Credibility is becoming the key driver of AI-driven visibility, not SEO keywords. AI systems surface brands they trust, not just pages that rank (Rzeszucinski, 2025). For most businesses, that means treating AI search as an “earned-first” channel. This happens when applying the POEM model. Here, the POEM (Paid, Owned, Earned Media) works together to feed answer engines. It does not just focus on search result pages (Passionfruit, 2025; Kelly, 2025; Engati, n.d.; Fidlon, 2025).

From SEO To AI Visibility

Traditional SEO aims to rank pages for keyword-based queries and generate clicks. In contrast, AI search and answer engines summarise multiple sources into a single response. This approach is known as Answer Engine Optimisation (AEO). The objective is to be cited within these answers. It is not just to receive clicks (Melinn, 2025; Passionfruit, 2025; Wilson, 2025; Ngugi, 2026).

Key differences:

• Rankings, organic traffic, and on-page engagement measure SEO success. AI visibility success is defined by citations, mentions, and recommendations within AI-generated answers (Wilson, 2025).
• SEO content often targets search volume and phrases; AI-oriented content prioritises clear, question-led, human-readable explanations with strong contextual authority (Ngugi, 2026; Halko, n.d.).
• AI engines increasingly favour third‑party, independent coverage and research over brand‑only pages, which is the reason why many commentators describe AI visibility as “earned-first” media (Greenberg, 2025; Noff, 2025).

Why AI Visibility Is “Earned” Media

Emerging data shows that AI models disproportionately draw on third‑party, editorial, and research content when generating answers. One recent analysis found that most of the AI citations came from earned media sources.

This preference for earned media reflects how AI systems establish authority:

• Independent coverage, expert commentary, and research-backed articles signal trust and relevance (Noff, 2025; Fidlon, 2025).
• Widely distributed, republished stories in credible outlets can increase AI citations by over 300%, suggesting that broad earned distribution produces a measurable “citation lift” (Greenberg, 2025).
• AI models look for consistent mentions across the ecosystem, not one isolated SEO-optimised page, which makes PR, thought leadership, and collaborations structurally more important (Fidlon, 2025; Noff, 2025; Greenberg, 2025).

POEM: How Paid, Owned, Earned Drive AI Search

The POEM model positions AI visibility as an ecosystem strategy rather than a single-channel tactic (Fidlon, 2025; Engati n.d.; Bot Penguin, n.d.).

Paid Media: Amplify & Seed Signals

Paid remains essential, but its role shifts from “buying clicks” to “seeding the proof” that fuels earned visibility and AI trust (Engati n.d., Fidlon, 2025).

Effective roles of “paid” media:

• Promote high‑value, research- or insights-based content (reports, studies, proprietary data) that journalists, analysts, and niche publishers will reference, thereby creating future earned coverage (Fidlon, 2025; Noff, 2025).
• According to a Forbes Technology Council report (Rzeszucinski, 2025), using paid distribution channels such as social ads, native ads, sponsored newsletters, and syndication networks can help ensure your best-owned content reaches key editors, creators, and industry communities. The report also recommends coordinating paid campaigns with media pitches for launches and announcements so that paid and PR efforts work together and increase the likelihood that your content will be selected and referenced in the data AI systems analyse.

In summary, paid media serves as an accelerator and targeting tool for the stories you want the ecosystem and, ultimately, AI engines to recognise (Engati n.d.; Fidlon, 2025).

Owned Media: Structure For Answers

Websites, blogs, resource hubs, socials, and newsletters that are “owned” are foundational. However, their optimisation target is now AI “readability.” This is as important as human and search readability (Engati n.d., Bot Penguin, n.d., Wilson, 2025).

“Owned” media priorities for AI search:

• Create answer-first content: clearly structured FAQs, “what/why/how” explainers, comparison guides, definitions, and use cases that map to natural language questions, not just head terms (Wilson, 2025; Halko, n.d.; Ngugi, 2026).
• Refine clarity and context: strong introductions, explicit problem–solution framing, plain language, and clear entity naming so models can easily understand who you are, what you do, and where you operate (Halko, n.d.; Wilson, 2025).
• Publish evidence-based content: case studies, data stories, and original research that can be quoted and referenced by other publishers and, eventually, by AI engines themselves (Noff, 2025; Greenberg, 2025; Fidlon, 2025).

Robust owned content provides AI with coherent material to process. It also offers journalists, partners, and communities authoritative resources to reference. This bridges owned and earned media (Bot Penguin, n.d.; Noff, 2025; Fidlon, 2025).

Earned Media: Core Driver of AI Visibility

Earned media includes organic mentions in news, podcasts, reviews, industry blogs, and social discussions. It is emerging as the strongest predictor of AI visibility (Bot Penguin, n.d.; Noff, 2025; Fidlon, 2025; Engati, n.d.).

Current research and industry commentary highlight that:

• AI engines prefer recent, credible, well-structured third‑party stories when assembling answers, often prioritising niche and trade media alongside national outlets (Fidlon, 2025; Noff, 2025).
• When a brand’s content is republished across multiple independent sites, AI citation frequency can rise dramatically, indicating that broad earned distribution increases “surface area” for inclusion in answers (Greenberg, 2025).
• Relationship-driven PR, expert commentary, and consistent thought leadership are now core SEO levers by another name, because they feed the trust graph that AI systems utilise (Noff, 2025; Fidlon, 2025).

These conclusions are why many strategists now describe AI-driven visibility as a form of “earned media SEO.” Here, reputation and third‑party validation matter more than raw keyword volume (Noff, 2025; Toscano, 2025).

Practical Playbook: Building An AI-Ready Profile With POE Media

To succeed in AI search, businesses should develop an integrated POEM programme. Each channel should explicitly support AI visibility goals (Passionfruit, 2025; Wilson, 2025; Fidlon, 2025).

1. Define your “answer territories.”

• Identify 10–20 core questions you want to “own” in AI answers (e.g., “best coworking space pricing model in Melbourne” or “how to apply the AI 30% rule in marketing teams” (Wilson, 2025; Ngugi, 2026).
• Map these questions to each stage of the funnel—awareness, consideration, and decision—and align them with your core propositions and Ideal Customer Profiles (ICPs).

2. Build answer-first owned assets.

• Develop pillar pages and supporting articles that address each core question clearly and concisely, incorporating original insights or data, as well as relevant location and niche context (Ngugi, 2026; Halko, n.d.).
• Use systematic content patterns—FAQs, glossaries, step-by-steps, and comparison guides—which support both traditional SEO and answer engine optimisation (Melinn, 2025; Ngugi, 2026; Halko, n.d.).

3. Use paid to drive discovery, not dependency.

• Run tightly targeted campaigns to put your best explainer content, guides, and research in front of journalists, analysts, influencers, and community leaders, not only prospects (Greenberg, 2025; Fidlon, 2025).
• Test sponsored placements in high-authority industry newsletters or platforms where coverage may later become organic or editorially driven. Reduce spending as organic traction and citations increase (Fidlon, 2025; Noff, 2025).

4. Systematically engineer earned visibility.

• Establish a regular schedule of newsworthy stories, including proprietary data reports, industry benchmarks, expert predictions, and opinion pieces, and pitch them to relevant media and niche outlets (Fidlon, 2025; Noff, 2025).
• Encourage syndication and republishing of your content through reputable networks or partners to increase citation lift across AI systems (Greenberg, 2025; Fidlon, 2025).
• Encourage customer advocacy and community-generated content, such as reviews, testimonials, and forum posts, to provide an additional layer of earned signals within the ecosystem (Bot Penguin, n.d., Engati n.d.).

5. Monitor both SEO and AI visibility.

• Track classic SEO metrics (rankings, organic sessions, click-through rates (CTRs) alongside AI-specific signals such as brand mentions and citations in tools that monitor AI-generated answers (Passionfruit 2025; Wilson, 2025).
• Adjust topics, messaging, and PR focus based on your brand’s presence or absence in AI summaries, not just in search engine results pages (SERPs) (Passionfruit, 2025; Wilson, 2025; Fidlon, 2025).

When considered through the POEM framework, AI visibility is not a threat to SEO. It represents its next evolution. Paid and owned activities should be intentionally designed to generate the earned authority. This earned authority is what intelligent engines reward (Toscano, 2025; Wilson, 2025; Fidlon, 2025).

REFERENCES

Bot Penguin (n.d.), POEM Model-Paid, Owned and Earned Media, Bot Penguin, <https://botpenguin.com/glossary/poem-model>

Engati (n.d.). What is the POEM Framework? Engati, < https://www.engati.com/glossary/poem-model>

Fidlon, Z. (2025), How Paid, Earned, Shared and Owned Media Shape Generative Search Visibility, Search Engine Land, < https://searchengineland.com/paid-earned-shared-owned-media-generative-search-visibility-465603>

Greenberg, N. (2025), How Earned Media Distribution Expands AI Visibility: A First Look at “Citation Lift”, Stacker, <https://stacker.com/blog/how-earned-media-distribution-expands-ai-visibility-first-look-at-citation-lift>

Halko, A. (n.d), Answer Engine Optimisation (AEO) vs. AI Search Optimisation: What’s the Difference?, Insivia, <https://www.insivia.com/answer-engine-optimization-aeo-vs-ai-search-optimization-whats-the-difference/>

Melinn, C. (2025), What Is SEO and How Does It Work?, Digital Marketing Institute, <https://digitalmarketinginstitute.com/blog/what-is-seo>

Ngugi, L. (2026), AEO vs SEO: Key Differences and Importance in Digital Marketing, SEO, <https://www.seo.com/ai/aeo-vs-seo/>

Noff, A. (2025), Earned Media is the New SEO, and AI is Rewarding Authenticity, Forbes, <https://www.forbes.com/councils/forbesagencycouncil/2025/10/29/earned-media-is-the-new-seo-and-ai-is-rewarding-authenticity/>

Passionfruit (2025), AI Search vs SEO: Why AI Answers Beat SERPS Every Time, Passionfruit <https://www.getpassionfruit.com/blog/why-ai-answers-beat-serps-every-time-(and-what-to-do-about-it)>

Rzeszucinski, P. (2025), AI Search Is Here, and it is Already Impacting your SEO, Forbes, <https://www.forbes.com/councils/forbestechcouncil/2025/06/24/ai-search-is-here-and-its-already-impacting-your-seo/>

Toscano, J. (2025), AI is Destroying SEO. Rank Now Requires Answer Engine Optimisation, Forbes, <https://www.forbes.com/sites/joetoscano1/2025/09/03/ai-is-destroying-seo-rank-now-requires-answer-engine-optimization/>

Wilson, K (2025), AI Search Optimisation vs Traditional SEO: Key Differences, Exposure Ninja <https://exposureninja.com/blog/ai-search-optimisation-vs-seo/>