This article was written by Brandon Murphy for WARC. Read the full article here.

The rise of AI curation is transforming brand marketing from optimizing for platform algorithms to earning recommendations from AI systems that represent consumer preferences.

Marketers must shift their strategies from targeting users to training AI models, treating their brand as a system that provides meaningful data through every interaction, which will influence AI's understanding and recommendations.

Success in the AI era requires brands to prioritize semantic clarity and emotional resonance, ensuring that their messaging is structured and legible to machines, while also creating memorable content that builds trust.

The future of marketing will depend on brands that can effectively communicate their truth and relevance to both consumers and AI systems, moving away from traditional metrics of visibility to a focus on how well they are understood and recommended by AI.

Why it matters

The rise of AI curation represents a seismic change for brand marketers, shifting the focus from optimizing for platform algorithms to earning recommendation from machines that represent people. The goal is moving from simply reaching users to actively training models. Marketers must ensure their brand systems are coherent, consistent, and credible, as AI agents filter, summarize, and decide which brands succeed. In this new environment, success requires being selected, not just seen. Marketers must act as meaning builders, creating ideas that stick and whose truth holds up in memory, meaning, and machine logic alike.

Takeaways

The fundamental goal of marketing has shifted from optimizing for platform algorithms to earning recommendation from machines that represent people. Success in this AI era depends on being selected, not just seen, as AI agents filter, summarize, and decide which brands successfully make it through the customer journey.

Marketers should pivot their strategy from targeting users to training models, viewing the brand as a system where every impression and conversation feeds the AI with meaningful data. Since machines interpret meaning and seek coherence, brands must signal authority by consistently behaving with intention and
speaking in a clear voice.

The focus must be on designing for interpretation, not interruption, which requires brands to craft systemsthat are legible to machines using structured data and credible expertise. This tactical shift means prioritizing semantic clarity (model-ready knowledge) and optimizing for memory, which creates the
emotional imprints that AI agents use as a shorthand for trust (AIO).

For the last decade, marketing has been built to please the algorithm. Every post, pixel, and placement tuned to reach the right person at the right time. The industry learned how to speak fluent platform; optimizing for feeds, formats, and fleeting attention.

But a new interpreter has entered the chat. AI isn’t just shaping what we see anymore; it’s shaping what we trust.

We’re moving from a world optimized for algorithms to one curated by agents.

The algorithm era: Distribution over depth

The algorithm era was about reach. Marketers mastered the mechanics of targeting, bidding, and retargeting.

Success meant hacking the feed, getting your message in front of as many likely buyers as cheaply as possible. Think of the early Facebook playbook or DTC brands that grew entirely off Meta’s lookalike targeting and Google’s performance loops. Those systems were powerful, but brittle. When Apple’s privacy updates hit, or when CPMs rose, the growth engine cracked.

Because algorithms reward what performs in the moment, not what persists over time. They optimize for clicks,
not conviction. For visibility, not value.

That’s why so many brands today are well-known but weakly remembered. Marketing became a race for relevance without staying power; engineered to stop the scroll, not shape memory.

The AI era: Recommendation overreach

Now, the ground is shifting. We’re entering a world where people won’t just scroll, they’ll ask. Ask an AI browser to plan their trip. Ask a shopping assistant to find the best value. Ask a personal agent to recommend what’s worth their time.

Already, Perplexity is reshaping search by curating answers instead of links. ChatGPT’s browsing mode turns brands into summarized knowledge. Amazon’s Rufus answers product questions directly in the shopping app. And soon, Apple’s and Google’s built-in assistants will mediate most of what consumers discover and buy.

These systems don’t just deliver content; they filter, summarize, and decide which brands make it through. The job of marketing used to be reaching people through platforms. Now it’s earning recommendation from machines that represent people. That’s a seismic change. Because agents don’t reward who shouts the loudest; they surface who speaks the clearest, the most consistently, and the most credibly.

From targeting to training

The center of gravity is moving from targeting users to training models.

Every brand impression, every article, every customer conversation becomes part of the dataset that teaches AI who you are and what you stand for. In that sense, your brand is no longer just a story you tell, it’s a system you train.

We’re already seeing this play out. Duolingo integrated directly into ChatGPT to let users practice languagesconversationally. Not just as an ad channel, but as a brand behavior that feeds the model with meaningful data. OpenTable and Instacart have APIs that plug straight into AI assistants; their brand relevance is built into the system itself. Spotify’s AI DJ now decides what people hear next, blending taste, tone, and trust. It doesn’t optimize for plays; it trains loyalty through voice and familiarity.

If algorithms were about signals, AI is about semantics.

Machines don’t just count engagement; they interpret meaning. They look for coherence: does this brand behave with intention, does it speak in a consistent voice, does it know what it’s talking about? In that future, distinctiveness becomes data. Clarity becomes discoverability. And memory becomes metadata.

Strategy in a curated world

This shift changes the strategy playbook in four big ways:

Ground in truth.

AI can synthesize patterns, but it can’t sense emotion. The brands that will thrive are those that start from real human truths: what people feel, fear, want, and value. And then scale that insight through technology. Synthetic intelligence only works when it’s built on something real.

Design for interpretation, not interruption.

In the age of AI browsers, success isn’t about being seen; it’s about being selected. That means crafting brand systems that are legible to machines (structured data, consistent language, credible expertise) so your story can be found and retold accurately.

Optimize for memory, not metrics.

As attention fragments, memory compounds. The most powerful marketing still creates emotional imprint and cultural familiarity: the cues AI agents will use as shorthand for trust.

Measure what holds.

Instead of testing for clicks or completion rates, test for stickiness: the emotional grip and recall strength of an idea. If it doesn’t stick in someone’s head, it won’t stick in an AI’s logic either.

Creative and media rewired

The tactical fallout is already here.

Search becomes conversation. SEO turns into AIO: AI Optimization. Brands will need to publish with semantic clarity, so models understand not just what they sell, but what they stand for. Media becomes mediation. The goal isn’t just buying impressions; it’s engineering relevance. Ensuring your brand is present in the decision pathways of both humans and machines.

Content becomes context. Quantity no longer wins. Consistency does. A thousand pieces of filler won’t outperform one coherent body of meaning. The future belongs to brands that build modular, interconnected storytelling systems that signal authority over time.

Creative testing becomes simulation. Instead of waiting for market feedback, we can now run creative ideas through synthetic audiences (digital twins that mimic how real people think and feel) to see what resonates before we launch. That’s insight at the speed of imagination.

Getting ready for the agent-led world

The shift to AI curation is upon us. Here are the first moves every brand should make:

Clean up your digital truth.

Agents repeat whatever they find. Fix inconsistent claims, outdated pages, confusing product info, and scattered tone. Label content clearly. Structure product and pricing data. Design for understanding, not interruption.

Publish content that teaches, not sells.

Agents favor clarity over authority. Create structured explainers, FAQs, comparisons, and how-tos that show you know the category. Think “model-ready knowledge,” not “marketing copy.”

Map the ecosystems that matter.

Different agents pull from different sources. Identify where your category’s questions are being answered (e.g. Reviews, APIs, Reddit, videos on YouTube) and optimize for those inputs.

Build integration points, not just campaigns.

This can be a lightning rod, but where possible, give agents direct access to your info: inventory, availability, booking, recommendations. Successful compatibility becomes distribution.

Create ideas that stick when compressed.

AI summarizes everything. Distinctive cues, emotional clarity, and consistent voice are what survive thatcompression. Sticky ideas become machine metadata.

The new reach equation

Reach used to mean how many people saw it. Now it means how many systems recommend it. In a world curated by AI, your competitive advantage won’t come from gaming the feed, it’ll come from teaching the machines why your brand matters.

That requires marketers to act less like media buyers and more like meaning builders. We used to market through algorithms. Soon, we’ll market with them; co-creating relevance instead of renting it.

So, what now?

The next great marketing challenge isn’t visibility; it’s viability inside an AI-mediated world.

Because when machines are curating for us, brands don’t just need attention. They need understanding. The future of marketing won’t belong to the brands that shout the loudest. It’ll belong to the ones whose truth holds up, in memory, in meaning, and in machine logic alike.

From algorithms to agents.

Brandon Murphy, Chief Strategy Officer