Marketing leaders prioritize AI search. Most still cannot measure it.

Short answer: Marketing teams are being asked to grow pipeline while traditional channels decay — and they know AI search matters. AirOps' 2026 Marketing Leaders Reality Index finds 86.6% of leaders prioritize AI search visibility, but roughly 36% rate measurement confidence at 2/5 or below, and only 7.4% describe their AI maturity as advanced or leading. Priority without observability is not a strategy.

This report translates that survey into an AEO lens: what is breaking in the funnel, why SEO/AEO content is one of the few channels still overperforming, and how to start measuring AI visibility without waiting for a perfect attribution model.

Browse live buyer prompts and brand mentions in the free Obsurfable Explorer.

Where the numbers come from

AirOps fielded the 2026 Marketing Leaders Reality Index in July–August 2026 across 300+ marketing leaders in B2B SaaS, B2B services, agencies, and B2C companies (under $10M to $1B+ revenue). Findings are self-reported; sample sizes vary by question.

Obsurfable is not affiliated with the survey. We cite it because it maps cleanly onto the practical problem our readers face: AI search is on the roadmap, but most teams cannot yet see whether they appear in the answers buyers actually get.

1. Targets are climbing faster than budgets

Pipeline or revenue targets increased for 75.4% of teams. Marketing budgets increased for only 43.0%.

Among teams with higher targets:

• 48.7% had budgets that stayed flat or decreased
• 20.4% saw budgets fall outright
• 28.3% stayed flat

That gap forces tradeoffs. You cannot fund every channel at last year's intensity and still open a new one. The survey's channel data shows where the pressure lands:

Paid search and paid social underperform about as often as they deliver. Meanwhile, events, field marketing, and OOH were the strongest overperformers (53.4%). SEO and AEO content was the second-strongest at 33.4% — ahead of every paid channel.

That ranking matters for AI visibility work. Teams that treat AEO as "another content experiment" miss that leaders already report it as one of the few channels punching above its weight under budget constraint.

2. Budget approval is a growth signal — not just a finance ritual

79.7% of respondents asked for more budget or headcount in the prior six months. Outcomes:

Teams with full approval were 2.35× as likely to grow headcount (72.1% vs 30.7%). They were also more likely to call AI adoption operational/advanced/leading (59.3% vs 50.0%) and to name AI search visibility a top priority (59.3% vs 49.4%).

The survey does not prove that budget causes maturity. It does show that resourcing and operating model move together. Partial approval keeps a plan alive; full approval is associated with teams that can fund new programs — including measurement for channels that do not look like last-click SEO.

3. Marketing teams are being rebuilt before they get bigger

"Doing more with less" is not always mass layoffs. It is a shape change:

• 40.3% have not backfilled open roles
• 37.5% report smaller, more senior teams
• 36.7% report fewer entry-level roles
• 47.7% have reduced agency or vendor spend
• 34.3% are increasing contractors or freelancers
• Only 15.5% report expanding the team's AI capacity

Hiring criteria are shifting too. Among teams changing their hiring process: 65.6% changed interviews or take-homes for AI use, 37.8% added AI proficiency requirements, and 42.2% broadened generalist scopes.

Implication for AEO: fewer junior producers and thinner agency benches mean less volume for volume's sake. The teams that win will need clearer evidence of which pages, mentions, and third-party sources actually show up in AI answers — so scarce senior time goes to the right work.

4. The priority–measurement gap on AI search

This is the headline for anyone doing answer engine optimization.

Nearly nine in ten teams say AI search matters. Fewer than one in four feel confident measuring it. Almost nobody rates themselves as leading.

Most AI usage still clusters around content production and workflow — 79.2% expect more than 25% of content to be AI-generated; 38.9% expect more than half. Using a tool is becoming normal. Building a repeatable operating model around AI discovery is not.

That gap is exactly where classical SEO metrics fail. Rankings and organic sessions measure a shrinking slice of discovery when buyers ask ChatGPT, Gemini, Claude, Perplexity, or Grok for a shortlist. If you cannot see whether your brand is named — or which competitor is — you cannot allocate the senior time the org just concentrated into a smaller team.

5. What growing teams do differently

AirOps compared a growth-system cohort of 76 teams that increased budget, headcount, and pipeline/revenue targets with the remaining 231 teams.

Growing teams are not escaping cost pressure — they report higher CAC more often. They are also less likely to report organic decline, more likely to have rewritten KPIs, and more likely to treat AI as an operating capability rather than a side project.

Changed KPIs are the bridge to AEO. If buyers discover via AI answers, last-click organic sessions undercount influence. Teams that update scorecards to include mention rate, citation rate, and multi-engine share of voice are measuring the channel leaders already say is a priority.

For a practical KPI framework, see How to measure AI visibility: KPIs beyond CTR.

What this means for AI visibility work

1. AEO is not a nice-to-have experiment under these constraints.
SEO/AEO content is already one of the few channels leaders report as overperforming while paid CAC rises and organic traffic falls for many teams.

2. Priority without measurement produces theater.
86.6% priority and 7.4% advanced maturity is the definition of a channel that gets slide-deck attention and weak operating discipline. Closing the gap starts with observing real answers — not with another content calendar alone.

3. Multi-engine reality is messier than a single "AI rank."
Obsurfable's own corpus work shows engines often disagree on brand shortlists for the same prompt — 46% of matched ChatGPT/Gemini/Claude prompts share zero brands in the top five. A measurement program that only checks one assistant will systematically misread the market.

4. Scarce senior capacity needs evidence.
Smaller, more senior teams and reduced agency spend raise the cost of guessing. The right next page or PR placement is the one that shows up in the answers buyers already ask.

Start with evidence: Obsurfable Explorer

You do not need a finished attribution stack to begin. You need a clear view of what AI systems currently say about your category.

Obsurfable Explorer is a free, public corpus of AI observations — prompts, answers, brands mentioned, and citations across major engines. Use it to:

1. Find prompts that match how buyers ask in your category (not just how you brand your product).
2. See which brands get named on ChatGPT, Gemini, Claude, Perplexity, and Grok — and where you are absent.
3. Compare engines side by side so you do not optimize for one assistant's quirks.
4. Ground the budget conversation in observable answers when you ask for headcount or program spend to close an AI-search gap.

Open Explorer, pick a category close to yours, and check whether your brand appears in the shortlists leaders already treat as a growth channel.

Methodology note

Survey statistics in this piece are from AirOps' Marketing Leaders Reality Index (fielded July–August 2026; 300+ marketing leaders; self-reported). Obsurfable's multi-engine shortlist findings are from our separate Explorer research corpus, documented in linked reports. We credit AirOps as the survey publisher; this analysis and the Explorer product recommendations are Obsurfable's own.