Google’s Search VP to CMOs: Good SEO Is Good GEO

Good SEO is good GEO — that is the message Google’s VP of Search and Commerce for Global Ads Solutions, Brendon Kraham, delivered to CMOs in a June 2026 Think with Google piece. His argument is structural, not rhetorical: AI Mode and AI Overviews are built on the same core ranking and quality systems that have always powered organic Search, so there is no separate “generative engine” channel for marketing leaders to fund.

For a CMO staring at a line item labeled “GEO” or “AEO,” that statement is a budget decision waiting to happen. If Google is right, several emerging spend categories — llms.txt implementation services, AI-bot-specific content rewrites, a standalone GEO retainer — are at risk of being money spent against a channel that does not exist. If Google is incomplete, skipping them could quietly cost visibility on the platforms Google does not control. Most coverage of Kraham’s piece either cheered (“SEO lives!”) or jeered (“Google is self-serving”). Neither helps you allocate a budget.

This analysis does something different. It takes the executive statement as the anchor, lays it next to the independent data from Ahrefs and BrightEdge, presents the strongest published critique fairly, and renders the whole thing as a line-by-line budget audit a marketing leader can act on. Every figure below is sourced and dated; where a number is vendor-stated or study-period-specific, we say so.

The piece is official Google guidance aimed squarely at marketing leaders, not an offhand conference remark. Brendon Kraham — whose full title is VP of Search and Commerce for Global Ads Solutions at Google, not simply “VP of Search” — published it on Think with Google in June 2026. The framing is reassurance: the AI search era does not demand a new optimization discipline, it rewards the one you already practice.

Kraham’s central message is that your existing SEO foundation is the asset that earns AI visibility, and that the durable strategy is relentless helpfulness rather than channel-specific tricks. He framed it directly for CMOs deciding where to put 2026 budget.

This is not a new Google line. In September 2025, Search director Danny Sullivan made essentially the same point with characteristic bluntness, listing every acronym the industry had coined and folding them all back into SEO. That continuity matters: it tells a CMO this is a stable, repeated position to plan around, not a single executive’s passing comment that could reverse next quarter. For the contrast with where the broader debate sits, our contrarian take on GEO over-investment argues much of the standalone GEO advice circulating in 2026 was never grounded in how the systems actually work — and Kraham’s statement is the closest thing yet to Google saying so on the record.

The statement rests on documented architecture, not marketing spin. Google’s AI Optimization Guide, published in Search Central on May 15, 2026, states that its generative AI features on Google Search are rooted in its core Search ranking and quality systems. The same guide draws the conclusion explicitly: optimizing for generative AI search is optimizing for the search experience, and thus still SEO. Google does not recognize GEO or AEO as separate disciplines.

The mechanism that makes this work is query fan-out. When AI Mode handles a complex question, it spawns multiple concurrent sub-queries through the same ranking signals used in traditional search, then synthesizes the results — Google describes this as a way to surface a wider and more diverse set of helpful links rather than a single blue-link list. For the most involved “Deep Search” queries, Google’s VP of Product for Search Robby Stein has said the system can issue dozens or even hundreds of background queries. Critically, those sub-queries draw on the same index and ranking machinery — there is no separate “AI ranking” you can optimize for in isolation.

The reason this guidance carries weight is the scale behind it. Announced at Google I/O 2026, AI Overviews now reach more than 2.5 billion monthly users globally, and AI Mode passed 1 billion monthly active users roughly a year after its I/O 2025 launch — with AI Mode queries reportedly more than doubling every quarter. Treat all three of those as vendor-stated I/O announcement figures rather than independently audited metrics; they describe momentum Google wants to emphasize, and they have not been third-party verified.

What is verifiable from primary financial filings is that the growth is translating into advertiser revenue. In Q1 2026, Google Search & other advertising revenue grew 19% year over year to $60.4 billion, and CEO Sundar Pichai stated on the earnings call that search queries hit an all-time high. That combination — more queries, more revenue — is the commercial backdrop for why Google is messaging AI search so positively: the “it’s still SEO” narrative keeps marketers investing in a channel that is performing.

Google’s claim is testable, and two independent datasets bear on it — pointing in partly opposite directions. The first supports the same-systems logic. BrightEdge’s 16-month study, covering May 2024 to September 2025, found that the overlap between AI Overview citations and organic rankings climbed from 32.3% to 54.5% — roughly a 69% relative increase over the period. Put plainly: ranking organically increasingly predicts getting cited in AI Overviews, which is exactly what you would expect if both run on one system. The important hedge is the window — that study predates AI Mode’s full rollout and broader international availability, so read it as a study-period finding, not a current-2026 measurement.

But the same data carries a warning against complacency: BrightEdge found only about 16.7% of AI Overview citations came from pages ranking in the organic top 10, with most citations drawn from pages ranking 21 to 100. Ranking #1 does not guarantee an AI citation. And the overlap varies enormously by industry — far higher in Healthcare (75.3%), Education (72.6%), and Insurance (68.6%) than in E-commerce (22.9%). Your vertical changes how much your organic rank actually predicts AI visibility.

The second dataset complicates the tidy story. An Ahrefs analysis of 540,000 query pairs from December 2025 found that AI Mode and AI Overviews reached semantically similar conclusions about 86% of the time — yet cited the same URLs only 13.7% of the time. Same underlying infrastructure, very different citation outputs. That is the paradox at the heart of Kraham’s message: “same systems” is architecturally true and practically insufficient. A unified content strategy can earn you a place in both surfaces, but it will not earn you the same citations in both. (As with BrightEdge, this is a single snapshot — a pre-2026 one — and AI Mode was changing fast through early 2026, so the exact percentages may have moved.)

The same Ahrefs study found the two surfaces behave differently in ways that matter for brand visibility: AI Mode cited sources more consistently (a 97% citation rate versus 89% for AI Overviews) and mentioned more entities per response (about 3.3 versus 1.3), while a striking 59.41% of AI Overviews contained no brands or entities at all. For a CMO, the takeaway is operational: AI Mode is the surface where brand and entity prominence has more room to show up, and the two need to be tracked separately even when the content behind them is one strategy. The table below turns that into a reference for which content traits each surface tends to reward.

One practical change makes all of this measurable for the first time. Google Search Console launched new generative-AI performance reports on June 3, 2026, giving site owners separate impression data for AI Overviews and AI Mode. At launch there is impression data only — no click or CTR breakdown — but it is the first time a CMO can verify Kraham’s claim against their own property rather than taking it on faith. For the broader traffic-impact context this lands in, our read on how AI Overviews now trigger for over 13% of queries frames why these impressions are worth instrumenting before you redesign any strategy around them.

The strongest published pushback came from Mike King, CEO of iPullRank, in a formal critique on May 18, 2026. His argument is not that Google’s “same ranking systems” architecture is false — he largely accepts it for Google Search. His charge is that the framing is strategically incomplete and self-serving: by telling marketers “it’s still just SEO,” Google discourages budget for genuinely new multi-platform optimization skills, and keeps the SEO industry focused on cleaning up technical debt that benefits Google’s platform over the open web.

King’s technical counter is worth weighing. Retrieval-augmented generation systems chunk content into passages regardless of Google’s guidance, and vector math favors focused, single-topic passages over multi-topic pages when retrieving — which, he argues, cuts against Google’s implication that passage-level structuring is unnecessary. The honest read is that both can be right at once: Kraham’s logic holds for Google Search specifically, where the BrightEdge overlap data supports it; King is right that a CMO optimizing for ChatGPT, Perplexity, and Claude cannot simply assume Google’s advice transfers.

Here is the part no recap gives you: a line-by-line translation of Kraham’s statement into a budget decision. Each row is a common GEO or AEO spend category. The columns separate what Google says from what the independent data implies, then split the risk of cutting it into two worlds — Google Search alone versus multi-platform AI — and land on a verdict. The split between those last two columns is the whole point: a line item can be safe to cut for Google and risky to cut for ChatGPT and Perplexity at the same time.

Kraham was specific about what not to do. His guidance for CMOs warns against five things: inventing specialty AI terminology and separate GEO optimization, producing bot-optimized or keyword-stuffed content, manufacturing third-party mentions, creating llms.txt files, and publishing generic content that lacks a brand-unique perspective. Read together, those are not five random prohibitions — they are a single instruction to stop gaming a channel that does not exist and start being genuinely useful.

The positive corollary is what survives the cut: authentic expertise, distinctive brand perspective, and the foundational SEO that makes both discoverable. Kraham’s framing is that in a world of infinite generated content, authenticity and real expertise are the durable competitive advantage. For the practical mechanics of how that expertise actually earns AI citations — the entity coverage, the answer structure, the authority signals — our guide to what actually earns AI citations and our breakdown of how AI Mode surfaces information and refers traffic are the companion playbooks to this strategy read.

The right move depends on where your audience actually searches. Sort your situation into the buckets below before you sign off on a 2026 GEO budget — the answer is rarely “all in” or “all out.”

For most teams the sequence is the same: instrument the new Search Console AI reports first so you are deciding on your own data, then audit every GEO line item against the matrix above, cut the ones that optimize for a channel Google says does not exist, and redirect that budget into expertise content and per-surface tracking. Running that audit — and standing up the cross-platform measurement that the 13.7% overlap demands — is exactly the kind of work our agentic SEO engagements are built around, so no single platform’s guidance becomes the only lens on your visibility.