Business
The Future of Paid Media Agencies in the AI Era
Seiji Morita explains why standalone media buying is losing ground and how artificial intelligence is reshaping agency operations.
With rising media costs and automated ad platforms, agencies focused solely on paid traffic face operational bottlenecks. Speaking on Marketing - The Podcast, Seiji Morita examines the shift toward AI-driven business models.
In a conversation with Bruno Gimenes on Marketing - The Podcast, Seiji Morita, CEO of Agência Omamori, discussed the transformations sweeping the digital agency landscape, rising customer acquisition costs, and the operational impact of artificial intelligence.
In the video above, Morita and Bruno break down the dynamics of media tools and discuss the practical shifts separating shallow automation from AI deeply integrated into business processes.
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The Exhaustion of the Traffic-Only Agency Model
Rising media costs and extra digital platform fees have squeezed margins for businesses that rely exclusively on paid ads for customer acquisition. According to Morita, depending solely on media buying without a strong brand foundation has become an increasingly uncertain path to profitability.
"I don't see much of a future for agencies that only handle traffic," Morita explains when comparing ad spend allocation to investments in retention and brand positioning. "There are several reasons. Sometimes it's just not profitable for the client you're running ads for, or they don't have a strong enough brand for that traffic to actually convert."
The Evolution of Media Buyers and Platform Automation
As algorithms advance across platforms like Meta, mechanical tasks like campaign creation and tweaking are being absorbed by automated systems. The media buyer's role is shifting toward business acumen and strategic structuring, while direct execution is streamlined by technology.
"It's not that the media buyer role will disappear, but what they actually do is changing. They won't just log in to set up a campaign—they'll structure it, map out where it goes, and look at the big picture rather than just pushing buttons," says Morita. In his view, a professional who used to manage one or two accounts can now, with AI support, handle five or six operations at a much larger scale.
AI as Core Operational Infrastructure and the Middle Market
Deploying generative tools as core operating infrastructure—rather than just secondary research aids—is setting the pace for modern agencies. Morita points to corporate models in China, where workflows systematically pass through artificial intelligence before undergoing expert human review.
Bruno cites data from a Notion study on the Brazilian market showing that 12% of companies are in advanced stages of AI adoption, with the greatest traction among businesses with 0 to 499 employees. Morita notes that lean teams can deliver substantial output by building on an AI backbone: "If AI didn't exist, I don't think I would even have an agency today. A lot of what we do starts as my ideas, which I structure through AI, make the final call, and say, 'Let's test this.'"
Security and Practical Workflow Implementation
Traditional firms often face internal friction when modifying established workflows, whereas lean operations can minimize overhead from day one. While AI accelerates ideation and content production pipelines, Morita emphasizes the critical need for cybersecurity and data governance when developing internal applications.
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