Nearly half of more than 500 US and UK marketing leaders surveyed by Typeface plan to deprioritize or stop investing in traditional search engine optimization, according to The Typeface Signal Report: The AI Visibility Gap, which the Palo Alto company published on October 14, 2026. The same respondents, by a margin of 62% to 61%, say brands are already giving up content quality and brand authenticity in pursuit of citations from AI systems.

In Short

Typeface asked more than 500 senior marketers in the US and UK how they are trying to get their brands mentioned by AI chatbots, and almost all of them said they feel ready. Yet most admitted their teams do not work together on it, half are guessing which questions to track, and many are using tricks they themselves consider overhyped. The survey suggests brands may end up sounding alike in AI answers just as more shopping and research starts to run through those answers.

What the survey measured

The report, a 13-page PDF dated October 14, is the latest edition of what Typeface calls its Signal Report series. According to Typeface, the findings are based on "an online survey of 500+ U.S. and U.K. marketing leaders, with titles ranging from director to vice president." Respondents came from organizations "including large enterprises" in construction, education, finance, insurance and real estate, healthcare, hospitality, manufacturing, professional services, retail, and software and technology. Results, the methodology note says, "are reported in aggregate."

That is the full extent of the disclosed method. Neither the report nor the press release gives an exact sample size, the fieldwork dates, the panel provider, the split between American and British respondents, any weighting, or a margin of error. The cover of the report describes the respondents as "marketing leaders at large enterprises," while the methodology section and the press release use the looser phrase "organizations, including large enterprises," which implies that some respondents work at smaller companies. Several findings are reported for subgroups - teams with fully connected content workflows, teams led by brand marketing, teams using automated prompt monitoring, teams building the most machine-only content - without any subgroup sizes. Every figure in this article is Typeface's own survey data and has not been independently verified.

The gap matters because the previous Typeface survey PPC Land covered was more transparent. That study, released in June at Cannes, was based on more than 200 marketing leaders at VP level or above surveyed online in May 2026, and found that 34% needed one to two months to launch a campaign. The new edition doubles the headline sample but drops the fieldwork window.

Typeface also has a commercial interest in the conclusions. The company describes itself as "the Orchestration Engine for the world's leading enterprises," and the report's central recommendation - a "shared foundation" of brand values, approved messages and a source of truth that every team and AI agent works from - closely matches what Typeface sells. In September, PPC Land reported that the company had made available a system that turns brand guidelines into structured rules for AI tools, including inside Claude and ChatGPT, under the names Arc Graph, Arc Fabric and Arc Loop.

Confidence without the operations to match

The opening finding is one of near unanimity. According to Typeface, 90% of marketing leaders say their teams are prepared to influence how AI describes their brand, and 97% expect AI to be one of the top three ways consumers discover them by 2030. Some 64% say AI chatbots will drive more brand discovery than traditional search within three years.

Money is following that belief, at least on paper. The report says 44% plan to increase their investment in answer engine optimization - the practice the industry also calls GEO, aimed at getting a brand named or cited in AI-generated answers - over the next 12 to 24 months. And 49% plan to "deprioritize or stop investing in traditional SEO as AI discovery rises." The report does not separate those who plan to deprioritize SEO from those who plan to stop entirely, which is a significant distinction for agencies and in-house search teams. Nor does it say whether the 44% and 49% groups overlap.

"Marketers are not waiting for proof," the report states. "They are moving money toward a channel they believe will define the next decade of brand discovery."

How sturdy is the 90% readiness figure? Other surveys PPC Land has covered point the other way. Adobe research among more than 500 marketers, published in April, found that 98% lacked a clear, documented AI optimization roadmap and full confidence in their approach. The questions differ - Adobe asked about documented roadmaps and full confidence, Typeface about whether teams feel prepared - but the contrast illustrates how much these readings depend on wording. Typeface itself acknowledges the tension: "confidence and readiness are not the same thing," the report says, before describing strategies "with no clear owner, toolsets that do not connect, and measurement they cannot trust."

Nobody owns the answer

Asked who owns AI visibility, respondents split five ways. According to Typeface, 28% say brand marketing, 22% content marketing, 19% SEO, 17% performance marketing and 14% PR. The figures sum to 100%, which suggests respondents could pick only one function.

The owner appears to shape the method. Where brand marketing leads, 38% of teams collaborate closely toward shared goals, against 30% overall, and those teams are the least likely to work in silos, according to the report. Where SEO leads, teams "lean on point solutions and automated prompt monitoring." Where communications and PR lead, one person or group tends to own the strategy and pass insights to everyone else. The report gives no percentages for the SEO-led or PR-led groups.

Across the whole sample, collaboration is the exception:

  • 30% say their teams collaborate closely with shared tools and shared metrics
  • 21% keep each other informed but mostly do their own thing
  • 19% operate in silos and rarely share what they learn
  • 30% rely on a single person or team to hand out insights to everyone else

The press release combines the middle two groups into a single figure, saying 40% "mostly work on their own or in silos." That arithmetic holds.

The pattern resembles one PPC Land reported earlier this year from the Interactive Advertising Bureau, whose August framework for measuring AI visibility found that only 16% of brands systematically track it, while more than 20 vendors sell tools that often disagree about the same brand.

A lifecycle that mostly runs on handoffs

The report's third chapter turns to how content is produced. According to Typeface, 93% of respondents say it is important that content creation, governance, activation and measurement stay connected as AI adoption grows. Only 39% say their content lifecycle is actually connected, from creation through measurement, in a shared workspace. For "about half," it still runs on manual coordination and handoffs, and for "nearly 1 in 10" it is completely disconnected. The report gives no exact figures for those last two groups.

When asked about the single biggest barrier to scaling AI-powered content, respondents put measurement and optimization first at 27%, followed by brand governance at 19% and integration across platforms at 18%.

The report then compares respondents with fully connected and disconnected lifecycles, and the comparison is harder to read than it looks. Among those with a fully connected lifecycle, 86% expect AI to be a top-three discovery channel by 2030, 53% plan to increase AEO investment and 49% feel "extremely prepared" to shape AI brand perception. Among those with a disconnected lifecycle, the report gives two different measures: 48% believe AI chatbots will outpace search for their brand, and 16% plan to cut AEO investment. The rows do not measure the same things across the two columns, so they do not show a like-for-like gap.

One figure also runs against the report's own narrative. If 97% of all respondents expect AI to be a top-three discovery channel by 2030, then 86% among the fully connected group is lower than the overall average. In other words, the teams Typeface holds up as better organized are less certain of AI's dominance, not more. The report does not comment on this.

Gaming the machine

The most detailed chapter documents what marketers are actually doing to earn mentions. According to Typeface, the most common tactics are:

  • 45% make site changes specifically for answer engines
  • 39% publish more press releases to be referenced in AI answers
  • 36% publish competitor comparison content
  • 34% publish list-style articles that place their product in a recommended set

A further 26% are building internal or hidden pages meant to influence how AI describes them, and 68% say they are creating content experiences for AI "that humans will likely never see." The report does not define what counts as such an experience, and the 68% figure is far larger than the 26% building hidden pages, so the category evidently includes more than concealed content - possibly structured data files, feeds or machine-readable FAQ pages.

The press release finding is worth pausing on. PPC Land reported in May that an Outcomes Rocket survey of 858 marketing and PR professionals found 44.8% of organisations had increased PR spending because of AI-driven search. Typeface's own announcement of this survey arrived as a press release, closing with the line "Press release created in Typeface. Dreamed up by a human."

What stands out is how little faith respondents have in some of these tactics. Among leaders who call publishing more press releases overhyped, 48% say their organization does it anyway, according to Typeface. The same contradiction appears for comparison content (39%), list-style articles (35%) and FAQ sections built for scrapers (31%). "When no one knows what works, everyone hedges by trying everything," the report says. These percentages are shares of the subgroup that considers each tactic overhyped, and the report does not say how large those subgroups are.

Guessing at prompts

Measurement is where the uncertainty is sharpest. AI platforms do not tell brands which prompts customers type, so marketers improvise. According to the report, 52% turn their top search terms into prompts, 50% make their best guess, and 48% ask sales teams what customers ask. To measure results, 39% use automated prompt monitoring at scale, 33% use web traffic from AI engines and 25% rely on manual checks.

Teams using automated prompt monitoring are the most likely to increase AEO investment, at 54% against 44% overall. Typeface reads this as "a sign that better measurement builds real conviction." A different reading is equally available: teams that already intended to spend more on AEO are the ones that bought monitoring tools. The survey design, a single cross-sectional poll, cannot distinguish between the two.

The measurement gap is consistent with earlier data. A survey of 481 marketers attached to Semrush's AI Visibility Index in June found that 45% said they could not properly measure AI answer visibility, and only 9% said they could measure all the relevant metrics. The same Semrush study found that just 36 of more than 1,200 tracked brands appeared in the top 100 most-mentioned list on every AI platform in every month - a reminder that the prompt lists marketers are guessing at produce volatile results.

The authenticity question

The report's title finding is the one with the least hard data behind it, because it is an opinion about other brands. According to Typeface, 62% of marketing leaders say brands are optimizing for AI citations at the expense of content quality, and 61% say the same about brand authenticity. "When every brand runs the same AEO plays with the same tools, those plays stop being an edge and become table stakes," the report argues. "The output converges."

Respondents most deeply involved in machine-facing content are the most willing to say so. Among teams building the most machine-only content, 72% say brands sacrifice quality for citations, against 62% overall. The report does not define how it identified this group.

On risk, 25% cite improved visibility for negative opinions and third-party content as their biggest AEO risk, according to Typeface. Only 42% say they are actively working to keep their brand presence consistent across the third-party content AI systems draw from.

Abhay Parasnis, Typeface's founder and chief executive, framed the problem around personal agents rather than chatbots. "As personal agents begin discovering, evaluating and acting on people's behalf, every enterprise has to ask what those agents will understand about its brand, and whether that experience is grounded in the same context, standards and values it gives its people," he said in the press release. "The answer isn't to optimize harder for machines. It's to give every person and agent a shared brand foundation, so greater AI visibility doesn't come at the cost of what makes the brand distinctive."

The report extends this into a prediction about how websites will work. "The web was built for a world where brands published fixed pages and people navigated them. That era is ending," it states, describing brand surfaces that adapt to "a person who expects a responsive, conversational experience, or an AI agent seeking structured, authorized answers." No survey data supports this section; it is Typeface's forecast.

Where the three documents disagree

Three documents carry the survey: the report, the press release and a pitch email sent to PPC Land on October 14 by the company's PR representatives. The report and the press release agree on every figure checked. The pitch email differs in two places.

First, the email says 49% plan to deprioritize or stop investing "in traditional AEO." Both the report and the press release say traditional SEO, which is the only reading consistent with the rest of the finding. The email appears to contain an error.

Second, the email says 63% say brands are optimizing at the expense of brand authenticity. The report and the press release both give 61%. This article uses the report's figure.

The email also states that 64% say "AI will drive more discovery than traditional search," whereas the report specifies AI chatbots and brand discovery. The difference is one of precision rather than number.

Why this matters for search marketers

For PPC Land readers, the 49% figure is the one with the most direct consequences. If roughly half of enterprise marketing leaders in the US and UK genuinely shift budget away from SEO in the next two years, agencies and freelancers selling organic search services will feel it before anyone else. But the survey does not say how much money moves, from what baseline, or whether "deprioritize" means a cut, a freeze or simply slower growth.

The evidence on organic search decline is real, if uneven. HubSpot, when it released its own AEO product in April, cited a 27% year-over-year drop in organic traffic for its customers. Microsoft, in a February guide to AI search for advertisers, took a more conservative line, saying traditional SEO remains essential while GEO adds requirements such as well-structured, authoritative product information. Much of what AI systems retrieve still comes from pages that rank in conventional search, which complicates any plan to defund one in favour of the other.

The report's tactical list is also a warning about the durability of these methods. Comparison pages, list articles, extra press releases and FAQ sections built for scrapers are the same kind of formula content that search engines have historically demoted once it became widespread. Typeface's own respondents seem to know this - large shares call the tactics overhyped while still using them.

There is a narrower point for performance marketers. Typeface found that 17% of organizations place AI visibility under performance marketing, and only 33% measure it through AI engine traffic. If discovery shifts toward personal agents that act on a user's behalf, the referral click that paid and organic search teams have long relied on to attribute value becomes less certain. The survey does not attempt to quantify that.

And for the industry's measurement debate, the report adds one more data point showing that most teams are improvising. Half pick prompts by guesswork, fewer than four in ten automate monitoring, and the most-cited barrier to scaling is measurement itself. Whatever share of budget moves to AEO over the next two years, a large part of it will be spent against metrics the buyers themselves do not trust.

Timeline

Summary

Who: Typeface, a Palo Alto company that sells AI orchestration software to enterprise marketing teams, surveyed more than 500 marketing leaders in the US and UK with titles from director to vice president. Founder and chief executive Abhay Parasnis is quoted in the release.

What: The Typeface Signal Report: The AI Visibility Gap found that 49% plan to deprioritize or stop investing in traditional SEO, 44% plan to increase AEO investment, 62% say brands trade content quality for AI citations, 68% are creating content for AI that humans will likely never see, only 30% collaborate closely across teams on AI visibility, and only 39% have a fully connected content lifecycle. The method discloses no exact sample size, fieldwork dates or margin of error, and a pitch email gave two figures that differ from the report.

When: The report and press release were published on October 14, 2026. Fieldwork dates were not disclosed.

Where: Respondents worked in the United States and the United Kingdom across industries including finance, healthcare, retail, manufacturing, and software and technology.

Why: As AI chatbots and personal agents increasingly sit between consumers and brands, marketers are shifting effort toward being cited in AI answers. The survey suggests that shift is happening without clear ownership, reliable measurement or confidence in the tactics being used, and that many respondents believe it is making brand content less distinctive.