated September 2026: we added links to Google’s guidance on AI content, the FTC’s rule on fake reviews and YouTube’s disclosure requirements.
High-value uses
Research and insight. Summarize customer reviews, survey responses, support tickets and sales call notes to find recurring themes. This kind of synthesis used to take days.
Briefs and ideation. Generate angles, headlines and campaign concepts, then let people choose and develop the best ones.
First drafts and variants. Draft emails, landing page sections, social posts and ad copy, and produce variants for testing.
Repurposing. Turn a webinar into a blog post, social clips, an email and a summary, using tools covered in our video tools guide.
Localization. Adapt campaigns across languages, with review by fluent speakers.
Analysis. Ask questions of campaign data, find anomalies and draft reports. See our spreadsheet guide for tips.
Content and search: quality over volume
Google’s guidance is clear that it rewards helpful, reliable, people-first content and that using automation to produce large amounts of low-value content primarily to manipulate rankings violates its spam policies. AI use itself is not penalized. In practice, this means:
- Add genuine expertise, experience and original insight, not just a rewrite of what already ranks
- Fact-check every claim
- Have a knowledgeable person edit and stand behind each piece
- Publish less, better
We made a similar argument in our column on AI-written content.
Personalization done responsibly
AI can tailor messages to segments and behaviors. Stay within your privacy notices and consent, avoid using sensitive personal data for targeting, and remember that some personalization feels intrusive rather than helpful.
Brand safety rules
- Keep a documented brand voice and give it to your AI tools, as in our custom assistant guide.
- Review all customer-facing output before it goes live.
- Never generate fake reviews or testimonials; regulators treat fake reviews, including AI-generated ones, as deceptive. In the US, an FTC rule finalized in August 2024 bans them and allows civil penalties.
- Check images for rights issues and do not depict real people without permission.
- Label AI-generated realistic imagery where platforms require it; YouTube, for example, has required disclosure of realistic synthetic content since March 2024.
A workflow that works Person writes the brief and key points. AI drafts variants. Person edits for voice, accuracy and insight. AI checks against the brief and style guide. Person approves.
Measuring impact
Track time saved per asset alongside performance: engagement, conversion and quality scores. Our ROI guide explains how to set baselines.
Speed needs standards
AI gives marketing teams speed. Strategy, taste, customer insight and editorial standards still decide whether that speed produces results or just more noise.
Sources
- Google Search’s guidance about AI-generated content, Google Search Central, February 2023
- Federal Trade Commission Announces Final Rule Banning Fake Reviews and Testimonials, FTC, August 2024
- How we’re helping creators disclose altered or synthetic content, YouTube, March 2024
