‍Agencies, AI and data: Feeding the beast

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The Data Paradox: How More Information Creates Less Friction

Across the agency landscape—from traditional powerhouses to AI-native upstarts—a fundamental shift is reshaping how agencies deliver client value. The equation is counterintuitive yet transformative: more data consistently delivers less—less guesswork, less operational clutter, dramatically reduced client product development cycles, and faster campaign time-to-market that drives competitive advantage.

It isn't just about efficiency. It is and continues to be about reimagining agency agility in an era where speed defines market leadership, especially as they prepare to transform, yet again.

The Client Imperative: An insatiable Data Appetite

While agencies optimize for operational efficiencies and excellence, clients demand exponential increases in data sophistication, especially as they begin to leverage AI, and expect their agencies to do the same. They need deeper customer segmentation insights, robust retention analytics, design-informed data sets, and comprehensive product development intelligence. All table stakes for modern brand building.

The smartest agencies have built capabilities to manage this client demand for more data. In-house data tech stacks are becoming as essential as creative departments. Dedicated data business units are emerging from cost centers to profit-drivers, provided these agencies differentiate their data offerings. As agencies build client-facing AI capabilities, data from just the large platforms means generic, and clients want anything but.

AI as Agency DNA

With competition more brutal than ever and 95% of agencies planning increased AI adoption within two years, traditional mid-size and large agencies face their second existential transformation in a decade. The first was digitization—migrating themselves and their clients into the digital ecosystem. Now it's AI integration: weaving artificial intelligence into creativity, strategy, and execution within a unified, intelligent operating system.

So where are the ad agencies when it comes to AI integration? A 2024 report from Forrester found that:

• 91% of U.S. agencies are using or exploring gen AI tools.
• 95% expect increased use within the next two years.
• 85% are using AI in some capacity.
• 30% of agencies, brands, and publishers currently have full integration of AI across the entire media campaign lifecycle.

The integration solution lies in building modular, interconnected systems where target audience intelligence flows seamlessly into planning, creative generation connects directly to media buying, and reporting feeds back into strategic optimization. Each module learns continuously from fresh data, creating a self-improving campaign machine.

Traditional agencies are racing to catch AI-native agencies like Supergood and Pencil, plus increasingly sophisticated independent shops that have the ability to move faster.

Time is (still) money and talent is key

Integrating AI into the end-to-end campaign journey is already creating revenue growth opportunities for agencies as well as their clients, but only if the models have clean, high fidelity data, and a lot of it. In addition, the smartest agencies use data providers that give them API choice based on their clients' needs. Curating clean, high fidelity data means it is accurate, has a consistent taxonomy, is refined and vetted, and is fully ready for analysis and/or for use in any system. Clean data has also been corrected, standardized, and stripped of errors, duplicates, or irrelevant information - all presented to your analyst, ready to go. Without clean data, agencies' data teams spend valuable client hours on clean up instead of analysis, results, and recommendations.

Steve Lohr, technology and business reporter at The New York Times, says that "Data scientists, according to interviews and expert estimates, spend 50% to 80% of their time mired in the mundane labor of collecting and preparing unruly digital data, before it can be explored for useful nuggets."

McKinsey reports that 60%–80% of a data scientist's time is spent preparing data for modeling, while only 4% is devoted to the actual tuning of models. This imbalance underscores how prepping clean, structured data is critical, but also time-consuming, largely unglamorous, and boring for experienced and talented data scientists.

Freeing up data scientist time means faster, more valuable insights, more clients per scientist, thus more revenue & profit. 

What if you could…A use case

In addition to all the AI and data use cases for campaigns, here's another use case we've discussed with some clients.

An AI native agency is building a platform designed to help smaller-budget indie film studios predict which storylines, genres, or characters are likely to resonate with specific audiences. Major studios and streaming services have been doing this for quite some time. BUT indie filmmakers and studios like A24 and Blumhouse work within very limited budgets, and certainly have far less sophisticated processes than the massive studios.

Problem: To attract indie studio clients and maybe even the big ones, this agency needs to have the most unique data set, based on both long-tail and large platform data sets in order to truly showcase comprehensive, real human thought and trends, not just the large influencer ones.

Solution: Using the Socialgist Filter API, the agency specified keywords and criteria to seek niche film-based online communities. The first benefit was, they saved 98% of their analyst’s time. They then were able to build deeper story insights using GenAI trained on better, high-fidelity entertainment data to help shape, pitch, and polish content that convinced and converted indie film clients. 

Taming the Beast: The Path Forward

AI is forcing agencies to fundamentally redefine their operations in order to compete. What was once a linear, manual, intuition-led process is evolving into a modular, intelligent ecosystem powered by data, automation, and adaptive creativity. For agency leaders, the challenge isn't just feeding the data beast that powers these AI systems—it's ensuring that the beast delivers measurable value to both your operations and your clients' bottom lines. This means investing in clean, high-fidelity data infrastructure, building scalable AI capabilities, and most importantly, maintaining the human insight and creativity that distinguishes great agencies from mere technology vendors.

As Fei-Fei Li, often called the godmother of AI and Sequoia Professor of Computer Science at Stanford, reminds us: "AI is a tool. And tools don't have independent values. Their values are human values. That means we need to be responsible developers as well as governors of this technology."

The agencies that will thrive in this AI-driven landscape are those that master this balance—harnessing the power of data and artificial intelligence while never losing sight of the human creativity and strategic thinking that transforms raw information into compelling brand stories and meaningful client results.

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