The real shift: from “rank on Google” to “be the answer everywhere”
Look at those headlines and a pattern jumps out:
- ChatGPT has 12% of Google’s search volume.
- Google is debating if you even need a website.
- Cloudflare is shipping AI features that rewrite content on the fly.
- People are publishing “AI engine optimization” audits alongside classic SEO audits.
We’re not in a “search vs social” world anymore. We’re in an AI-first discovery world.
Users ask assistants, agents, and feeds for answers. Those systems decide whether your brand is even mentioned. Your analytics are increasingly blind (anonymized queries, dark social, AI answers). And you’re still being asked to hit a CAC target.
This isn’t a thought experiment. It’s a commercial problem: how do you keep winning demand when intermediaries – not users – are your new primary audience?
The uncomfortable truth: your “site” is now a data source, not a destination
Google’s own search team is openly asking if brands “still need a website.” Airbnb is bragging that its own AI search converts better than Google. Cloudflare is inserting AI into the delivery layer. ChatGPT is already siphoning 12% of search volume.
In practice, this means:
- More answers happen off your properties (AI chats, SERP summaries, social feeds, marketplace search).
- When people do click, it’s often later in the journey, closer to decision, with less patience.
- Your content is being read by machines first, humans second.
So the job is no longer “get traffic to the site at the lowest CPC.” It’s:
- Be consistently chosen as the answer by AI systems and platforms.
- Convert harder when you do get a click.
- Measure reality even when attribution windows and query data are collapsing.
From SEO to AEO: optimizing for AI engines, not just search engines
Classic SEO is being rebuilt in front of us:
- Entity-based SEO is replacing keyword stuffing.
- E-E-A-T audits now run to 220+ markers.
- AI engine optimization audits are becoming a thing.
- Almost half of Google Search Console queries are anonymized.
AI systems don’t “see” your brand the way humans do. They see:
- Entities and relationships (brand ↔ category ↔ problems ↔ solutions).
- Consistency of claims across the web.
- Signals of trust, recency, and usefulness.
What to actually change in your search strategy
Here’s how to move from SEO theatre to AI-first discoverability.
1. Build a clean entity graph around your brand
Stop thinking “keywords,” start thinking “concepts and connections.” Operators can do this without boiling the ocean:
- Define your core entities: brand, flagship products, core problems you solve, primary audiences, key industries.
- Standardize naming across site, social, PR, and marketplaces. AI models hate ambiguity.
- Use structured data (schema.org) ruthlessly:
- Organization, Product, FAQ, HowTo, Review, Article schemas.
- Make sure your sameAs links (LinkedIn, Crunchbase, Wikipedia, GitHub, etc.) are correct and consistent.
- Publish “canonical explanations” for the problems you own:
- 1-3 definitive guides per core problem.
- Clear definitions, examples, and comparisons that AI systems can quote.
2. Treat E-E-A-T as a media buying problem, not a checklist
That 220+ point E-E-A-T audit is basically a scoring model for “would I trust this source?” AI systems approximate the same thing.
Instead of obsessing over every micro-signal, treat E-E-A-T like you would a channel mix:
- Experience: Put real operators, customers, and practitioners on the record.
- Video walkthroughs.
- Signed case studies with named companies.
- First-person “here’s how we did X” content.
- Expertise: Concentrate authority.
- Fewer authors, deeper bios, clear credentials.
- Recurring bylines for the same experts across site, LinkedIn, and industry pubs.
- Authority: Borrow trust where it already exists.
- Guest posts and quotes in established media.
- Co-branded research with known players.
- Speaking slots and webinars that live on third-party domains.
- Trust: Remove doubt signals.
- Clear ownership, contact info, pricing logic, and policies.
- Visible security/compliance details where relevant.
Budget this like a channel: a fixed monthly “authority spend” across PR, research, and content that builds compounding trust signals for both humans and machines.
3. Optimize for “no-click” outcomes on purpose
In an AI-first world, a “no-click” answer can still be a win if:
- Your brand is mentioned as the example or recommended solution.
- Your proprietary term becomes the generic answer (“Kleenex effect”).
- Your framework is what AI tools repeat back to users.
Tactically:
- Name your frameworks and use that name everywhere. AI systems latch onto repeatable patterns.
- Publish short, direct Q&A content that matches how people prompt AI (“How do I…”, “What’s the best way to…”).
- Seed your terminology consistently in:
- Help docs.
- Sales decks.
- Public talks and transcripts.
- Guest content.
Your “brand search share” in AI tools will matter more than your blue-link rank.
Your owned properties still matter – but for different reasons
There’s a hot take floating around that you “might not need a website.” That’s wrong for anyone spending real money on media.
You absolutely need owned properties. You just need them to behave like:
- Conversion engines for high-intent visitors.
- Canonical sources for AI systems and aggregators.
- Data collection points for measurement and modeling.
1. Treat landing pages as performance infrastructure, not brochures
We’re seeing:
- Local landing page frameworks.
- Case studies of 37% lifts in inquiries from conversion-focused redesigns.
- Title tag rewrites at 8,000-page scale.
That’s not vanity work. It’s survival. If AI and platforms filter who arrives, you can’t afford to waste a single click.
For performance teams, that means:
- Segment landing pages by intent, not just campaign:
- Problem-aware vs solution-aware vs brand-aware pages.
- Different proof and CTAs for each.
- Local and vertical variants where they actually change the message (not just city tokens).
- Systematic testing of:
- Offer framing (trial vs demo vs calculator).
- Social proof placement.
- Form friction vs lead quality.
2. Fix the “73% of your emails are broken” problem
Email is one of the last channels where you still own the relationship. And yet most ecommerce and B2B flows are quietly broken:
- Misfiring triggers.
- Dead segments.
- Outdated logic from a previous offer or ICP.
In an AI-dominated discovery world, your email list is your hedge. Treat it like a critical system:
- Quarterly email systems audit:
- Check every trigger, branch, and dynamic field.
- Kill flows that don’t drive revenue or engagement.
- Shift from “broadcasts” to community-style programs:
- Named series with a clear promise.
- Predictable cadence and recognizable voice.
- Use AI for QA and diagnostics, not voice replacement:
- Have AI agents crawl flows looking for broken logic.
- Use them to generate test cases, not final copy.
Media buying in the age of AI intermediaries
So how should CMOs and performance leads actually adjust spend and operating models?
1. Redraw your channel map
Stop thinking “search / social / display / email.” Think in layers:
- Discovery layer: Google, TikTok, Meta, YouTube, marketplaces, AI assistants, newsletters, influencers.
- Decision layer: Your site, landing pages, sales calls, trials, retail environments.
- Memory layer: Email, communities, remarketing, owned content, product experiences.
Then ask, for each major product or segment:
- Where does discovery actually start now (not two years ago)?
- Which intermediaries control that discovery?
- What signals do those intermediaries use to decide who to show?
Allocate budget to influence those signals, not just impressions.
2. Shorten attribution windows and widen credit
With anonymized queries, AI answers, and tighter privacy, the classic 7/28-day click windows are fantasy. Practical moves:
- Standardize on shorter windows for platform optimization (1-7 days) to keep bidding responsive.
- Use modeled attribution at the portfolio level:
- Media mix modeling for larger budgets.
- Simpler “anchor tests” for smaller teams (geo splits, on/off tests by channel).
- Track “assist channels” explicitly:
- Newsletter mentions.
- Podcast reads.
- Influencer content.
The goal is not perfect attribution. It’s a defensible model that lets you move budget with confidence.
3. Use AI as an operator, not as a copy machine
Everyone is “rethinking prompting.” Most are still using AI as a faster intern. That’s fine, but the real value is operational:
- Creative ops:
- AI to generate structured briefs and variations from your best-performing ads.
- AI to cluster creatives by concept and performance for faster iteration.
- Search ops:
- AI to detect cannibalization and redundant pages.
- AI to propose title/description rewrites at scale, with humans approving.
- CRM ops:
- AI to simulate user journeys and spot dead ends in flows.
- AI to flag segments with declining engagement before they churn.
Guardrails:
- AI drafts, humans own message and positioning.
- No “set and forget” AI agents touching live campaigns without human review.
What to do in the next 90 days
If you’re running a marketing or growth team, here’s a concrete 90-day plan that won’t blow up your roadmap.
- Week 1-2: Discovery audit
- List the top 5 ways new customers actually find you today.
- For each, map the intermediaries (Google, TikTok, ChatGPT, marketplaces, newsletters, etc.).
- Document what those intermediaries reward (speed, recency, engagement, authority, etc.).
- Week 3-4: Entity and E-E-A-T baseline
- Run a quick entity and E-E-A-T audit on your top 20 pages.
- Fix obvious gaps: missing schema, inconsistent naming, thin bios, no case studies.
- Choose 1-2 problems you want to “own” and draft canonical guides.
- Week 5-8: Conversion infrastructure
- Pick your top 3 paid campaigns and rebuild or tighten the matching landing pages.
- Run a basic email systems audit and kill or fix broken flows.
- Set up a simple testing plan: one meaningful test per month per key funnel.
- Week 9-12: Measurement and AI ops
- Standardize your attribution windows and document your model.
- Choose 2-3 AI use cases in ops (not copywriting) and implement them with clear owners.
- Define a small, recurring “authority budget” for PR, research, and external content.
The AI-first discovery world isn’t coming; it’s here. The brands that win won’t be the ones with the most prompts or the fanciest dashboards. They’ll be the ones that treat AI systems as real distribution partners, tune their owned properties for conversion and trust, and run media like an experiment, not a religion.