What AI Search Actually Changes (And What It Doesn't)

Everyone in digital marketing is talking about AEO (Answer Engine Optimization, or GEO if you prefer). The terminology is still settling, which is fine; the underlying shift is real regardless of what we call it.

At Big Human, we design, build, and market digital products for brands across consumer tech, travel, health, and more. SEO and AEO are part of the work we do for clients every day, which means we have a front-row seat to how the search landscape is shifting and what's actually moving the needle. Right now, that landscape is changing in ways that have real consequences for any brand that cares about being found.

Here's our current thinking on what's actually different, what's overblown, and what to do about it.

AEO Isn't Replacing SEO. It's Bigger Than That.

The dominant assumption — that AI search would cannibalize traditional search — turns out to be wrong. Statistically, people are not replacing Google with ChatGPT. They're using both. They're using more tools, spending more time researching, and moving through more touchpoints before they reach a brand's website.

What's changed is the order. AI tools are increasingly the first point of contact. A potential customer might start with ChatGPT, get a general sense of the landscape, and then head to Google or go directly to a brand's site. The first impression is happening somewhere new. This is actually an opportunity, not a threat, if you're paying attention to it.

It also makes attribution messier. A visitor who lands on your site through direct or organic search may have first encountered your brand through an AI response. That handoff is largely invisible to standard analytics, which means the value you're already getting from AI search is likely higher than your dashboards suggest. The old clean funnel — impression, click, convert — is getting blurrier, and measurement strategies need to catch up.

SEO has always been a top-of-funnel, single-channel discipline. AEO spans content, PR, social, and technical, and it influences the entire buyer journey, from initial awareness all the way to the final decision. That's a meaningful expansion of what "search" means for a brand's marketing strategy.

LLMs Have Opinions About Your Brand. You Should Care.

Whether you're actively doing AEO or not, AI systems are already forming an impression of your brand. They're aggregating everything publicly available: your website, reviews, press, industry listings, mentions across the web, and synthesizing it into an answer when someone asks about you.

For a long time, owning your story in search meant owning your own website, your own top result. That's no longer sufficient. Now, the story being told about your brand is built from multiple sources, and if you're not managing what's out there across those sources, someone else is effectively doing it for you.

This is especially relevant for B2B brands and companies where reputation is the primary selling mechanism. If a potential customer asks an AI assistant to compare options in your category, you want to know what it says.

The practical implication: treat your off-site presence (third-party review platforms, industry listicles, press mentions, LinkedIn content) with the same intentionality you'd bring to your own website copy.

Your Website Now Has Two Audiences

For most of the web's history, you optimized your site for one audience: humans. Now you're writing for two. LLMs crawl your content and, much like Google, make rapid judgments about quality and relevance, often deciding within the first few paragraphs whether the rest of the page is worth reading.

This isn't as daunting as it sounds. Writing clearly for humans and writing clearly for machines are not that different. The shift is structural: content needs to be easy to parse quickly, with clear hierarchies, explicit answers to implied questions, and metadata that tells the machine what it's looking at.

The brands that will win in AI search are the ones that can communicate their value to both a potential customer and to the model that customer consulted first.

AI Traffic Converts Better

One counterintuitive data point worth highlighting: conversion rates from AI-referred traffic tend to be significantly higher than from traditional organic search. Data backs this up: ChatGPT traffic has been shown to convert 31% higher than non-branded organic search, and Shopify's own 2026 data puts AI-referred conversion rates nearly 50% above standard organic on product pages.

The reason is the nature of the query. Someone searching Google might type "product design agency" and start from scratch. Someone asking an AI assistant is likely asking something much more specific, like "what's the best product design agency for a healthcare startup," and the model is doing the filtering work before the visitor ever reaches your site. By the time someone clicks through from an AI citation, they've already done more research than the average organic visitor. They're further along in the decision process. That's worth orienting your AEO strategy around: fewer, better-qualified visits rather than raw traffic growth.

LLMs Look for Consensus

One of the clearest patterns in how AI search works: LLMs favor consensus. They're not relying on a single authoritative source. They're aggregating signals from across the web to triangulate what's true about a brand, company, or category.

This means the work of showing up in AI search is distributed. Getting mentioned in relevant industry roundups, earning reviews on third-party platforms, publishing content on LinkedIn, being cited in press: all of these create the kind of distributed signal that LLMs use to form an opinion.

Think of it as reputation-building at scale, applied to machine-readable signals.

What to Actually Do Right Now

The good news is that most of what works for AI search is also good content practice. You're not rebuilding from scratch. You're adjusting:

Restructure headings as questions whenever relevant. LLMs respond well to content organized around explicit questions and direct answers. This is also just clearer writing.

Add tables of contents and FAQ sections to key pages. These structural elements help machines parse your content quickly, and they help humans navigate it too. Schema markup on FAQs is especially valuable here. Unlike some SEO signals that have waned in importance, schema is something LLMs actively use.

Refresh content regularly. A significant majority of LLM citations come from content updated within the last ten months. Stale content isn't just a Google problem anymore.

Make sure your site is machine-readable. Clean HTML, proper metadata, schema markup on key pages. Not glamorous work, but it matters.

Publish on LinkedIn with intent. For B2B brands especially, LinkedIn content is increasingly relevant to how AI models understand what a company does and who it serves. Content published there contributes to the broader signal.

Define your AI narrative. Before any of the tactical work, it's worth spending a few minutes asking an AI system what it currently says about your brand. Then decide what you want it to say, and work backward from there. It's often the most clarifying exercise of all, and it's one we walk through with clients as part of brand and launch strategy.

Expand Your Brand’s Presence Through AEO

The playbook here is still being refined: the field is moving fast, and anyone who tells you they have it fully mapped out is oversimplifying. What's clear is that the foundational principles are solid, and the brands acting on them now will be ahead of those waiting for certainty before they move.

We apply this thinking to the products and brands we build at Big Human, across launch strategy, content, and technical execution. If you want to work through what it means for your brand, we'd love to talk.