How to Hack Your Existing Marketing Budget to Win in AI Search

Most marketing leaders haven’t carved out a line item labeled “AI SEO.” And yet AI search is already reshaping how brands get found, how buying decisions get made, and where attention flows before a single ad impression is served.

Here’s what we’ve seen working with clients at Xponent21: the brands winning in AI search aren’t the ones with the biggest budgets. They’re the ones who stopped treating AI visibility as a future problem and started reallocating today.

The good news? You probably already have the money and the resources to succeed. You’re just spending them on the wrong things.

Why the Urgency Is Real

The proof is indeed in the pudding.

According to Seer Interactive’s September 2025 study — the most comprehensive analysis of its kind, tracking 25.1 million impressions across 42 organizations over 15 months — organic click-through rates for queries featuring Google AI Overviews have dropped 61% since mid-2024, falling from 1.76% to just 0.61%. Paid CTR on those same queries has fallen even harder, plunging 68%, from 19.7% down to 6.34%.

Ahrefs’ December 2025 study of 300,000 keywords puts the CTR impact at 58% for the top-ranking position — nearly double what they measured just eight months earlier. And critically, Seer’s data shows that even queries without AI Overviews are seeing organic CTR decline 41% year-over-year. This isn’t just an AI Overview problem. It’s a fundamental shift in search behavior.

Zero-click searches have crossed a threshold: Semrush’s 2025 data shows that roughly 60% of U.S. Google searches now end without any click to an external website. For queries that trigger AI Overviews specifically, that rate climbs to 83% according to Similarweb. Users aren’t skimming your results and moving on — they’re getting the answer inside the search interface and never arriving.

Meanwhile, AI platforms themselves are growing at a pace that should be impossible to ignore. AI referral traffic surged 527% year-over-year between January and mid-2025. ChatGPT alone now drives 87.4% of all AI referral traffic and has become the 4th most-visited website globally. Google’s AI Overviews now reach 1.5 billion users monthly across 200+ countries.

The brands appearing inside AI search results are capturing trust and attention before a paid ad even enters the picture. If your budget allocation still looks like it did in 2022, you’re funding a strategy that’s actively losing ground.

The real risk isn’t a lack of budget. It’s budget inertia.

The Exception That Proves the Rule

Before we talk about reallocation, it’s worth sitting with the most important finding in all of this data — because it’s the entire strategic argument.

Brands that are cited inside AI Overviews don’t just survive the CTR decline. They outperform. Seer’s research found that brands cited in AI Overviews earn 35% higher organic CTR and 91% higher paid CTR compared to non-cited brands on the same queries. And Semrush data shows AI-referred visitors convert at 4.4x the rate of standard organic visitors, meaning the traffic you do get from AI citations is dramatically more valuable than the traffic you’re losing.

One AI search citation can generate more qualified traffic than ranking third in traditional results.

This reframes the entire conversation. It’s not a story of decline. It’s a story of where visibility has moved — and how to follow it.

Paid Search: The Most Obvious Reallocation Opportunity

Paid search still works. We’re not suggesting you abandon it. But the old model of routing the majority of your search budget into ads is increasingly hard to defend when AI search is answering your target queries directly — and when paid CTR on those queries has dropped 68% in 15 months.

Consider this framing: ads rent visibility. AI SEO builds it.

A fraction of your paid search spend redirected toward definitive written content — comprehensive FAQ libraries, long-form answer hubs, original research — creates assets that AI systems can cite, synthesize, and recommend. An ad disappears the moment you stop paying. A well-structured, authoritative piece of content can generate AI search citations for years. This is where the concept of AI search stops becoming a concept, and becomes doctrine.

We’re not talking about replacing paid search wholesale. We’re talking about running a controlled test — redirecting even 10-15% of underperforming ad spend, particularly on high-funnel informational queries where AI Overviews are most dominant, toward content that AI models actually want to pull from.

The data on which queries are most affected makes targeting straightforward: Semrush analysis of over 10 million keywords found that 88.1% of queries triggering AI Overviews are informational in nature. If you know which of your paid search campaigns target informational intent, you know exactly where to start the reallocation conversation.

Your Existing SEO Budget: You’re Closer Than You Think

If you’re already investing in SEO, you’re not starting from zero. The overlap between traditional SEO and AI SEO is significant — but the relationship is more nuanced than many assume. People have the misinterpretation that traditional SEO and AI SEO are different, but they’re one and the same. AI SEO takes traditional SEO tactics and amplifies them so companies, regardless of marketing dollars, have a fighting chance in the battle for customer attention.

For Google AI Overviews, 76% of cited URLs rank in Google’s top 10, so organic authority still matters. But for other AI platforms, the picture is different: Ahrefs’ August 2025 research found that 80% of LLM citations don’t rank in Google’s top 100 for the original query. In other words, ChatGPT, Perplexity, and other platforms are pulling from a completely different authority model than Google, one based more on content depth, structure, and trustworthiness than on traditional link equity.

This matters for budget. It means SEO investment alone isn’t enough, but it’s also an opportunity: brands that aren’t dominant in traditional search can still earn substantial AI visibility if their content is structured correctly.

What changes in an AI SEO-refined budget is the emphasis: content engineered for synthesis, schema and technical improvements that help AI systems understand your entity relationships, deeper topic clusters that signal genuine expertise, and performance tracking that measures AI inclusion alongside traditional rankings. This isn’t new spend. It’s refined direction for budget you’re already committing.

Content Budgets: Train the Writers, Increase the Output

Most organizations already fund content creation. The problem is that most content teams are still writing for human readers skimming a blog post — not for AI systems synthesizing answers across dozens of sources.

The structural differences matter. Research shows that 44.2% of all LLM citations come from the first 30% of a piece of text — meaning your introductions and opening sections carry disproportionate weight. Content with statistics, citations, and clear data achieves 30-40% higher visibility in AI responses. And structured content — clear headings, FAQ sections, organized lists — is consistently the format AI systems favor most, with pages that have well-organized heading structures being 2.8x more likely to earn AI citations.

Perhaps most critically for content freshness: pages updated within two months earn 28% more citations than older content. This changes how content maintenance should be budgeted — it’s not just about publishing new work, it’s about systematically refreshing existing assets.

The investment here isn’t necessarily hiring more writers. It’s about training the team you have, building brand-aligned knowledge systems that keep messaging consistent at scale, and implementing AI-assisted drafting workflows that let your writers produce more without sacrificing quality.

Video Production: Stop Leaving Transcripts Behind

Video still matters — but most organizations are capturing only half its value. The visual content gets published, and the transcript gets ignored.

AI systems can’t watch your video. They can read your transcript. A well-optimized transcript structured around high-value questions, cross-linked to related written content, and published on a crawlable page does double duty: it reinforces your brand’s entity signals and creates another surface for AI citation.

There’s also a SERP-level opportunity here. Commercial keywords triggering video results on the SERP increased 24% between October 2024 and January 2025, signaling that video content is gaining real estate even as traditional blue links lose it.

If your video team is already producing content around industry topics, the lift is relatively small. Build transcript optimization into the post-production workflow, develop summary pages designed for AI extraction, and align script development around the specific questions your target audience is asking AI systems. Multimodal reinforcement — the same ideas and positioning appearing in video, transcript, and written form — strengthens the entity recognition signals that AI search relies on.

Podcasts: An Underutilized AI Asset

If your organization produces a podcast, you’re sitting on an asset most brands don’t leverage properly for AI visibility. Natural language transcripts, structured around clear topics, with cross-links to related written content, are exactly the kind of material AI systems draw from for conversational queries.

Published, full-text transcripts support voice mode queries, reinforce topic authority, and build the pattern of consistent positioning that AI systems reward. Structure each episode around a definable topic, create summary pages designed for extraction, and publish transcripts as indexable content — not buried in a podcast app.

Your podcast budget can directly support AI visibility. It just requires a small shift in how the output gets structured and published.

PR Budgets: Shift From Exposure to Citation

Most PR strategies are built around brand mentions, media impressions, and reputation management. Those things still matter. But AI SEO adds a layer most PR teams aren’t thinking about yet: citation authority.

AI systems draw from high-trust sources — and 90% of AI citations driving brand visibility originate from earned and owned media, not paid placements, according to Edelman research. That makes PR one of the highest-leverage channels for AI visibility when it’s directed correctly. Brands in the top 25% for web mentions get 10x more AI visibility than others, according to Ahrefs data.

When your executives appear in authoritative publications with structured, quotable expert commentary, those placements don’t just build reputation — they build the citation trail that AI models use to determine credibility.

Shifting PR strategy from exposure-driven to citation-driven means targeting publications that AI systems index as authoritative, crafting thought leadership placements that can be extracted and attributed, and building entity reinforcement across high-trust domains. This doesn’t require a larger PR budget. It requires redirecting existing outreach toward outlets and formats that carry weight with AI systems, not just human readers.

Technical and Website Budgets: Integrity Signals AI Confidence

Technical SEO and AI SEO are deeply connected. AI systems need to crawl and understand your content before they can cite it. Page speed, schema implementation, content architecture, and clean crawl structure aren’t just ranking factors — they’re trust signals that AI models factor in when deciding what to recommend.

The structural evidence supports prioritization here. Proper FAQ schema increases AI citations by 28%. Sites loading under 2 seconds receive preferential treatment from Perplexity. And schema markup that clearly defines your brand’s entities, content architecture that groups related topics coherently, and knowledge graph consistency across your site all directly improve your AI visibility ceiling.

This isn’t a separate technical budget. It’s making AI readiness part of the criteria for how existing technical spend gets prioritized.

The Reallocation Opportunity Map

Here’s a practical starting framework:

Budget Category	Current Use	AI SEO Redirect
Paid Search	Ad placements	Definitive content, answer hubs, FAQ libraries
SEO	Rankings-focused content	Structured answer content, schema, topic depth
Content	Blog posts, social copy	Content engineering, knowledge base, stat-rich assets
Video Production	Brand storytelling	Transcript optimization, topic-aligned scripts
Podcasts	Audience building	Full transcripts, summary pages, topic structuring
PR	Impressions, mentions	Citation-worthy placements, authority publications
Website/Technical	Redesigns, CRO	Schema, crawl structure, content architecture
Research	Internal reports	Published data, AI-citable original research

Every content-producing activity you already fund can be redirected — even slightly — to feed AI visibility.

The Unifying Principle: Message Discipline

AI systems reward consistency. When your brand’s positioning appears clearly and repeatedly across multiple formats and sources — written, video, audio, PR — AI models develop confidence in recommending you. When messaging is scattered and inconsistent, that trust signal weakens.

This is also why AI recommendations are highly inconsistent by nature: there’s less than a 1 in 100 chance that ChatGPT, asked the same question 100 times, will give you the same list of brands in any two responses. The brands that appear most consistently are the ones with the strongest, most reinforced signals — not necessarily the biggest names.

Every channel your marketing dollars touch should reinforce the same core themes, the same subject-matter authority, the same narrative. Not because it sounds good in a brand guidelines document, but because message discipline is literally how AI systems learn to trust and cite a brand.

A Practical Roadmap for Marketing Leaders

If you’re ready to start, here’s a straightforward sequence:

1. Audit your current spend categories against the reallocation map above.
2. Identify underperforming paid channels — particularly search ad spend on informational queries where AI Overviews are dominant.
3. Redirect a test percentage (10-20%) toward structured, AI-optimized content.
4. Align your writers, video team, and PR agency under a unified AI visibility strategy.
5. Implement structured publishing workflows — opening sections that answer directly, consistent use of headings and FAQ structure, regular content refreshes.
6. Start measuring AI inclusion — track how often your brand appears in AI-generated answers across your key topics across Google AI Overviews, ChatGPT, and Perplexity.
7. Expand investment next cycle based on what’s working.

The advantage of this approach is that it’s reversible and testable. You’re not betting the entire budget on a new channel. You’re running a structured experiment with dollars that are already underperforming.

The Brands Moving First Are Building Structural Advantage

AI visibility compounds. The brands appearing consistently in AI answers today are building citation authority, entity recognition, and trust signals that will be increasingly difficult for late movers to overcome. AI search visitors are predicted to surpass traditional search visitors by 2028 — and if Google makes AI Mode the default search experience, that timeline compresses significantly. For context, AI Mode queries show a 93% zero-click rate, meaning the moment that becomes the default interface, traditional click-based visibility nearly disappears.

The money to fund your AI SEO strategy is almost certainly already in your marketing budget. The question is whether you’re directing it toward assets that build durable visibility or toward channels that are losing ground.

If you want to audit your current budget allocation and identify the strategic opportunities specific to your brand, that’s exactly what we do at Xponent21. Let’s talk.