Social Media Marketing Podcast
Episode: Recommended or Rejected: Does AI Trust You
Host: Michael Stelzner
Guest: Marcus Sheridan
Published: January 22, 2026
Episode Overview
This episode explores the fundamental shift in how consumers use AI tools for search and discovery and why it's critical for businesses and marketers to ensure their brands are trusted— and thus recommended— by AI. Michael Stelzner is joined by Marcus Sheridan (author, keynote speaker, founder of AITrustSignals.com) to discuss how AI recommendation systems operate, what “trust signals” matter most, practical strategies to boost visibility in AI-generated results, and how to future-proof your marketing approach as AI shapes online discovery.
Key Discussion Points and Insights
The AI-Driven Search Shift
- Google’s “blue links” are fading: The traditional model of search engines presenting a list of clickable links (the “blue links”) is being replaced by AI giving a single, direct answer.
- “You’re either recommended, part of the answer, or rejected. There’s nothing in between... There’s no page two.” – Marcus Sheridan [05:25-06:26]
- Changing consumer behavior: Increasing use of AI (e.g., ChatGPT, Gemini, Copilot) as primary sources for answers.
- By audience poll, half now use ChatGPT for answers—a number growing rapidly. [06:27]
The New Gatekeepers: Trust Signals and AI Authority
- Winning in the AI era: No longer about ranking for keywords—it’s about being recommended or omitted by AI.
- Trust signals defined: Any content—good or bad—about your company (articles, reviews, awards, videos, social content), created by you or others, that AI uses to judge your credibility.
- “If AI doesn’t trust us, they’re not going to recommend us.” – Marcus Sheridan [06:27]
- AI is moving towards acting as a trusted assistant: It needs accuracy, recency, authority, and proof behind recommendations, not just relevance. [08:01-09:03]
The Critical Categories of Trust Signals (and Actionable Steps)
Marcus Sheridan identifies three main types:
1. Technical Signals
- Schema markup: “Invisible” code on your website labelling data (e.g., reviews, FAQs, product variations, content freshness) for easier AI parsing.
- “One of the biggest components of AI getting what it wants is through what’s known as schema or advanced schema...” – Marcus Sheridan [19:56]
- Tip: Use AI to audit your schema by pasting your HTML and asking for missing markup. [21:44]
- Don’t block AI: Tools like Cloudflare can block AI’s access; if you do, your brand is invisible to LLMs. [24:44-25:55]
- “I want my stuff to be consumed by AI no different than I wanted it to be consumed by Google back in the day.” – Marcus Sheridan [25:30]
2. Brand Signals
- Reviews (the #1 brand trust signal): AI analyzes not just averages, but volume, recency, and especially negative reviews to build a “reputation graph.”
- “AI… reads the review and that dictates who they recommend, who they reject.” – Marcus Sheridan [26:30-28:24]
- Actions:
- Aggregate key reviews from all platforms on a single page, using proper schema and outbound links to original sources so AIs can ingest them—especially if direct API access (like Google) is limited. [29:38-31:14]
- Awards & Recognition: Dedicated pages for industry awards, team member credentials, and achievements (with explainers and outbound links) are powerful signals.
- “They will almost always cite an award or recognition that they have received before.” – Marcus Sheridan [31:49]
- Content Surface Area: Publish relevant content and show up across platforms—LinkedIn, YouTube, podcasts, etc. The broader your presence, the higher your trust score. [44:39-45:49]
3. Authority Signals
- Pricing Transparency (“the new must-have trust signal”):
- Robust pricing pages, with ranges, videos, and (where possible) estimators, are now vital. AI will reject brands that can’t answer “what will this cost?” [34:17-38:34]
- “If you don’t do it, you will definitively be rejected by AI… you will not be the one that’s recommended.” – Marcus Sheridan [37:43]
- Author bylines and expertise: Articles need clear authorship tied to author bio pages showing credentials, experience, and recognition. [39:07–40:26]
- Accurate, verifiable claims: Unsupported boasts will hurt you; link out to third-party proof of your claims (awards, certifications, media hits). [41:53–44:13]
AI Recommendations are Personalized
- No universal “#1” ranking: AI recommendations are user-tailored, so two people making the same query (e.g., “best roofer in Nashville”) may get entirely different answers based on their previous behavior and preferences. [14:24-15:23]
Rapidly Evolving Opportunity
- Real-time AI indexing: Updates and new trust signals are processed instantly, unlike Google’s historic (slower) index. [33:14]
- Window of opportunity: Most competitors haven’t pivoted to optimizing for AI yet—doing so early gives you a significant edge.
- “You have a window whereby the majority of your competitors are not sitting here thinking about things like schema…” – Marcus Sheridan [46:08]
Notable Quotes & Memorable Moments
-
On the new binary reality:
- “You’re either recommended—part of the answer—or you’re rejected. There’s nothing in between.”
— Marcus Sheridan [05:25]
- “You’re either recommended—part of the answer—or you’re rejected. There’s nothing in between.”
-
On the risk of invisibility:
- “If we do not show up in AI, you’re screwed.”
— Marcus Sheridan [10:23]
- “If we do not show up in AI, you’re screwed.”
-
On AI’s assessment of trust:
- “Every piece of content… every article… every video… these become trust signals. And AI is getting much better at consuming all of them.”
— Marcus Sheridan [11:37]
- “Every piece of content… every article… every video… these become trust signals. And AI is getting much better at consuming all of them.”
-
On the need for robust review and awards pages:
- “You want one hub on your site that highlights every platform and a bunch of the reviews from that platform. That is the best trust signal you can use.”
— Marcus Sheridan [30:08]
- “You want one hub on your site that highlights every platform and a bunch of the reviews from that platform. That is the best trust signal you can use.”
-
On pricing:
- “It has quickly become the fundamental trust signal… number one.”
— Marcus Sheridan [37:43]
- “It has quickly become the fundamental trust signal… number one.”
-
On content authority:
- “Content surface area—do they just talk about this one subject one time on their website, or do they talk about it 20 different times on their site… across five different platforms? …That’s a major authority signal.”
— Marcus Sheridan [45:08]
- “Content surface area—do they just talk about this one subject one time on their website, or do they talk about it 20 different times on their site… across five different platforms? …That’s a major authority signal.”
-
On the urgency for marketers:
- “This is a business opportunity that is huge. This is huge. This transcends… this is so big. This literally is going to make or break businesses down the road.”
— Michael Stelzner [47:17]
- “This is a business opportunity that is huge. This is huge. This transcends… this is so big. This literally is going to make or break businesses down the road.”
Important Segment Timestamps
- [03:59] – Why visibility in AI is critical for every marketer
- [05:25] – The end of “blue links” and the zero-sum future of AI answers
- [08:01] – The “three Fs” of innovation (faster, friction-free, fear reduction)
- [11:37] – The definition and role of trust signals
- [14:24] – How AI’s answers differ user-to-user (personalization)
- [19:55] – Essential technical trust signals: Schema and content freshness
- [23:58] – Why schema matters for AI parsing
- [26:33] – Reviews as the top brand signal and how AI interprets them
- [29:38] – The importance of aggregating reviews on your own site
- [31:49] – Industry awards as a trust signal
- [34:17] – Pricing transparency as the new top authority signal
- [39:07] – Author bios and accuracy of claims
- [44:39] – Content surface area: broad presence matters
- [46:08] – The wide-open opportunity for marketers proactive about AI
Actionable Takeaways
- Audit and enhance schema markup across your site using AI tools, ensuring last-updated dates, FAQs, reviews, and all content types are clearly labeled for bots.
- Create (and maintain) a reviews page showing actual reviews from multiple platforms, properly formatted and linked.
- Showcase all your awards, certifications, and third-party recognition on a dedicated, up-to-date page.
- Publish a robust pricing page or estimator that provides clear ranges and explanations—even if your service is custom.
- Consistently create expert-level content across multiple platforms with clear author attribution and outbound proofs of claims.
- Monitor how AI models “see” your brand by testing with accounts that have no search history or by toggling off personal training in AI tools.
Final Thoughts
The rise of AI recommendation and answer engines is redefining digital marketing. Visibility, trust, and authority aren’t about being #1 on Google anymore—they’re about AIs knowing and trusting your brand (or not knowing you at all). Marketers who embrace the new rules—technical, brand, and authority signals—will own the future of discovery and lead generation. Those who cling to legacy search tactics risk becoming invisible.
For More Info
- Marcus Sheridan: AITrustSignals.com, LinkedIn
- Show notes: socialmediaexaminer.com/702
- Social Media Marketing World 2026: Info and tickets
- Michael Stelzner’s AI Explored podcast: Listen here