How Can Agencies Adapt as AI Reshapes the Traditional Agency Model?

Key Takeaways:

• The agencies that succeed in an AI-driven industry will be those that use the technology to amplify their unique differentiators.
• AI-driven efficiency gains are reshaping what brands expect to pay for, pushing agencies to move away from commission, FTE, and billable-hour models in favor of output- and performance-based pricing that better reflects the value they deliver.
• As AI compresses timelines and automates many tasks previously handled by junior staff, agency leaders must strategically audit workflows, identify where human expertise remains irreplaceable, and prioritize building AI fluency across their teams.
• High-quality, unified data is the foundation of high-impact AI outputs: Agencies that invest in data readiness and fuel their AI solutions with clean, comprehensive inputs will be best positioned to deliver differentiated results for their clients.

AI is coming for the traditional agency model.

The technology is rewriting the way agencies do business in real time, driving efficiencies, transforming workflows, and opening up new strategic and creative opportunities. AI represents a powerful opportunity for agencies to evolve and improve the way they operate, which is why agency leaders have named it their top investment priority for the second year in a row. At the same time, as these tools automate the time-intensive work that once justified traditional billing structures, 87.3% of agency professionals and 91% of senior agency leaders believe that the traditional agency model is either broken or quickly heading in that direction.

To come out ahead as AI transforms that model, agency leaders must use this critical time to strategize around how the tech can amplify their unique differentiators, adapt their pricing models to account for how AI is changing advertising work, and build the AI-fluent teams that the next era of advertising demands.

How Agencies Can Use AI to Strengthen Their Competitive Differentiators

Embracing AI is table stakes for agencies looking to evolve their revenue models in the years ahead. But how agencies adopt it is what will separate the frontrunners from the stragglers.

To start, there are a variety of best practices agency leaders should follow around AI implementation. Providing in-depth AI education to employees is critical, as teams that understand AI’s strengths and weaknesses are better equipped to apply it effectively. Thoughtfully integrating AI into existing workflows, rather than layering on disconnected point solutions, ensures efficiency gains aren't undermined by the creation of new silos. Investing in custom or specialized AI tools, meanwhile, empowers agencies with advantages that are harder for competitors to replicate. Data readiness is also critical, as AI outputs are only as good as their inputs: Agencies that fuel their AI solutions with large volumes of high quality, unified data will generate outcomes that are more precise, personalized, and tailored to drive maximum impact for their clients.

These operational moves are the foundation for effective AI usage. However, the agencies that stand out in this new era will be those that go further by using AI to amplify their differentiators. Agencies have long distinguished themselves with unique offerings—access to unique audiences, strategy planning processes,  attribution processes, and more. This remains critical today: With 99% of agencies now using AI, those that simply incorporate it into their processes without combining it with genuine differentiators will risk irrelevancy. To provide brands with the value they expect, agencies must offer something inherently unique that they’ve amplified through AI.

How AI is Changing Agency Compensation Models

As agencies realize efficiency gains from AI, brands expect to realize them too—which is why agencies’ pricing models must evolve to stay relevant. Even back in late 2024, three-quarters of brands wanted to change their agency compensation model.

As agencies know all too well, getting the agency compensation model right was a longstanding challenge even before the rise of AI. Part of that challenge has been that brands want to hire agencies for high-level strategic thinking, not to fund the mundane tasks typically handled by junior staff. For many years, however, that kind of manual busywork was unavoidable.

That started to change with the rise of digital and programmatic advertising, and AI is poised to further automate many of the manual tasks that took up a significant portion of agencies’ billable hours. Tasks like pulling reports, putting decks together, billing, and reconciliation—which were once very manual—can now be largely automated with AI.

What does the path forward look like? Savvy agencies are already sunsetting pricing models based on commission, FTEs, or billable hours. And as AI compresses timelines, brands are looking for models that are output-based rather than time-based. For example, some agencies are exploring hybrid pricing models, which mix a percent of media with incentive tiers based on innovation or performance. However, performance-based models are complicated by the industry’s continued struggles to actually prove out performance effectively.

While most agencies are still in the early stages of figuring out these evolutions, those best positioned for what’s ahead are already having these conversations with clients. Doing so proactively signals the kind of forward-thinking partnership that brands expect from their agencies in this new era.

What AI Means for Agency Team Structure and Talent Strategy

Agency leaders must identify which processes they can automate with AI and where to invest in headcount. With over a quarter of marketers reporting that their organizations have replaced human tasks with AI solutions in the past year, auditing workflows to find places where AI can drive efficiency is important work for agency leaders right now.

Reduced headcount may be one outcome for some agencies, but even more, AI will fundamentally change how agencies work, from team structure to how time is spent. Agencies have been through these kinds of shifts before: Before the rise of programmatic advertising, for example, high-impact advertising skills centered around RFPs and negotiations; advertisers had to be great negotiators if they wanted to get the best rates for their clients. Then, once programmatic advertising took hold, the most valuable skills shifted to how effectively advertisers could place bids, test and learn, and optimize accordingly. As the industry shifts again, it’s the individuals with expertise in AI who will drive the most profit for agencies.

Agency leaders should structure their teams accordingly, and work to upskill their current workforce in the technology as well. With 80% of CMOs concerned about an “AI skills gap,” agencies can increase the value they provide their clients by upskilling current employees and growing the AI expertise that brands are seeking.

What the Future of the Agency Model Looks Like in an AI-Driven Industry

AI is raising the bar for what agencies must do to stay relevant. Those that use the technology to amplify their unique offerings, price around the value they deliver rather than the hours they bill, and build AI-fluent teams will be the ones best positioned to maintain and grow their client base.

The traditional agency model may be under pressure, but the opportunity to build something better in its place is real. The agencies taking full advantage of that opportunity now are the ones that will lead the industry in the coming years.

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Looking for more insights around how agencies are approaching this moment? Our 2026 Advertising Agency report synthesizes insights from advertisers working across leading agencies, exploring how they feel about their jobs, their organizations, and the future of the agency work.