From impressions to influence: Rethinking measurement in the age of AI 

The evolving media ecosystem, accelerated by generative AI (GenAI), is fundamentally reshaping how we measure success in communications. Traditional metrics like impressions and unique visitors per month (UVMs) are being disrupted, but this change represents not a collapse, but a necessary correction toward deeper, more meaningful engagement metrics. This moment presents an opportunity for communicators to redefine success — shifting from volume-based proxies to influence-driven insights that reflect true audience impact.

 

1. The decline of UVMs: A correction, not a collapse

 

For years, metrics like UVMs served as inflated proxies for the value of earned media. The advent of GenAI has disrupted this reliance. With tools like ChatGPT replacing traditional click-based behaviors, UVMs may decline, but they now signify something more valuable: intent, investment, and attention. The audience isn’t disappearing; it’s transforming. Growth is emerging in new platforms, behaviors, and ecosystems beyond traditional publishers.

 

The data is clear: top-tier publishers have reported a nearly 20% decline in UVMs over the past year. However, this decline reflects a natural evolution, where audiences demand more meaningful media experiences.

 

2. The era of “Everyone Is Media”

 

The democratization of influence is accelerating. New research shows that over a third of responses from large language models (LLMs) like ChatGPT draw on a diverse array of sources—spanning traditional journalism, Reddit threads, YouTube videos, academic papers, and even GitHub snippets. The implication is profound: everyone is media now. Influence stems from content that is well-structured, well-cited, and delivered at the right time.

 

Moreover, as LLMs shape behaviors, they are also transforming the purchase journey. E-commerce now accounts for one-fifth of top domains referenced by AI platforms. For communicators, failing to embrace this shift risks irrelevance.

 

3. Making media discoverable to machines

 

The partnership between humans and LLMs reshapes search behaviors and media strategies. Unlike traditional search engines that prioritize ranking and clicks, LLMs reorganize information based on user intent. Two clear behaviors are emerging:

 

• Awareness-driven queries: Broad, exploratory questions (e.g., “What’s a good skincare routine?”) often remain contained within AI-generated answers. Here, shaping the response becomes the primary way to exert influence, even if no clicks result.
• Action-driven queries: Specific, decision-focused questions (e.g., “Best sunscreen for sensitive skin in humid weather”) create opportunities to drive users to external sources. However, for content to surface, it must meet heightened standards for quality, credibility, and abundance.

 

In this context, earning discoverability requires communicators to understand how LLMs prioritize relevance and to craft content that directly aligns with user intent.

 

4. Earning influence through culture

 

In the AI-influenced media landscape, influence is earned—not paid. Brands achieve relevance by carving out a distinct role in culture, adhering to the following principles:

 

• Repeatability: Consistently show up in ways that reinforce the brand’s positioning.
• Value contribution: Deliver content that meaningfully addresses audience needs.
• Alignment: Ensure strategies intuitively resonate with both the brand and its audience.

 

By embedding themselves into cultural conversations, brands can organically rise to the top of AI-curated responses, driving deeper engagement and lasting relevance.

 

5. A new measurement mandate: From impressions to influence

 

Generative AI has revealed what communicators have long suspected: impressions and UVMs were never adequate measures of influence. While GenAI has disrupted these traditional metrics, it also provides powerful tools to replace them.

 

The focus must shift from “How many people saw it?” to questions like:

 

• Did it land? Was the message understood and well-received?
• Did it spread? Was the story shared widely, organically resonating with audiences?
• Did it stick? Did the audience take action, reflect intent, or change behavior?

 

New AI-powered methodologies now allow teams to track cultural penetration, narrative uptake, and intent signals—revealing metrics that truly reflect attention and engagement.

 

 

Final takeaway: Clarity over volume

 

This shift isn’t about reducing media impact but refining how we define and measure it. Impressions didn’t fail because of AI; they were insufficient all along. GenAI has simply exposed their shortcomings and opened the door for a more nuanced, influence-driven measurement framework. For senior executives and communications leaders, this is an opportunity to lead the transformation—adopting new tools, metrics, and strategies that align with the realities of the AI-powered media landscape.

 

Read the full report below.