“Made with AI” gets lower engagement

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📝 Context

Topic: AI | Social Media 
For: B2C
Research date: May 2026
Universities: University of Southern California

Imagine you’re scrolling on Linkedin and you see one of my posts. It’s the usual format with our purple graphics, however, this time it says “AI-generated”. 

How would you feel? Would you be as likely to read and engage with it?

Science says you probably wouldn’t, why, and by how much engagement would drop.

P.S.: People have double standards when it comes to AI. We think it’s more acceptable when we use it, but not when others do. Keep this in mind when you create with AI and think about how it would be perceived by others.

📈 Recommendation

Be careful when using AI to generate content. If you do, make sure to explain you’ve still put effort into it, and why you’re using it (e.g. “I spent 20 minutes on this visual and used this model to create special effects”).

People will be more likely to engage with your content.

🎓 Findings

• When people know a social media post is created with AI (e.g. has a “made with AI” label), they engage with it less.

• Across 8 experiments and an analysis of 1m TikTok posts, researchers found that when people knew posts were created with AI, posts:

  • Received 7 to 8% fewer likes 

  • They had 7% lower combined engagement (comments, shares) even if quality was the same

  • Creators were seen as putting 15.6% less effort into their work, and people felt 14.5% less connected to them

• The effect disappears when the AI used is considered complex, requiring effort to use (e.g. Photoshop Neural Filters)

🧠 Why it works

• We value things when we think other people have put time, care, and effort into making them.

• This also helps us feel connected to the creator, which makes us even more likely to engage with them. 

• However, when something is created with AI, we assume people have not put in the time and effort needed to create it.

• This makes us less likely to engage with the post.

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✋ Limitations

• The study only looked at social media content from creators. The effect might not apply in contexts where AI use is expected (e.g. AI-native accounts and influencers).

• The analysis was on a wide range of content types (e.g. video, video and audio, single image, image with text). We don’t know if the effect is stronger or weaker for exclusively text (e.g. newsletters) or audio-based content (e.g. podcasts).

• The effect might differ across content categories. For example, technical content coming from institutions (e.g. public health, tech, announcements) where social connection is less important, might still drive engagement if AI-created.

• Some kinds of AI content look realistic and without labels, it’s hard to spot they were not human-created. The effect might not apply to those cases.

👀 Real-life example

SheerLux, a fashion magazine, experimented with AI-generated content. They announced it on their page with a video of their new AI avatars.

❌ Issue: Compared to their usual engagement, this post got about half the engagement, and comments show mixed feelings.

✅ Solution: There are a few ways in which they could have made this content more effective:

• Specify how and what they've used AI for. For example, by saying that real people have put in the effort to research and create this extra-personalized content. 

• Match the AI avatars to content on innovative topics like tech innovation in fashion.

• Create content that makes viewers think about others (e.g. show something useful, solving relatable problems) to give it a boost and make people more likely to share it.

🔍 Study type

Online experiments and market observation (analysis of 1,135,817 TikTok posts from 8,650 accounts)

📖 Research

Made With AI: Consumer Engagement with Social Media Containing AI Disclosures. Journal of Consumer Research (May 2026)

🏫 Researchers

• Stephan Carney. Marshall School of Business, University of Southern California. 

• Ignacio Riveros. Marshall School of Business, University of Southern California. 

• Stephanie M. Tully. Marshall School of Business, University of Southern California. 

Remember: This is a new scientific discovery. In the future it will probably be better understood and could even be proven wrong (that’s how science works). It may also not be generalizable to your situation. If it’s a risky change, always test it on a small scale before rolling it out widely.

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🎓 It took me, a PhD analyst, and a marketing pro 12 hours to accurately turn this 75-page research paper into this 3min insight. 

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