The Wikimedia Foundation just dropped some bombs:
Direct quote: “AI cannot exist without the human effort that goes into building open and nonprofit information sources like Wikipedia.”
The data:
The implications:
My questions:
This feels like a pivotal moment for the entire AI industry.
I work in ML training. Let me explain why this matters technically.
Why Wikipedia is irreplaceable:
What happens without Wikipedia:
We tested models trained excluding Wikipedia:
The economic reality:
Building something like Wikipedia from scratch would cost billions. AI companies got it for free. Now the infrastructure is straining.
This is a classic tragedy of the commons playing out in real-time.
Long-time Wikipedia contributor here. The volunteer perspective:
What we’re feeling:
We’ve spent thousands of hours building this knowledge base. Now:
The bandwidth crisis is real:
Jimmy Carter’s page + video = temporarily maxed several internet connections That’s from ONE article going viral with AI traffic
What we want:
The irony:
If Wikipedia degrades due to lack of resources, AI models degrade too. They need us healthy to stay healthy.
I study model collapse. Let me explain why Wikipedia is essential for AI’s future.
Model collapse in simple terms:
When AI trains on AI-generated content:
The Nature study (2024):
Showed recursive AI training causes “irreversible forgetting” of original content. Each generation of AI gets worse.
Why Wikipedia prevents this:
Wikipedia is STRICTLY human-curated:
The strategic importance:
As AI-generated content floods the internet, Wikipedia becomes MORE valuable, not less. It’s the anchor of truth in a sea of synthetic content.
Brands that get properly represented on Wikipedia will have advantages as AI increasingly relies on verifiable sources.
Running an AI company. Here’s the business reality:
The uncomfortable truth:
We absolutely depend on Wikipedia. Our model quality is directly tied to Wikipedia quality. We should pay for it.
What we’re doing:
Why more companies should do this:
The cost:
Less than 0.1% of our compute costs. Trivial.
The risk of not paying:
If Wikipedia restricts access or degrades in quality, our model quality suffers. It’s risk management, not charity.
Let’s talk practical implications for brands:
The training data hierarchy:
| Source | AI Training Value | Brand Control |
|---|---|---|
| Wikipedia | Highest | Lowest (can’t directly edit) |
| News sites | High | Medium (through PR/coverage) |
| Company sites | Medium | Highest |
| Social media | Medium | Medium |
| User forums | Medium-Low | Low |
Strategic implications:
Wikipedia matters most, but you control least
Your website matters less for AI
News and authoritative sources are key
The Am I Cited angle:
Monitor how AI synthesizes information about your brand across all sources. The output tells you which inputs are working.
I negotiate data licensing deals. Here’s what’s coming:
The licensing landscape:
Expected pricing structure:
Per-crawl fees (for training)
+ Per-query fees (for RAG/grounding)
+ Base access fee
= Sustainable Wikipedia funding
What this means for AI products:
Costs will increase. But it’s still cheaper than:
What this means for brands:
As AI access to Wikipedia becomes more formal:
The open source/commons perspective:
The CC-BY-SA license requires:
AI companies are arguably violating this:
The philosophical question:
Wikipedia was built for human knowledge sharing. Is training commercial AI what the community intended?
My view:
The license allows commercial use. But the spirit of Wikipedia is open access to knowledge for humans. AI companies should contribute back.
What brands should know:
Your content, if cited by Wikipedia, enters this commons. This can be powerful - but you lose control over how it’s used by AI systems.
Multilingual perspective:
Wikipedia’s 300+ language editions matter:
For global brands:
Your Wikipedia presence in multiple languages affects AI responses in those languages.
What we discovered:
Our German Wikipedia page was minimal. ChatGPT’s German responses about our company were vague and sometimes wrong.
The fix:
Generated more German media coverage → German Wikipedia page improved → German ChatGPT responses improved
Key insight:
Each language is a separate AI visibility challenge. Monitor across all relevant markets.
Looking ahead 3-5 years:
Likely developments:
Mandatory licensing
Improved attribution
Quality control mechanisms
New content types
What this means for AI visibility:
Wikipedia’s importance will INCREASE, not decrease. As AI access becomes formalized:
Start building Wikipedia-worthy notability now. It takes years.
Excellent discussion. Here’s my synthesis:
The fundamental reality:
Wikipedia is AI infrastructure. Not optional - required. The Wikimedia Foundation’s statement is literally true: “AI cannot exist without Wikipedia.”
What this means for AI development:
What this means for brands:
The action items:
For AI companies:
For brands:
The Wikipedia-AI relationship will only become more important. Plan accordingly.
Get personalized help from our team. We'll respond within 24 hours.
Monitor how your content influences AI-generated answers and understand the sources AI uses to represent your brand.
Community discussion on Wikipedia's dominant role in AI citations. Real experiences from marketers and SEO professionals on leveraging Wikipedia for AI visibili...
Community discussion on Wikidata entries for AI visibility. Real experiences from SEO professionals on creating Wikidata entries to improve AI search presence.
Community discussion on the role of news publishers in AI search engines. Real experiences from content creators, journalists, and marketers on how AI platforms...
Cookie Consent
We use cookies to enhance your browsing experience and analyze our traffic. See our privacy policy.