Anyone actually made money licensing content to AI companies? What's realistic for smaller publishers?

I’ve advised on several of these deals, including some at the smaller end. Here’s the reality:

The market is tiered:

What gives smaller publishers leverage:

1. Niche expertise - If you’re THE authority in a specialized field, that’s valuable
2. Unique data - Original research, proprietary datasets, historical archives
3. High-quality content - Well-structured, factually accurate, regularly updated
4. Clean rights - You own everything, no licensing complications

How to approach:

• Start by understanding what you have (content audit)
• Document your authority signals (citations, backlinks, expertise indicators)
• Approach through aggregators first if you’re smaller
• Consider collective licensing groups forming in your industry

One warning: Don’t accept the first offer. AI companies are still figuring out market rates.

I’ll share our actual experience since we’re similar scale to you:

Our situation:

• 20-year-old trade publication in manufacturing
• ~8,000 articles
• Strong industry reputation

What happened:

• Approached by an AI company aggregator (not OpenAI directly)
• Offered $175,000 for 3-year training rights
• We countered with display-only for $100K/year
• Settled on hybrid: Display rights + limited training on pre-2020 content
• Final deal: $150K upfront + $75K annually for 3 years

What gave us leverage:

• We’re the only comprehensive source for our niche
• Historical archives with unique data
• Expert bylines with real credentials
• Clean copyright ownership

The lesson: Specialty publishers have more leverage than you’d think. AI companies need diverse, authoritative content. General news is everywhere - niche expertise is rare.

Let me add the negotiation tactics that actually work:

Before any conversation:

1. Audit your content - What’s unique? What’s authoritative?
2. Document your value - How often is your content already cited in AI answers?
3. Understand your rights - Do you own everything? Any third-party content?
4. Know the market - What are similar publishers getting?

During negotiation:

• Never take the first offer (seriously, never)
• Separate training from display rights
• Ask for usage reporting requirements
• Include audit rights
• Negotiate for product access as part of the deal
• Include protective clauses (match any better deal they give competitors)

What to protect:

• Future content (don’t lock in prices for content you haven’t created)
• Specific high-value properties (exclude your best assets if appropriate)
• Your ability to license to competitors

Tools that help: Use Am I Cited or similar to document how often your content appears in AI answers. This data supports your negotiation position.

Legal considerations smaller publishers often miss:

Rights you MUST clarify:

• Do you own all content or are some articles freelance work-for-hire?
• Any third-party content (images, quotes, data) with licensing restrictions?
• Have you already granted any exclusive rights elsewhere?

Contract terms to insist on:

• Non-exclusivity (always)
• Clear termination rights
• Usage reporting requirements
• Audit rights
• Data deletion upon termination
• Attribution requirements

Red flags in AI licensing offers:

• Exclusive deals (unless payment is extraordinary)
• Perpetual licenses with no renewal terms
• Broad derivative works rights
• No usage reporting
• No attribution requirements

First-mover protection: If you’re early to license, include a clause letting you renegotiate if they later give better terms to competitors. AP reportedly got this from OpenAI.

Alternative perspective from someone who chose NOT to license:

We’re a content company with valuable industry analysis. Had licensing conversations but decided against it.

Why we said no:

• Our competitive advantage IS our unique content
• Worried about AI generating competing analysis
• Display-only deals weren’t enough revenue to matter
• Wanted to stay fully independent

What we did instead:

• Optimized content to be cited in AI answers (visibility without formal licensing)
• Built our brand through AI mentions
• Used AI visibility to drive subscription growth
• Kept training rights entirely to ourselves

Result: We get cited frequently, drive traffic, maintain complete control.

Point is: Licensing isn’t the only way to benefit from AI. Sometimes strategic visibility without formal deals is better for smaller players.

If you’re considering licensing, the first step is understanding your current AI presence:

What to measure before negotiations:

• How often is your content cited in AI answers?
• Which specific articles are most referenced?
• What prompts trigger your content?
• How do you compare to competitors?

Why this matters:

• Proves your content has AI value
• Identifies your most valuable assets
• Gives you negotiation leverage
• Helps you understand what to protect

We used monitoring tools to build this case before our licensing conversations. Showed the AI company we knew exactly how valuable our content was and what they were already using. Changed the conversation entirely.

Tools: Am I Cited lets you track citations across platforms. Essential for building your negotiation position.

Sharing our actual payment structure to help set expectations:

Our deal (mid-tier B2B publisher):

• Upfront: $500K
• Annual guarantee: $150K/year for 3 years
• Variable: Additional payment tied to citation volume
• Technology credits: $100K in API access
• Total potential value: ~$1.2M over 3 years

What we negotiated for:

• Quarterly usage reports
• Real-time dashboard access
• Audit rights annually
• Attribution requirements (our brand visible in citations)
• 6-month termination notice

What we protected:

• Training rights only for content older than 2 years
• Display rights for all content
• Excluded our premium research reports entirely
• Right to license same content to competitors

The deal isn’t transformative revenue, but it’s meaningful and gives us insight into how AI uses our content.

Market trends worth knowing:

The licensing market is consolidating:

• Big players (OpenAI, Google, Meta) are locking up major publishers
• Smaller AI companies may be more willing to deal with niche publishers
• Aggregators are forming to represent smaller publishers collectively

Pricing is still being established:

• Early deals set precedents (maybe too low)
• Some publishers regret early agreements
• First-mover clauses are becoming standard to protect pioneers

Emerging models:

• Usage-based pricing (pay per citation)
• Revenue sharing on AI-generated content
• Hybrid display + limited training deals
• Technology partnership deals (access to AI tools)

My prediction: The market will mature with standardized pricing by 2027. Right now, it’s still the Wild West, which can favor savvy smaller publishers who negotiate well.

Incredible information in this thread. Here’s my action plan:

Immediate steps:

1. Complete content audit - document what we own, what’s unique
2. Set up AI citation monitoring (Am I Cited looks right for this)
3. Build the case for our content’s value with data
4. Consult IP attorney to clarify our rights situation

Negotiation approach:

1. Start with display-only rights to minimize risk
2. Protect training rights for recent content
3. Consider archival training rights for older content
4. Include protective clauses (match competitors, audit rights, attribution)

Key insights I’m taking:

• Niche expertise is more valuable than I thought
• Separating training from display rights is crucial
• Non-exclusivity is standard - demand it
• Build leverage with data before any conversation
• Don’t take the first offer

Thank you all - this went from “is this even possible for us” to “here’s exactly how to approach it.”