The landscape of strategic communications is currently undergoing a significant transformation as organizations grapple with the implications of artificial intelligence (AI) on brand visibility. Recent industry research has ignited a debate over the continued relevance of the PESO Model—an integrated framework encompassing Paid, Earned, Shared, and Owned media—in an environment where Large Language Models (LLMs) like ChatGPT, Claude, and Perplexity are becoming primary search and discovery tools. Two distinct studies published in mid-2024 have highlighted a growing divergence between public relations (PR) professionals and marketers regarding which media types most effectively influence AI discoverability, while simultaneously exposing a critical "confidence gap" between agencies and the brands they serve.
The Duel of Data: PR vs. Marketing Perspectives
The discourse began with the release of a report by D S Simon titled “Earned Media in the AI Era: Disrupting the PESO Model®.” The study surveyed 168 brand and agency PR executives to determine which component of the PESO framework holds the most weight in ensuring a brand is "discovered" and cited by AI models. The findings were heavily skewed toward traditional PR strengths: 44% of respondents identified Earned media as the most vital factor for AI discoverability. Paid media followed in second place, while Owned media ranked third. Notably, only 5% of PR executives believed Shared (social) media was the most important factor in this new era.
However, a secondary survey conducted by Sword and the Script Media presented a contrasting narrative. Surveying 200 U.S. marketing and communications professionals—the majority of whom were in-house marketers—the study asked which media type has the most significant impact on AI visibility. In this cohort, Paid media emerged as the leader with 35% of the vote. Shared media followed at 28%, Earned media at 24%, and Owned media trailed at 14%.
Analysts point out that these results suggest a "confirmation bias" within professional silos. PR practitioners, whose primary currency is Earned media (media relations and third-party validation), naturally view it as the most effective tool. Conversely, marketers, who often control larger budgets dedicated to Paid and Shared channels, prioritize those avenues. This discrepancy highlights a fundamental tension in the industry: professionals tend to equate the media they purchase or manage with the media that provides the most strategic value.
Chronology of the Shift: From SEO to AI Visibility
The transition from traditional Search Engine Optimization (SEO) to AI-driven discovery has occurred with remarkable speed over the last 24 months.
- Late 2022: The public launch of ChatGPT introduced the concept of conversational search, where users receive synthesized answers rather than a list of links.
- Early 2023: Search engines began integrating generative AI (e.g., Microsoft’s Bing AI and Google’s Search Generative Experience), forcing brands to consider how their content is summarized.
- Mid-2024: The emergence of "Answer Engines" like Perplexity and SearchGPT shifted the focus toward citation. For a brand to be mentioned in an AI response, it must exist within the training data or be accessible via real-time web crawling.
In this new chronology, the traditional "linear" path of a customer journey—seeing an ad, searching on Google, and visiting a website—is being replaced by a "synthetic" journey where an AI model acts as an intermediary. Consequently, the industry is moving toward "Visibility Engineering," a strategy where Owned and Earned media serve as the primary signals for AI models, while Shared and Paid media serve as amplifiers for those signals.
The Mechanics of AI Discoverability
To understand why Earned and Owned media are increasingly viewed as the "engine" of AI visibility, it is necessary to examine how LLMs process information. AI models prioritize high-authority, third-party sources to verify facts and determine credibility. A mention in a reputable news outlet (Earned media) acts as a high-quality "backlink" for an AI model, signaling that the information is trustworthy.
However, Earned media cannot function in a vacuum. Industry experts argue that for a media mention to be effective, it must point back to robust Owned media properties. This includes technical documentation, white papers, executive bylines, and comprehensive FAQ pages. If an AI model identifies a brand through an Earned media citation but finds the brand’s Owned content to be "thin" or lacking depth, the model may fail to synthesize a detailed or accurate response about the company.
Despite this, the Sword and the Script survey found that only 14% of marketers believe Owned media is the most important factor. This suggests a potential strategic failure; many organizations are investing in visibility (Paid and Earned) without ensuring their "ground truth" (Owned) is prepared to receive the resulting traffic or crawl requests.
The Confidence Gap and the Measurement Crisis
Perhaps the most significant finding buried within the D S Simon report is the "confidence gap" between service providers and clients. According to the data, 87% of PR agencies believe they are successfully optimizing their clients’ content for AI discoverability. In stark contrast, only 59% of brand-side respondents agree with that assessment.
This 28-point discrepancy is largely attributed to a lack of standardized measurement. When asked about barriers to success:
- Brands cited a "lack of clear measurement" as their primary concern (44%).
- Agencies ranked measurement as a low priority, placing it fifth on their list of challenges. Instead, agencies identified the "client relationship" and "internal alignment" as their top hurdles.
This misalignment suggests a looming crisis in the agency-client dynamic. Agencies are reporting success based on traditional metrics—such as the number of placements or "share of voice"—while brands are struggling to see how those activities translate into AI-driven results. Without a shared framework for what "success" looks like in an AI context, the tension between these parties is expected to increase.
Broader Impact and Industry Implications
The integration of AI into the PESO Model is not a disruption of the framework itself, but rather a clarification of its internal mechanics. Historically, some practitioners viewed the letters in PESO as a sequence or a hierarchy of importance, often putting Paid first due to its position in the acronym. However, the current data suggests that the model functions more effectively as an "OESP" sequence: Owned and Earned building the foundation of authority, followed by Shared and Paid distribution.
For marketing and communications teams, the implications are three-fold:
1. The Primacy of Integration over Silos
The fact that PR pros and marketers gave nearly opposite answers regarding media importance indicates that many organizations are still operating in silos. AI models do not distinguish between a "marketing" signal and a "PR" signal; they ingest the totality of a brand’s digital footprint. Organizations that fail to integrate their PESO activities risk sending fragmented or contradictory signals to AI crawlers.
2. The Necessity of a New Measurement Standard
Traditional KPIs, such as "Ad Value Equivalency" (AVE) or even standard click-through rates, are insufficient for measuring AI visibility. New metrics are required, such as "Citation Share" (how often a brand is cited by an LLM compared to competitors) and "Prompt Accuracy" (how accurately an AI model describes a brand’s core value proposition).
3. The Role of Paid Media as an Amplifier, Not a Source
While 35% of marketers believe Paid media is the most important for AI visibility, there is currently little evidence to suggest that advertising spend directly influences the training data or the organic output of LLMs. Paid media remains a powerful tool for driving immediate traffic, but it cannot replace the long-term authority generated by Earned and Owned media.
Conclusion: Refining the Operating System
The debate sparked by recent surveys underscores that the PESO Model remains a vital "operating system" for modern communications, provided it is applied with an understanding of AI’s technical requirements. The "disruption" claimed by some analysts is, in reality, a validation of the model’s original intent: that no single media type is sufficient on its own.
As organizations look toward 2025, the focus is likely to shift from "buying visibility" to "engineering authority." This will require a pivot toward high-quality Owned content and strategic Earned media placements, supported by a rigorous measurement framework that can prove value to brand stakeholders. The agencies that bridge the 28-point confidence gap by providing transparent, data-driven insights into AI performance will likely emerge as the leaders in this new era of digital strategy. In the final analysis, Earned media is not disrupting the model; it is simply proving to be a critical component of the engine that drives AI discovery.
