Conductor, a US-based organic marketing platform, surveyed over 250 digital leaders at US enterprise companies about how they're approaching Answer Engine Optimisation in 2026. The research covers budget allocations, challenges, team structures, and measurement priorities.
The survey was conducted in late 2025. Respondents were decision-makers with budget authority: 48% were C-suite executives and 45% were marketing or digital leaders. Industries represented included Financial Services (20%), Retail/eCommerce (20%), Technology (18%), and others.
We've pulled out the key findings that matter for New Zealand marketing managers watching these trends.
Impact on Marketing Funnels
97% of enterprise leaders reported AEO had a positive impact on their overall marketing funnel in 2025. The split was notable: 44% said "large positive impact" whilst 53% reported "slight positive impact".
When asked about top metrics, "conversions and leads from AI search" ranked highly. The research noted that AI search traffic converts better than traditional organic traffic, with visitors tending to be more qualified and further down the funnel.
Primary Challenges
Creating AI search-optimised content at scale ranked as the top challenge.
Many enterprises initially thought they could scale content production by feeding prompts into ChatGPT and publishing the output. What they discovered quickly is that generic AI-generated content is essentially worthless for building visibility in AI search results.
The difference from traditional SEO content production comes down to what AI systems reward. Traditional SEO content could succeed by hitting keyword targets, building backlinks, and following on-page optimisation best practices.
AI search engines prioritise something different: unique perspectives, original data, and real humans having real conversations about your brand. Content imbued with a company's specific point of view, proprietary data, or genuine expertise performs significantly better than generic keyword-optimised material.
The multi-platform distribution requirement adds another layer of complexity. AI systems favour seeing the same information validated across multiple sources. You need to turn that article into a video, have conversations on Reddit if that fits your brand, repurpose for YouTube or TikTok, and build that cross-web consensus.
The third biggest challenge was monitoring whether LLMs are crawling your content. The research showed "unable to monitor if content is being crawled by LLMs/AI bots" surprised researchers because the technology to do this exists. The finding speaks to an education gap.
The operational practice is log file analysis: examining your server logs to see which AI bots are visiting your site and how often. The key bots to monitor include GPTBot (ChatGPT), PerplexityBot (Perplexity), Google-Extended (Google's AI systems), ClaudeBot (Anthropic's Claude), and CCBot (Common Crawl, used by multiple AI systems). When these bots visit your site, they're retrieving information that may end up in AI-generated answers.
If they're not visiting, or they're only hitting certain pages, you're invisible to those systems.
Budget Allocation and Investment Trends
The average budget allocation to AEO/GEO across enterprise companies is 12% of total marketing spend.
This breaks down by company size:
- Organisations with marketing budgets between $2.5M-$25M allocate around 9%
- Those with $26M-$50M budgets allocate 11%
- Companies spending $51M-$100M allocate 13%
- The largest enterprises ($101M-$250M marketing budgets) dedicate 15%
94% of enterprises plan to increase their AEO/GEO investment in 2026.
The growth trajectory is striking: 94% of enterprises plan to increase their AEO/GEO investment in 2026. The breakdown shows 43% plan to increase significantly whilst 51% plan to increase slightly. Only 4% are holding steady with no change, and just 2% plan to decrease slightly.
Nobody reported planning to decrease significantly.
The resourcing data tells an interesting story. The overwhelming majority (64%) plan to upskill their current SEO and marketing team members rather than hiring externally. Another 29% are hiring new AEO-specific roles. Only 5% are outsourcing to agencies and a mere 2% are bringing in consultants.
This suggests investment is flowing towards internal capability building: platform subscriptions, training, and headcount.
Technology Pain Points
Data quality and trustworthiness of visibility insights ranked as the number one pain point with AEO/GEO technologies.
The presenters were blunt about why: we're in the Wild West phase of this market. There are vendors out there who have essentially "vibe coded" technologies and are selling them despite shaky methodologies. Some companies have already closed because they underestimated how hard it is to do this properly.
The trustworthiness problem is more acute in AEO than traditional SEO because of how fundamentally different the measurement challenge is. With traditional SEO, you had relatively stable signals: Google published ranking positions, Search Console gave you impression and click data, and third-party tools could crawl and index the same pages Google did.
AI search engines don't work that way. They synthesise answers dynamically, they don't publish rankings, and the same query can generate different responses depending on context, timing, and which model version is running.
There's no equivalent of checking your ranking position. You're trying to measure something that's inherently fluid.
The practical implication is that high-fidelity AEO data is expensive to collect, and coverage is necessarily limited right now. Enterprises want to trust their visibility metrics, but many are stuck with tools offering either questionable accuracy or limited depth of monitoring.
Measurement Priorities
AI referral traffic currently sits at around 1% across the board. It's not going to replace the organic traffic you're losing to zero-click searches anytime soon.
The value is in being cited, being mentioned, being the brand that AI recommends when someone asks a question in your space.
Brand sentiment and mentions matter more now because that's what AI systems actually use to decide who to recommend. Traditional SEO cared about links and domain authority. AI systems care about entity association and consensus.
They scan the web looking for how often your brand name appears alongside specific topics in trusted contexts. If your brand is mentioned positively on industry publications, Reddit threads, review sites, and news outlets, the AI builds confidence that you're a legitimate player.
The top metrics enterprises are prioritising for 2026:
- Conversions and leads from AI search
- AI search market share
- AI referral traffic
- Brand sentiment
- Brand mentions
Notice that traffic is third, not first. Teams are now putting brand sentiment (how AI systems characterise your brand when they mention it) and share of voice in AI responses into their board decks alongside traditional performance metrics.
2026 Strategic Priorities
AEO/GEO ranked as the number one marketing priority for 2026, ahead of paid media, paid search, and traditional SEO.
SEO has never been number one. In over 20 years of search marketing, practitioners have always been fighting for budget and executive attention. This research suggests that fight might be over, at least for now.
The C-level visibility that AI search has generated (partly because CEOs are reading about it in business press and testing their own brands in ChatGPT) has elevated the entire discipline in ways that years of SEO advocacy never achieved.
The top strategic priority for 2026 is straightforward: increase AI search visibility. But the second priority is where it gets operationally interesting. Enterprises want to integrate AEO/GEO into their broader content strategy.
Rather than treating AEO as a separate initiative run by a specialist, companies are recognising it needs to sit alongside and influence how content gets created across the organisation.
Pat Reinhart from Conductor predicted we'll see dedicated AEO specialist teams emerge and eventually converge with traditional search teams. His view is that over the next five years, these two disciplines will merge into a unified function.
What This Means for New Zealand
These are US enterprise companies with marketing budgets ranging from $2.5 million to $250 million — a different scale to most NZ organisations. But the underlying dynamics don't change with geography: people prefer getting answers over researching options, they trust conversational AI interfaces, and they're delegating more decision-making to these systems.
Practical starting points from the research include understanding whether your content is being crawled by AI bots (or finding someone who can check for you), auditing your content for structural clarity and factual density, and tracking brand mentions across platforms where AI systems pull data — review sites, industry publications, Reddit, and forums relevant to your sector.
The budget benchmarks offer useful ammunition for internal conversations. US enterprises are allocating 12% of marketing spend to AEO/GEO on average, with 94% planning to increase that investment.
The resourcing approach is predominantly internal: 64% of enterprises plan to upskill existing teams rather than outsourcing, whilst 29% are hiring new AEO-specific roles.
That said, these are US enterprises with substantial budgets and deep talent pools. For many NZ organisations, building dedicated AEO capability in-house isn't realistic. The practical path may be a hybrid: upskill your team on the fundamentals so they understand what's changing, whilst working with an AEO/SEO specialist to handle implementation.
Access the Full Research
The complete State of AEO/GEO report is available at https://www.conductor.com/academy/state-of-aeo-geo-report/
The report includes detailed breakdowns by company size, additional technology insights, and specific methodology information for marketing managers looking to build their own AEO programmes.
Source: Rod Russell, Managing Partner, ADMATIC, 05th February 2026
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