Generative AI can make a marketing organization faster at producing content while leaving harder marketing decisions unresolved. For content agencies, this puts pressure on production as a reason to hire an outside partner. Research by Risqo Wahid, researcher at the School of Business and Economics, University of Jyväskylä; Joel Mero, professor of marketing at the School of Business and Economics, University of Jyväskylä; and Paavo Ritala, professor at the LUT School of Business and Management, LUT University, examines how agency professionals and clients perceive this change. Their study, “Technology-Enabled Democratization: Impact of Generative AI on Content Marketing Agencies,” published in “Industrial Marketing Management,” points to judgment, creativity, and business strategy as sources of perceived value as routine production gets cheaper.
AI weakens production as a differentiator
The competitive question is larger than how much agency work generative AI can perform. Agencies and their clients can access similar production tools, making that access a weaker reason to hire an agency, according to participants in the research. The pressure shifts to what an agency contributes to the decisions that shape the work.
A client interviewed for the study described the effect: “We are on the same level. Small companies can produce exactly the same content in the same way. A single person can do an awful lot of what used to require a big organization and a large number of content creators.” This is one participant’s assessment of how the market is changing, rather than a measured market-wide result.
That distinction matters for agency strategy. Production remains necessary because ideas eventually have to become material customers can encounter. The research suggests a change in perceived differentiation: easier access to production puts more pressure on agencies to show expertise in deciding what should be created and why.
More output creates an attention problem
One client interviewed by the researchers described what happened after increasing production: “Over the last month, we have produced two or three times the amount of content, but actually, the number of readers has not grown in proportion, or those who consume the content, or how much they consume.” The observation comes from one participant, so it is not an industry productivity benchmark. It shows the practical gap between producing more material and gaining a proportional increase in consumption.
Another participant described the pressure created by growing web content: “The challenge is that when everyone does the same… the amount of web content will blow up. Even though it might be cheap to produce the text, does it give you the benefit anymore?” This links cheaper production to a harder question: whether another piece of content provides enough benefit to justify making it. The decision shifts toward which work has a strong enough reason to exist.
For executives, output gives only part of the performance picture. A larger volume shows that a team produced more, while consumption and business relevance help determine whether that extra output has value. Selection becomes a central management task: choosing the customer problem, idea, message, and business objective that deserve production resources.
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Agency value shifts toward selection and strategy
An agency executive in the study identifies creativity and strategic work as areas customers may still pay for: “I do still think people’s creativity is what customers are ready to pay for… The strategic work and creativity, to use these tools creatively, only the people can do.” This is the executive’s commercial assessment and should be read in that context. An agency has a stake in customers continuing to pay for expertise as production tools become more accessible.
For buyers, this demands a harder test than monthly asset volume. The research points to customer and business context, messaging, creativity, and strategic choices as areas where agencies can seek to demonstrate value. These decisions determine what enters production and how AI is directed toward an objective. Shared access to generation tools can make the judgment applied around those tools more important when comparing agencies.
Wahid, Mero, and Ritala also identify greater emphasis on strategic consulting, AI implementation, personalization, and business advisory work in their interviews. These are directions perceived by participants rather than evidence that such services produce superior commercial results. The study is based on interviews with 22 people: 13 content marketing agency professionals and nine client-side marketers. That qualitative evidence can show how participants understand changing agency relationships; industry-wide prevalence and business performance require separate evidence.
AI orchestration inside marketing teams
The same decision problem arises inside marketing teams. Higher production without matching consumption is a warning against equating additional output with additional marketing benefit. CEOs, CTOs, and marketing leaders can ask why an asset should exist, which business goal it advances, and what audience response would make the work worthwhile.
AI orchestration means directing AI tools and workflows toward a defined outcome. Here, that means deciding which work a tool should perform and where people should supply customer knowledge, business context, creativity, and judgment. Productivity then becomes a management question about how production capacity is used. Internal teams and external agencies face the same standard: connect execution to a clear customer need and business objective.
Key highlights
- Make judgment the agency differentiator: Generative AI gives agencies and clients access to similar production capabilities. Agencies can differentiate through customer knowledge, creativity, strategic choices, and decisions about what deserves production.
- Measure attention alongside output: Higher content volume does not guarantee proportional growth in consumption. Marketing teams can pair production metrics with audience response and business relevance to judge whether additional content creates value.
- Evaluate agencies on strategic contribution: Buyers can assess agencies by how well they connect messaging, creativity, and customer context to business objectives. Asset volume alone provides a limited view of that contribution.
- Orchestrate AI around defined outcomes: Marketing leaders can assign AI work based on a clear customer need and business goal, while directing human expertise toward context, creativity, and judgment. This keeps increased production capacity tied to marketing outcomes.
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