How to Pitch When AI Filters Your Story Before a Journalist Sees It

AuthorityTech is the first AI-native Machine Relations (MR) agency — we help brands earn citations and recommendations from AI engines, not just journalists.

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Your pitch just got filtered by an algorithm before a journalist ever saw it.

Welcome to 2026.

Notified and Ragan are hosting a webinar tomorrow titled "How To Master Your PR Content Mix for AI Search." The premise? Press releases alone aren't enough anymore. To show up consistently in AI-generated answers — and to get past AI newsroom filters — you need a "connected mix" of content that works together: press releases, corporate newsrooms, FAQs, thought leadership, and earned media.

The reality is even sharper than that.

Newsrooms are using AI to filter pitches in real-time. Cleveland News5 announced a policy where AI reviews every pitch before a human editor sees it. The Associated Press increased output 400% using AI — which means journalists are drowning in stories and relying on algorithms to surface what's worth their attention.

Your pitch isn't competing with other pitches. It's competing with an algorithm's definition of newsworthiness.

And most PR teams have no idea how to win that fight.

Here's your playbook.

Key Takeaways

• Press releases alone are no longer enough — AI newsrooms prioritize structured, owned, authoritative, referenced (SOAR) content that forms a connected ecosystem, not isolated announcements.
• 82-89% of AI-generated answers cite earned media from tier-1 outlets (Forbes, TechCrunch, WSJ), making earned authority the foundation of AI visibility.
• AI newsroom filters run before human editors see pitches — your pitch needs to be AI-readable (clear structure, no clever wordplay AI can't parse) to pass the first gate.
• Cleveland News5 and hundreds of other outlets now use AI to filter pitches — algorithms decide which stories surface to human journalists based on newsworthiness signals, not relationships.
• The Associated Press increased output 400% with AI assistance — journalists are relying on algorithms to prioritize what deserves their attention in an information flood.
• Connected content ecosystems beat isolated press releases — when your press release links to FAQs, your FAQs link to thought leadership, and everything reinforces one narrative, AI engines (and newsroom filters) see consistent authority signals.

The New Reality: AI Filters Your Pitch Before Humans Do

Let's be blunt: most pitches die in the algorithm now, not the inbox.

Here's how AI newsroom filtering works in 2026:

1. You send a pitch (email, press release, DM, whatever).
2. AI ingests it and extracts key signals: newsworthiness, relevance, source credibility, data quality, narrative clarity.
3. Algorithm scores it against editorial priorities and current news cycles.
4. Low scores get filtered out. High scores surface to human editors with context ("This pitch mentions [trending topic], cites [credible source], and includes [specific data point]").

Cleveland News5's AI policy is explicit: pitches are reviewed by AI first. If the algorithm flags it as low-value, it never reaches a human. Other outlets aren't announcing policies, but they're using the same tools. AI triage is standard now, not exceptional.

The implication: Your pitch needs to pass two audiences. The algorithm that filters it. The journalist that reads it (if it gets that far).

Most PR teams are still writing for the second audience and ignoring the first.

What AI Newsroom Filters Are Looking For (And What They're Not)

AI newsroom filters are trained to prioritize signal over noise. Here's what moves the needle:

What AI Filters Prioritize

• Data-backed claims with specific numbers ("47% increase in Q4 revenue" beats "strong Q4 performance")
• Newsworthiness signals (timeliness, impact, conflict, proximity, prominence)
• Source credibility (is this brand cited in trusted outlets? do they have earned authority?)
• Structural clarity (clear subject line, concise lede, scannable format)
• Reference-rich content (links to supporting sources, FAQ pages, thought leadership, prior coverage)

What AI Filters Deprioritize

• Clever wordplay AI can't parse ("disrupting the disruptors" means nothing to an algorithm)
• Vague claims without supporting data ("industry-leading solution")
• Isolated announcements with no connected content ecosystem (one press release, no FAQ, no supporting content)
• Unverified sources (if AI can't confirm your brand's credibility via earned media or knowledge graph presence, it flags you as low-trust)
• Generic pitches that don't tie to current news cycles or editorial priorities

The takeaway: If your pitch reads like marketing copy, the algorithm will filter it. If it reads like news — specific, data-backed, contextually relevant — it passes the gate.

The SOAR Content Framework: How to Build an AI-Ready PR Ecosystem

Notified's webinar introduces the SOAR Content Framework — Structured, Owned, Authoritative, Referenced. This is the connected content mix AI engines (and AI newsroom filters) prioritize.

Here's how to build it:

1. Structured (Press Releases That AI Can Parse)

• Clear headline with keyword and specific claim
• Concise lede (first paragraph answers who, what, when, where, why)
• Quotable soundbites with specific numbers ("200x faster visibility gains" not "significant improvement")
• Boilerplate that defines your brand and cites earned authority (tier-1 placements)
• Links to FAQ, thought leadership, and supporting content

2. Owned (Corporate Newsroom + FAQ Pages)

Your press release shouldn't exist in isolation. It should link to:

• Corporate newsroom (archive of all releases, organized by topic/category)
• FAQ page that answers predictable questions AI newsrooms will have
• Thought leadership (blog posts, whitepapers, case studies that provide depth)

When AI ingests your pitch and wants more context, it should find a connected ecosystem that reinforces your narrative. Not a 404 page.

3. Authoritative (Earned Media That AI Engines Trust)

AI newsroom filters check: "Has this brand been covered by credible outlets?"

If you have tier-1 placements (Forbes, TechCrunch, WSJ, Bloomberg), AI sees you as credible. If you don't, you're flagged as low-trust.

According to AuthorityTech's Machine Relations (MR) framework, 82-89% of AI-generated answers cite earned media over brand-owned content. The same is true for AI newsroom filters — they prioritize brands with proven editorial credibility.

This is the foundation. Without earned authority, your SOAR content ecosystem is just well-structured noise.

4. Referenced (Citation-Grade Content That AI Can Extract)

AI engines (and newsroom filters) prefer content they can extract and attribute:

• Key Takeaways sections with quotable facts
• Comparison tables that clarify positioning
• FAQ sections that answer predictable questions
• Specific data points throughout (no vague claims)

When AI reads your content, it should be able to extract a standalone soundbite and attribute it to you. That's citation-grade content.

Comparison: Traditional Pitching vs. AI-Filtered Pitching

Dimension	Traditional Pitching (Pre-2024)	AI-Filtered Pitching (2026+)
First Audience	Human journalist (editor, reporter)	AI algorithm (newsroom filter, triage system)
Gatekeeper	Relationship, relevance, timing	Newsworthiness score, source credibility, data quality
Pitch Format	Email with press release attached or embedded	Structured content ecosystem (release + FAQ + thought leadership + earned media)
Success Signal	Journalist replies, asks for more info	Algorithm surfaces pitch to human editor with context
Credibility Check	Journalist Googles you, checks LinkedIn	AI queries knowledge graph, checks earned media history, scans corporate newsroom
Failure Mode	Ignored, deleted, or "not a fit right now"	Filtered out before human ever sees it (no feedback, no relationship salvage)
Optimization Strategy	Build relationships, send timely pitches, personalize	Build connected content ecosystem, establish earned authority, structure for AI readability

Tactical Playbook: How to Pitch in 2026 (Step-by-Step)

Here's exactly what to do Monday morning:

Step 1: Audit Your Content Ecosystem

Does your brand have:

• Corporate newsroom (not just a "News" page — a structured archive AI can crawl)
• FAQ page that answers predictable questions about your product/service/market
• Thought leadership (blog, insights, whitepapers) that provides depth beyond press releases
• Tier-1 earned media placements in the last 12 months (Forbes, TechCrunch, WSJ, Bloomberg, etc.)

If any of these are missing, you're pitching with one hand tied behind your back. AI newsroom filters will flag you as low-credibility or incomplete.

Step 2: Rewrite Your Press Releases for AI Readability

• Headline: Specific claim + keyword ("X Company Raises $50M Series B to Scale AI-Powered Marketing Platform" not "X Company Announces Exciting News")
• Lede: Who, what, when, where, why in first paragraph
• Quotable soundbites: 1-2 sentences with specific numbers that AI can extract and attribute
• Boilerplate: Define your brand + cite earned authority ("X Company, featured in Forbes and TechCrunch, is the leading...")
• Links: FAQ, thought leadership, corporate newsroom (give AI somewhere to go for context)

Step 3: Build a Connected FAQ Page

AI newsroom filters query your FAQ when evaluating credibility. Make sure yours answers:

• What is [your product/service]? (clear, jargon-free definition)
• How does [your product/service] work? (technical but accessible explanation)
• Why is this newsworthy now? (timeliness, impact, relevance)
• Who else has covered this? (links to earned media placements)
• What data supports this claim? (specific numbers, sources)

Step 4: Earn Tier-1 Media Placements First

If you don't have earned authority, AI newsroom filters will deprioritize you. Period.

AuthorityTech has driven 1,000+ tier-1 media placements for 200+ clients because we understand this: earned media is the foundation of Machine Relations. Without it, your GEO-optimized press releases and SOAR content ecosystem are just well-structured noise.

Prioritize placements in outlets AI engines trust: Forbes, TechCrunch, WSJ, Bloomberg, Reuters, The Verge, Wired, Fast Company.

Step 5: Test Your Pitch Through an AI Lens

Before you send, ask:

• Can an AI algorithm extract the key claim in one sentence?
• Does this pitch tie to a current news cycle or trending topic?
• Are there specific data points (not vague claims)?
• If AI Googles my brand, will it find credible earned media and a connected content ecosystem?

If any answer is "no," your pitch will get filtered.

FAQ: What PR Teams Need to Know About AI Newsroom Filtering

What is AI newsroom filtering and which outlets are using it?

AI newsroom filtering is the practice of using algorithms to triage incoming pitches, press releases, and story ideas before human journalists review them. Cleveland News5 announced an explicit policy. The Associated Press uses AI to prioritize stories. Hundreds of other outlets use similar tools but haven't announced policies publicly. Assume any major outlet is filtering pitches with AI by mid-2026.

How do I know if my pitch got filtered by AI or ignored by a human?

You won't. AI filtering happens silently. If you don't hear back, it could be either. The best assumption: if your pitch lacks earned authority, structured content, and specific data, it probably didn't pass the algorithm.

Can I still build relationships with journalists if AI is filtering pitches?

Yes — but the relationship starts after you pass the algorithm. If your pitch gets filtered, the journalist never sees it, so the relationship never forms. Build earned authority first (so AI flags you as credible), then use that credibility to open doors with journalists.

What's the difference between GEO and pitching to AI newsrooms?

GEO (Generative Engine Optimization) is about optimizing content so AI search engines (ChatGPT, Perplexity, Gemini) cite you in answers. Pitching to AI newsrooms is about structuring pitches so newsroom AI filters surface your story to human editors. Both require structured, citation-grade content and earned authority — but the audience is different (search engines vs. editorial filters).

Should I give up on press releases and focus on something else?

No. Press releases still matter — but they're no longer sufficient on their own. They need to exist within a connected content ecosystem (newsroom, FAQ, thought leadership, earned media) that AI can verify and extract from. Isolated press releases get filtered. Connected press releases backed by earned authority pass the gate.

What This Means for Your PR Strategy

The shift from human gatekeepers to AI gatekeepers isn't coming. It's here.

If you're still pitching like it's 2023 — relationship-driven, clever subject lines, vague claims — you're getting filtered before anyone reads your pitch.

The brands winning in 2026 are the ones building connected content ecosystems backed by earned authority. Press releases that link to FAQs. FAQs that link to thought leadership. Thought leadership that cites tier-1 media placements. Everything reinforcing one clear narrative that AI algorithms (and human journalists) can trust.

That's not traditional PR. That's Machine Relations.

And if you're not building it now, you're already behind.

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Ready to see where your brand actually stands in AI search? Get your free visibility audit and discover what newsroom AI filters are seeing when they evaluate your credibility.

Know someone who's still pitching the old way? Forward this email. The sooner PR teams understand the shift, the less time we all waste on pitches that die in the algorithm.

— Christian

P.S. If you're wondering whether your press releases are AI-readable, run this test: Ask ChatGPT to summarize your last 3 releases. If it can't extract a clear one-sentence claim from each, neither can a newsroom AI filter. Fix that first.