The Rise of Human Content and AEO Opportunities Amid AI Spam

Editor’s Pick · A Serial AI Entrepreneur’s Take (Content distilled by AI; views belong to the original author; reading the source is optional.)

The article notes that Dianping removed 11.61 million AI reviews (A· Platform Data), while LinkedIn’s new reporting button caused AI-driven article views to drop by 40% (A· Platform Data), revealing a crackdown on AI spam across platforms. For monetizers, this signals surging demand for authentic original content and AEO/GEO optimization services—ideal for those with content or SEO experience. The biggest pitfall lies in confusing SEO logic rather than grasping how AI citations actually work. Next step: test your brand’s visibility in ChatGPT responses.

• Build an account centered on authentic original content and explicitly label it as human-authored to earn platform recommendation.
• Run AEO service tests for B2B clients, measuring how often their brand appears in ChatGPT answers and why.
• Step away from automated AI content factories and pivot toward deep, human-written reviews and real-experience sharing.

1. What’s the opportunity?

As major content platforms tighten restrictions on AI-generated spam, there’s room to offer two things: “authentic original content” and AEO/GEO (Answer Engine Optimization / Generative Engine Optimization) services. The former taps into users’ craving for a genuine human voice; the latter helps brands secure placement in AI-generated answers on ChatGPT and similar tools. Target customers include B2B brands that need to protect their AI-facing reputation and C-end creators hunting for traffic upside.

2. Independent assessment

Worth pursuing, but the track is splitting. LinkedIn’s suppression of AI articles after adding the reporting button cut views by 40%, proving users strongly reject homogeneous AI content—human content now carries real scarcity. That said, AEO/GEO isn’t pure traffic arbitrage; it’s essentially “SEO for the AI era,” and the core lies in understanding AI citation logic rather than keyword stuffing. Slapping old SEO habits onto AEO will likely lead into the same trap described in the article—flooding Reddit with marketing accounts—and your service will fall flat.

3. Cold-start playbook

Step one is validation: pick three to five niche categories (e.g., sensitive-skin skincare, workplace productivity tools), then test how brands perform in ChatGPT and Perplexity answers—note whether they’re mentioned, the reasoning behind recommendations, and which sources get cited. Cost is minimal (API calls or manual lookup), and the cycle runs 1–2 weeks. From that research, produce a white paper such as “AI Citation Performance in the XX Category” and use it as a hook to sell “AI visibility optimization” packages to brands.

4. Biggest risk and how to avoid it

• Mixing up SEO and AEO logic: Traditional SEO fights for ranking; AEO fights for citation accuracy and authority. If you just mass-post in communities (the Honeydew Labs case in the article is a cautionary example), platform algorithms will flag you as a bot or marketing account and throttle or ban you. Mitigation: Build a pool of real human experts and produce deep, traceable first-hand experience data instead of churning out AI-generated reviews at scale.
• Platform-policy volatility: Platforms vary in how harshly they target AI content—Snapchat bans pure-AI posts from its feed, TikTok lets users toggle AI disclosures. Over-relying on a single platform means policy tightening can wipe out your traffic overnight. Mitigation: Distribute across multiple channels and prioritize high-authority communities like Reddit, which feed directly into large-model training corpora.

5. Case breakdown (what others are doing)

• Platform cleanup: LinkedIn’s “AI spam” report button drove a 40% view drop for AI workplace posts the moment it launched; Dianping removed 11.61 million AI reviews last year; Spotify pulled 75 million AI-generated spam tracks. By restricting AI content supply, these platforms artificially boost the weight of human content.
• AEO gray-hat tactics (cautionary tale): Marketing accounts disguised themselves as helpful Redditors in skincare communities—first admitting they’d never used a competitor’s product, then spilling detailed notes on Honeydew Labs’ concentration, gentleness, and institutional endorsements. Each account lurked across multiple forums, steering any thread back to its own product. Short-term influence on AI training data is possible, but long-term this gets labeled as “marketing-account pollution.”
• Data-partnership endorsements: Google and OpenAI have both partnered with Reddit to license its community content for large-model training. That means high-quality human discussions on Reddit directly shape AI response tendencies—turning the “living human corpus” into a quantified asset.
• Platform-specific differentiation: Snapchat bans pure-AI video from Spotlight recommendations; human-shot footage plus AI edits must carry a disclosure tag to enter algorithmic distribution. Pinterest and TikTok hand the decision to users: whether to show AI content at all. These tolerance gaps should dictate your content-placement strategy.

6. Dual-track feasibility

Cross-border: feasible. Prioritize Reddit, LinkedIn, and other mainstream Western communities; leverage the higher acceptance of AEO/GEO concepts abroad to offer AI-search optimization for brands going global. Domestic (China): feasible but requires caution. Chinese platforms enforce stricter AI oversight, and Dianping already deploys AI-detection systems. A safer bet is to position as an operator of “human store-visits and in-depth product reviews,” sidestepping pure AI generation and relying on human endorsements to unlock organic platform-weight boosts.

Source · WeChat Official Account: Guokr · Read original article →