Are publisher licensing deals with AI companies affecting who gets cited? What's happening?

This is one of the most significant shifts in publishing economics in years. Let me share what the data shows:

The deal landscape:

How deals affect citations:

1. Training data inclusion - Licensed content is systematically included
2. Attribution requirements - Deals often mandate proper sourcing
3. Real-time access - Some deals include live content access
4. Visibility priority - Licensed sources may get preference

The uncomfortable truth:

Yes, the playing field is tilted. Publishers with resources to negotiate deals have advantages smaller publishers can’t match.

Small publisher perspective:

Our reality:

• 50K monthly visitors
• No realistic path to an OpenAI deal
• Our content appears in AI answers occasionally
• When it does, traffic back is minimal

What we’ve tried:

1. Blocked some AI crawlers (reduced our visibility further)
2. Focused on original research (helps somewhat)
3. Joined industry coalition discussions
4. Accepted that AI traffic may never be significant for us

The paradox:

If we block crawlers, we’re invisible. If we allow crawling, our content trains AI models without compensation. There’s no winning scenario for small publishers right now.

My conclusion:

We’ve shifted focus to community building, newsletter subscriptions, and direct audience relationships. AI visibility is a game we can’t win, so we’re playing a different game.

Legal perspective on the licensing landscape:

The Anthropic settlement matters:

$1.5B settlement for using pirated books established ~$3,000 per work valuation. This creates legal pressure for AI companies to license properly.

Ongoing litigation:

• Encyclopedia Britannica vs. Perplexity
• Penske Media vs. Google
• Multiple author class actions

What this means for publishers:

1. Legal precedent is building for compensation
2. AI companies are increasingly motivated to license
3. Smaller publishers may eventually benefit from collective action

My advice:

Document your content usage in AI systems. If you’re being cited without compensation, that documentation may have value in future legal or licensing discussions.

The legal landscape is evolving in publishers’ favor, but slowly.

Trade/tech publisher perspective:

Our niche advantage:

We cover a specialized B2B technology niche. Despite having no formal AI deals, we get cited consistently because:

1. We’re THE authority in our niche
2. Our original research is unique
3. Few competitors in our space
4. Technical accuracy matters in our domain

What this means:

The “big publisher advantage” is real for general news, but niche publishers with true expertise can still compete on authority.

Our approach:

• Double down on original research
• Publish first with breaking industry news
• Maintain technical accuracy standards
• Build expert author credentials

The lesson:

Expertise and uniqueness can overcome lack of licensing deals in specialized verticals.

Perspective on blocking AI crawlers:

The blocking trend:

• 32% of top 50 US news sites block OpenAI’s search crawler
• 40% block OpenAI’s training crawler
• 56% block Perplexity
• 60% block Anthropic crawlers

Why publishers block:

1. Leverage for licensing negotiations
2. Prevent content use without compensation
3. Protest current industry dynamics
4. Maintain some control over content

The catch:

Blocking reduces your AI visibility to zero. You’re invisible in AI search, which increasingly matters for discovery.

Strategic blocking:

Some publishers block training crawlers but allow search crawlers. This prevents training on your content while maintaining some visibility.

My take: Blocking is a negotiating tactic, not a long-term strategy. Eventually you need visibility.

Synthesizing the discussion. Here’s where I’ve landed:

The reality:

• Licensing deals do create advantages
• The playing field is tilted toward larger publishers
• Legal landscape is slowly evolving
• No perfect solution for small publishers

Our strategy going forward:

1. Niche authority focus

• Double down on what makes us unique
• Original research and data
• Expert author development

2. Community-first approach

• Newsletter subscriptions
• Direct audience relationships
• Less dependence on discovery platforms

3. Monitor and document

• Track our AI citations with Am I Cited
• Build documentation for future discussions
• Understand our current visibility

4. Industry participation

• Join collective bargaining discussions
• Support initiatives like RSL
• Advocate for fair compensation

The perspective shift:

We can’t out-spend News Corp. But we can out-specialize, out-community, and out-focus them in our specific domain.

Thanks for the candid discussion.

Looking ahead at the publisher-AI relationship:

Emerging solutions:

1. Cloudflare Pay Per Crawl - Micropayments for AI access
2. RSL (Real Simple Licensing) - Standardized licensing protocol
3. Microsoft Publisher Marketplace - Two-sided content marketplace

The trajectory:

AI companies are under increasing pressure to compensate publishers fairly. Legal precedent is building. Industry solutions are emerging.

Prediction:

Within 18-24 months, we’ll see more standardized licensing frameworks that give smaller publishers access to compensation they currently lack.

In the meantime:

Build direct audience relationships. AI discovery is one channel among many. Publishers who over-indexed on platform dependence before are making the same mistake with AI.

Data journalism perspective:

Our content gets cited more despite no deals.

Why? We produce original data that AI systems can’t get elsewhere:

• Proprietary datasets
• Original surveys and research
• Unique analysis and visualizations
• First-to-publish findings

The lesson:

AI systems need fresh, original data. If you produce it, you become valuable regardless of licensing status.

Practical application:

Whatever your niche:

• Conduct original surveys
• Create proprietary datasets
• Publish unique analysis
• Be first with data-driven stories

This makes you cite-worthy beyond what licensing deals can provide.

Revenue perspective on AI traffic:

Even with citations, the economics are challenging.

Research shows 93% of AI Mode searches end without a click. Publishers cited in AI responses receive attribution but minimal traffic.

The math:

Even publishers with $50M licensing deals are losing more than that in traffic value from AI summaries.

What this means:

Licensing deals are compensation for traffic cannibalization, not a path to growth.

The strategic question:

Is AI visibility worth pursuing if it doesn’t drive traffic? The answer depends on:

• Brand awareness value
• Authority positioning
• Audience expectations

Some publishers are deciding AI visibility isn’t worth the trade-offs.