Generative Everything Optimization: Survive the Wild of AI Mediation and Translation
What you’ll learn:
While brand fundamentals still hold, the well-worn paths to customers are all but erased. AI is now generating—and regenerating—the terrain between discovery and choice. Survival in this world demands a hacker mentality. All aspects of how we think of brands and experience must be optimized to compete in today’s machine-mediated decision system.
We believe in the power of brands. While the speed of AI transformation has been thrilling and frightening, health and wellness brands will always need solid positioning and a strong character to form living connections. Stories still give meaning to mechanisms. Social and creator content still drives influence and keeps brands present in culture.
But when it comes to discovery and active decision-making, AI is the new intermediary.
89% of tracked healthcare keywords triggered AI Overviews in Dec 2025(1)
~80% of consumers rely on zero-click results at least 40% of the time(2)
As a result, customers no longer need to manually search and distill online health and product information; AI does that now, almost instantaneously. It generates—and regenerates—the way brand information is summarized, ranked, interpreted, and served to customers. As a result, engaging and highly visual brand content is increasingly flattened and delivered to customers in a purely verbalized format.
None of this means brands matter less. They matter differently.
GEO (generative engine optimization) is just the beginning of how brands need to rethink visibility and authority in the age of AI. “Generative Everything Optimization” is what comes next if the system is generating the output and strategy has to rethink all aspects of how we infiltrate and feed it. It’s a reset in how we research, position, create, and structure ecosystems, build content, and prove performance—so customers ask the right questions and brand stories land as intended.
Six optimizations that go beyond the engine:
More authentic conversation insights are happening inside the machine.
We cannot solely rely on traditional approaches like market research, social listening, and in-office conversations to understand customer needs. AI-mediated chats offer rich insights through an unfiltered look at how customers ask questions, in contrast to the highly filtered, generative responses from LLMs.
Questions: AI search is more autonomous and intimate. Queries are longer, more candid, and often reveal what people won’t say publicly. If we want the deeper human truths beneath stigma and uncertainty, we need to study what customers are asking AI.
Responses: Just as important is how AI answers. The framing of diseases, categories, and solutions is increasingly machine-shaped. If we want to influence the conversation, we have to understand how the model is responding and ensure the brand is informing the answers.
Positioning isn’t a claim, it’s a conclusion.
With AI, how a brand is framed is based on what the machine believes matters most and the sources it draws from to make these determinations. The sources aren’t the same across all brands—they are highly dependent on specific categories and product verticals. To tap into AI search as a dataset for effective positioning, we have to ask some new questions:
How is AI framing the need, category, and competitive set?
How is AI positioning and ranking brands against these dynamics?
What do the sources tell us about where and how to position a brand?
We don’t set and forget ecosystems, we feed them.
AI draws from nearly the entire public web, with a strong preference for medical publications when answering health questions. What it surfaces isn’t random, it reflects patterns. Understanding where the model pulls from is critical to knowing where brands can win.
For example, if an OTC brand is presented as one option among many, differentiation can’t live only in ads. It has to show up across e-commerce, retail listings, and AI-integrated shopping layers.
Or let’s say a brand has an active creator or enthusiast community, its content needs to be part of that ecosystem, where recency, authority, and repetition are the signals language models (LMs) look for when scraping information.
Consider when a treatment has a real-world use case that isn’t well-represented in published data. If the indication, dosing pattern, or patient type that clinicians actually see every day is under-discussed in the PubMed record, AI will default to the “official” narrative and omit the use case.
Content isn’t king—it’s the entire kingdom.
With machine mediation, AI now scans and distills the total body of brand promotion. This doesn’t make timely, culturally relevant content obsolete,it creates a second audience: systems looking for consistent and repeatable signals. Achieving relevancy now operates on two levels: direct connection with the community and legibility for AI analysis and transmission.
If a brand is meaningfully embedded in a specific community, but that relevance isn’t documented in ways AI can interpret, it may not surface.
If cultural language is nuanced, coded, or community-specific, AI may flatten it into a generic category narrative.
Influence is shifting from mass persuasion to one-to-one mediation.
AI is becoming the always-on intermediary. The external voices surrounding a brand become data LMs use to speak on their behalf; this changes the entire constellation of influence as AI doesn’t just amplify voices, it ingests them, interprets them, and redeploys them into an ongoing conversation.
If KOLs publish clear, differentiated thought leadership, those signals don’t just reach audiences directly, they instead become material that the model can draw from when answering questions.
If creators consistently frame a product in a certain way, that framing can be absorbed into how the category is described in future AI-generated responses.
Performance needs to adapt for constant optimization.
In a zero-click world, broad visibility will matter far less than visibility on the topics that drive your business. In a system that is being redefined and regenerated at such incredible speeds, what’s true about visibility or ranking today may not hold next month.
We need to measure how AI frames and surfaces the brand, not just how many people click, but how the reputation is being shaped.
We need leading indicators that show whether our positioning, ecosystem, and content are influencing the system’s interpretation and lagging indicators that connect that influence to brand and business outcomes.
Performance in this environment is a continuous evaluation of how the system is interpreting us and constant optimization in response.
AI mediation and translation is a structural shift in how people behave and how the system verifies and verbalizes content.
65% of CMOs expect AI to dramatically change their role within two years(4)
94% of life sciences leaders expect agents to be critical for scaling capacity(7)
Generative Everything Optimization is our response. It expands upon GEO as an engine-focused practice into a system-wide doctrine: how we research, position, build, measure, and adapt brands to a terrain that will change again tomorrow.
Klick has hacker roots—permeate the system, test the edges, iterate fast, and rebuild when necessary. We use GEO as the tip of the spear; we work to understand your visibility in AI search while also providing a holistic view of where and how to position and deploy your brand to win across paid, owned, and earned platforms.
We were built for moments like this, so you can be built for this as well.
Klick Health is the world’s largest independent commercialization partner for life sciences and a leading full-service pharma marketing partner, serving as agency of record for leading pharma, biotech, and healthcare brands. Klick’s specialized offerings are rooted in deep medical and scientific understanding, including market insights, award-winning creative, and proprietary AI and data models to craft impactful brand narratives and seamless customer journeys. Backed by nearly 250 medical experts and advanced healthcare analytics, Klick delivers integrated marketing strategy and communications, from new product launch strategy to MLR review with real-world evidence, helping brands thrive in today’s complex healthcare landscape. Learn more at Klick.com.
著者
Jason Kaminsky
SVP, Strategy
Jason Kaminsky is a strategic thinker with 15 years of marketing experience and an unconventional journey from fine artist to designer to brand strategist. Known for his storytelling mindset, he blends creativity with sharp business insight to tackle complex challenges across categories. Jason has led work on major health brands—from oncology to MDD to fertility—and previously shaped campaigns for IKEA North America and Comcast B2B. A Temple University grad and proud Philadelphian, he brings clarity, imagination, and impact to every brief.
Amanda Kleinberg
Senior Vice President, Strategy
Amanda is a seasoned strategist who integrates an earned-first perspective to craft ideas that are worth talking about. With over 15 years of experience in PR, social, and digital agencies—and a lifetime of being “perpetually online”—she brings deep cultural competence and a sharp understanding of how information flows through today’s complex media landscape. She has worked extensively on mental health, women’s health, rare diseases, and issues disproportionately affecting LGBTQ+ and Black communities. At Klick, Amanda applies this expertise to build resilient brands that can survive in the wild, creating work that drives business, grows reputation, compels action, and sparks conversation.
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