How Much Longer Can The Agency/Client Model Survive?

By Shelly Palmer

“The agency model is broken.” This refrain is so worn out it’s a cliché. Yet, despite its obvious flaws, the model has survived for decades. Here’s how it works: agencies base their fees on the number of “Full-Time Equivalents” (FTEs) assigned to a client—essentially, headcount. In theory, more complex projects require more FTEs, allowing agencies to scale revenue with staff allocation. More FTEs mean higher fees; simple math, straightforward billing.

When 1=12

While the FTE-based model is flawed and often exploited, its one saving grace is that it creates predictable billing for both sides. But there’s a new problem. With a single AI-enhanced, well-trained FTE capable of outproducing entire teams, the math changes. Now what?

The Impact of AI on Agency Economics

For agencies, AI-enhanced productivity is quickly creating a serious financial paradox. The FTE-based model, which ties revenue to headcount, is at odds with increased productivity. Said differently, agencies don’t benefit from doing more with less.

Clients are quick to see these opportunities and expect cost savings, pressuring agencies to pass AI-driven efficiencies through lower fees. Brands, focused on maximizing value, view AI-enabled productivity as a way to achieve more for less. This has created an uncomfortable tension: agencies that don’t evolve risk irrelevance, while those that do must find ways to defend or reinvent their fee structures in a world that needs fewer human resources.

Outcome Based Agency Fees

Some agencies are working on transitioning to outcome-based fees (a page out of the performance marketing playbook). In this model, compensation is tied to measurable results like increased sales, higher engagement, or improved brand visibility. This approach directly links agency revenue to performance and better aligns agency efforts with client success.

However, outcome-based fee structures come with their own challenges. Establishing fair and achievable targets requires significant trust and transparency. Both sides need to agree on metrics and understand how factors like market conditions or client-side execution can influence outcomes.

For agencies, this model demands advanced data tracking and analytics capabilities to validate their impact—an area where many clients either lack the necessary infrastructure or are unwilling to share the data needed for accurate attribution.

Alternative Models

There are several alternative models being considered by my agency clients, including project-based pricing, value-based pricing, and even subscription-based services. Each of these models or a hybrid model may ultimately win the day. But there is another approach.

The Future Is Clear, But The Model Is Less So

WPP, Omnicom, Publcis, IPG, and Dentsu are all racing to integrate AI technologies into their service offerings. They are heavily investing in proprietary AI platforms and are quickly evolving into tech-centric entities. How quickly? Far more quickly than procurement departments are going to evolve their approach to agency selection.

What about the client side? Every one of my Fortune 500 clients has dozens (sometimes hundreds) of AI projects underway. Many marketing organizations are deploying in-house AI tech stacks dedicated to specific business outcomes such as: media optimization, creative optimization, personalization, etc. If this trend continues, will they even need their agencies?

This is not a tech issue, it’s a leadership issue. Agencies serve an extremely important purpose. They bring fresh, bright talent with an outside perspective and have the capacity to explore and innovate in ways that in-house teams do not. As AI forces us to separate creativity (humans) and execution (machines), new innovative workflows will naturally emerge. Human-AI co-worker teams will attend to these workflows and all of this will require leadership to evolve.

Which leaves us where we began. “The agency model is broken.” A refrain is so worn out it’s a cliché. Yet, despite its obvious flaws, the model endures. How long will it survive? Your guess is as good as mine. But, I’m looking forward to writing about the brave business leader that steps up and changes the game.

Author’s note: This is not a sponsored post. I am the author of this article and it expresses my own opinions. I am not, nor is my company, receiving compensation for it. This work was created with the assistance of various generative AI models.