Marketers recognize AEO’s strategic significance, yet adoption remains limited
Answer engine optimization, or AEO, is not a speculative bet. It’s a rational shift, it meets users where they’re going. Executives know it. A majority of marketing leaders agree that AEO will shape the trajectory of digital strategy over the next three years. Still, only 1 in 5 have taken steps to act on that understanding. The value is clear, but execution is missing.
This isn’t a capability problem on the surface, it’s more of a transition delay. Many companies are watching, waiting for more proof of ROI, or trying to align internal teams around a strategy that feels unfamiliar. Meanwhile, generative AI models like ChatGPT, Bard, and search features on platforms like Bing and Google are already changing how people query and consume information. The content that ranks, or even appears, in those environments is different. AEO isn’t just a feature upgrade to SEO. It’s a complete rewiring of how search ecosystems decide what matters.
From a leadership standpoint, this isn’t something to delay. Most companies are working under the illusion that there’s time. There isn’t, really, at least not if you want to win. Start small, test content formats built to surface in language models, and measure early signals. Waiting for “best practices” to emerge while competitors experiment is the long road to irrelevance.
According to a 2025 survey by Acquia and Researchscape, only 20% of U.S. and U.K. marketers have implemented AEO. That should spark action. If you’re among the 80% holding back, you’re competing in a game with outdated rules.
Budgetary constraints and skill gaps are major obstacles to AEO integration
The truth is, adopting AEO does require resources, time, people, and money. But it doesn’t have to be a full-blown overhaul. The top two barriers marketing teams cite: budget and internal capability. 45% say budget limitations are slowing them down. Another 40% say they lack the expertise to move forward. That combination is predictable but solvable.
AEO isn’t about adding another expensive tool to your stack. It’s about adapting your content to match how AI systems interpret and return information. That means investing in skills, technical copywriting, prompt tuning, parsing model output, analytics tuned for LLM traffic. If you’re running a digital operation and your team can’t yet do these things, that’s your signal to prioritize training or hire selectively.
If money’s the issue, start lean. Run pilot programs. Shift allocation from over-performing paid channels to fund early AEO efforts. You’ll get better insights, and likely see long-term gains at a lower cost per engagement. You don’t need dozens of people doing this, what you need is the right three.
Again, from the 2025 Acquia and Researchscape survey: 45% of surveyed marketers called budget limits their biggest challenge, and 40% cited lack of internal expertise. These are solvable problems. The only real risk is inaction.
Adapt now, or play catch-up later.
Declining traditional search traffic is urging marketers to adapt their strategies
Organic search traffic is falling off. That’s not speculation, it’s what the data shows. In the 2025 survey from Acquia and Researchscape, 62% of marketers said they’ve seen a drop in website clicks and search engine traffic. Of that group, 39% can even quantify the decline. That means site visibility is shrinking, and marketers know it.
The culprit isn’t just algorithm changes. It’s how users consume information today. When someone types a question into an AI-powered search engine, they’re often getting direct answers without needing to visit your site. That disrupts traditional SEO. Clicks that used to drive conversions are getting intercepted or never happening at all. That should fundamentally change how you’re thinking about content distribution.
For leadership teams, this shift demands a new set of metrics. If you’re tracking top-of-funnel performance the same way you did five years ago, you’re probably reporting fiction. A better path is to evaluate your content based on how it appears in AI-generated answers, voice responses, and knowledge panels. These aren’t fringe use cases, they’re quickly becoming default search behavior.
Beyond visibility, you’re also dealing with trust positioning. If your product or brand isn’t referenced in the answer layer of search ecosystems, by Google, by ChatGPT, by any AI tool, you’re not losing market share. You’re being erased from the conversation. Fixing it requires rethinking how your content is structured and how it interacts with models trained to give answers, not links.
Now is the time to experiment aggressively. Standard search tactics won’t deliver future growth. Shift resources toward content that feeds answer engines, and measure accordingly.
Uncertainty regarding AI-driven traffic sources hampers effective strategy formulation
A large part of the marketing ecosystem is flying blind when it comes to AI-driven traffic. According to the same 2025 survey, half of small businesses (fewer than 100 employees) and large enterprises (10,000+ employees) say they don’t know how much of their website traffic is driven by large language models (LLMs).
That’s a massive visibility problem. If you can’t trace the path to your users, you can’t optimize it. And if you’re not sure whether search traffic came from a human using Chrome or an AI scraping your site for summary content, you’re not truly controlling the levers of your own demand pipeline.
This isn’t about installing one more analytics plugin. It’s about pushing your tech stack and data strategy to account for how AI alters referral patterns. Many signals that used to be useful, page previews, referral tags, bounce rates, get obscured or broken when AI is the intermediary. You need new frameworks for attribution. Start there.
For enterprise teams, especially, that includes close coordination between product, marketing, and engineering. If those teams are still siloed, real-time learning about traffic composition and LLM-triggered engagement is impossible. You’ll respond late, or not at all, to shifts in demand.
At the executive level, the path is clear. Invest in tooling that’s purpose-built to track AI interactions, audit digital touchpoints for LLM-compliant structure, and align your KPIs to behaviors that reflect the way people now search and engage.
You can’t forecast growth if you don’t know where it’s coming from, or worse, who’s actually seeing your brand.
Personalization remains a critical pillar for future content strategies amid evolving search landscapes
If you’re building content that doesn’t adapt to the user, you’re building content for the past. The data confirms this direction: 51% of marketers, according to the 2025 Acquia and Researchscape survey, rank personalization as the single most important element for their future content strategy. That insight is not optional. Users expect relevance, and algorithms prioritize it. You either deliver or get ignored.
Personalization today goes beyond tagging someone’s name in an email. The focus now is on intent, understanding what the person wants based on their actions, context, and preferences, not just identifiers. Generative AI is accelerating this shift. Models surface information based on how well it aligns with a user’s expressed need. If your content isn’t structured to reflect specific user intents across audiences, it may never reach the screen, voice prompt, or chatbot where discovery happens.
From a leadership standpoint, personalization isn’t solved by one tool. It takes coordination between your data infrastructure, content design, and digital distribution systems. If your data isn’t structured to feed adaptive logic, what content shows to whom, when, and in what format, you’re underleveraging everything you create. Structured content, API-ready blocks, modular copy, these are not technical overreaches, they’re foundational.
It’s important to also recognize that personalization is becoming a trust currency. When users see content tailored to their needs, they’re more likely to engage, convert, and return. That isn’t just good marketing, it’s an efficiency gain across the funnel.
For executives, the agenda is: make personalization your default. Align your teams around data-driven customization. Measure performance at the segment level, and build processes where content is ready to flex for each use case, mobile, email, AI-generated summaries, whatever’s next. Consistency is fine. Relevance is better.
Key highlights
- AEO awareness is high, but action is lagging: Most marketers see AEO as strategically important, yet only 20% have initiated efforts. Leaders should act now to avoid falling behind as AI-driven search gains ground.
- Budget and skills remain bottlenecks: 45% cite budget limits and 40% cite internal expertise gaps. Executives should reallocate resources and invest in upskilling to enable lean, early-stage AEO execution.
- Search traffic is declining fast: 62% of marketers report drops in search traffic, with 39% able to quantify the decline. Leaders must adapt strategy now to counter shrinking visibility in traditional search.
- AI-driven traffic remains a blind spot: Half of small and large businesses don’t know how much traffic comes from language models, impacting strategic clarity. Decision-makers should improve tracking and attribution systems to close this visibility gap.
- Personalization is now a growth lever: 51% of marketers see personalization as a top priority in future content strategy. Businesses should build systems that scale tailored experiences across discoveries, channels, and AI interactions.
