A recent Search Engine Land analysis put a number to something many agency leaders already feel: in 2024, 44% of digital marketing agencies viewed AI as a significant threat to their business model. One year later, that figure had jumped to 53%. The squeeze is real, it is accelerating, and the traditional response — adopt AI to cut costs, pocket the efficiency gain — is not working. Clients are doing the same math, and reaching the same conclusion: if AI makes this cheaper, why are we paying agency fees?
The double squeeze
The pressure on agencies is structural, not cyclical. It comes from two directions simultaneously.
On one side, AI is automating the execution layer that used to justify retainers: content briefs, campaign reporting, ad copy variations, keyword research, initial drafts. Tasks that once required hours of junior time now take minutes. The efficiency gain is real — but it flows to the client, not the agency. Budgets shrink to reflect what AI now handles. Retainers that were built on labor hours lose their rationale.
On the other side, the same AI tools are enabling brands to build competent in-house teams faster than ever. Platforms that once required specialist knowledge have become accessible. The bar for what counts as "differentiated agency value" has risen sharply — and many agencies haven't crossed it yet.
The result, as Search Engine Land's analysis documents, is a pipeline crisis: only 14% of agencies describe their current pipeline as "very healthy." Over half say it's average. 32% admit it's not good.
What AI cannot replace — yet
The agencies that are surviving, and in some cases growing, share a common characteristic: they have stopped competing on execution and started competing on insight. Strategic positioning, deep vertical expertise, the ability to read market dynamics that AI cannot yet contextualise — these remain genuinely difficult to automate.
But there is a more specific answer emerging, one that the Search Engine Land analysis gestures toward without naming directly: the agencies that will thrive are the ones that can offer clients visibility in the AI layer itself. Not just search rankings. Not just social reach. Visibility in the responses that AI models generate — the answers, recommendations, and citations that an increasing share of users now treat as definitive.
This is not a marginal observation. As AI Overviews, ChatGPT, Perplexity, and Claude become primary information channels, the brands that appear in those responses have a structural advantage over the ones that don't. And the ability to measure, optimize, and grow that presence is a service that very few agencies currently offer — which means very few clients are currently receiving it.
Citation Rate as an agency model
This is precisely the gap that Citation Rate was designed to fill — and not only for the large brand with an internal marketing team. The platform is built to work as a partnership layer for agencies.
The model works on three levels.
For independent clients and SMEs, Citation Rate provides a self-serve entry point: a Citability Score audit that shows exactly where the brand stands in AI visibility, what the gaps are, and what to fix first. The value is immediate and tangible — and it requires no prior knowledge of AI systems or technical SEO.
For brands with internal marketing teams, Citation Rate becomes an intelligence layer: continuous monitoring of how AI models describe the brand, how that description compares to competitors, which sources AI is citing, and where the brand's narrative is losing coherence across platforms. The AI Visibility Index tracks Presence, Position, and Sentiment across all major AI models — not as a snapshot, but as a trend over time.
For agencies, the model shifts entirely. Citation Rate is not a tool the agency uses internally — it is a service the agency delivers to clients under a partnership structure. The agency gains access to the full platform, can run audits across its entire client portfolio, and presents the results as proprietary intelligence. The Citability Score becomes a client retention mechanism: a metric that the client cannot easily replicate in-house, cannot buy from a commodity provider, and that demonstrates clear, measurable value month after month.
The agencies that will survive the AI squeeze are not the ones that use AI to do the same things faster. They are the ones that use AI to offer something clients cannot get anywhere else.
Retention through measurable value
The Search Engine Land analysis identifies a critical dynamic: clients are cutting agencies when the value feels interchangeable. When content can be generated in-house, when reports can be automated, when the deliverable looks the same regardless of who produces it, the agency becomes a line item — and line items get cut.
Citation Rate changes this calculus. A Citability Score is not interchangeable. It is a proprietary metric, built on a methodology that covers 56+ parameters across five macro-categories — Identity & Structured Data, Reputation & External Network, Content Quality, Semantic Consistency, and Technical Performance. A client who has been audited, receives monthly score updates, and can see their AI visibility trending upward over time is not looking for a reason to cut the engagement. They are looking at a number they did not have before, and that number is moving because of work their agency is doing.
This is outcome-based value — exactly what the Search Engine Land analysis identifies as the direction agencies must move. Not hours billed. Not deliverables submitted. A score, a trend, and a clear line between the agency's work and the client's position in the AI landscape.
The junior talent problem, reframed
The analysis raises a concern that deserves more attention than it typically receives: 66% of agency owners worry that junior team members will have fewer career opportunities because AI has automated the entry-level work that used to train them. This is a real structural problem for the industry.
But it also points to an opportunity. AI visibility work — building citability, auditing brand entity consistency, mapping citation sources, optimising content for machine readability — is not automatable in the same way that content briefs and campaign reports are. It requires human judgment, strategic thinking, and the kind of contextual understanding that develops through experience. It is, in other words, exactly the kind of work that can rebuild the talent pipeline that AI execution has disrupted.
Agencies that build AI visibility practices are not just adding a service line. They are creating a career path for the next generation of strategists — one that is genuinely differentiated from what AI can do, and genuinely valued by clients who are trying to navigate a landscape they do not yet fully understand.
The window is open — briefly
The agencies that move into AI visibility work now have a significant first-mover advantage. Their clients do not yet understand what Citability Score means, do not know how to measure AI Visibility Index, and are not yet asking for it. That is an opportunity, not an obstacle: it means the agency that introduces this framing owns it, and owns the client relationship that comes with it.
That window will not stay open indefinitely. As AI visibility becomes a recognised discipline — and the pace of that recognition is accelerating — the agencies that established their capability early will have case studies, benchmarks, and client trust that later entrants cannot replicate quickly.
The squeeze is real. But so is the exit. It runs through the AI layer — and it starts with knowing what your clients' brands look like to the models that are increasingly making recommendations on their behalf.
Source: Search Engine Land — AI is squeezing marketing agencies from both sides, by Benjamin Wenner (March 23, 2026).