U.S. Marketing Agencies Use AI to Cut Costs at the Expense of Creativity

Artificial intelligence is now pervasive across U.S. marketing agencies, with nine in 10 using generative AI and half using agentic AI for marketing execution, Forrester Research noted in a new report.

Yet rapid adoption, combined with an industrywide focus on productivity and cost efficiency, is undermining marketing effectiveness, creativity, and long-term brand growth, the firm also found.

The report further states that enhancing the productivity and impact of staff remains the primary objective for agencies to use genAI (81 percent) and AI agents (63 percent). For the second consecutive year, the most cited use cases of AI in marketing include building creative content, crafting media and SEO strategy, and improving internal productivity.

While chief marketing officers and marketing teams can benefit from productivity boosts and cost efficiency in the short term, the emphasis on efficiency stifles creativity and growth in the long term, according to the report.

To realize AI's full potential, Forrester recommends that CMOs and agency leaders must reinvest efficiency gains into talent, training, and AI-powered marketing operating systems that enable differentiated experiences, stronger performance, and sustainable revenue growth.

"AI has fundamentally transformed marketing agencies, but the industry is at risk of mistaking efficiency for effectiveness," said Jay Pattisall, a vice president and principal analyst at Forrester. "Our research shows that while agencies have successfully embedded AI into workflows and boosted productivity, they must now reset expectations and invest in creativity, talent, and marketing performance. Leaders who reinvest AI-driven efficiencies into innovation and differentiated experiences will be best positioned to drive sustainable growth and deliver meaningful business outcomes."

Forrester also pointed out that key takeaways from U.S. marketing agencies' AI adoption, usage, benefits, barriers, and commercial models include the following:

• AI is deeply embedded across creative, strategy, and media workflows Agencies are using AI extensively for ideation, content creation, competitive analysis, and performance reporting; 74 percent use genAI to summarize documents and communications, and 70 percent apply it to research and competitive intelligence, demonstrating its central role in day-to-day operations.
• Reliability, legal, and privacy concerns remain major barriers to scale. Challenges such as accuracy and bias (63 percent), legal concerns (62 percent), and privacy and security risks (55 percent) continue to slow deeper integration. For AI agents specifically, lack of expertise (54 percent) and data infrastructure gaps (51 percent) further complicate adoption.
• Monetization lags, with most agencies treating AI as a cost center. Sixty-one percent of agencies still classify AI as a cost of business, with limited direct monetization, but agentic AI shows promise, with 31 percent of agencies planning to monetize it within the next two years, indicating a potential shift toward revenue-generating AI services.

"The conversation around AI is evolving from adoption to impact. Agencies have embraced the technology; now the focus needs to be on how we use it to drive better marketing, stronger client outcomes, and new forms of value," said Mollie Rosen, president of member solutions at 4As. "The real opportunity isn't simply doing the same work faster; it's using AI to unlock capabilities, experiences, and growth that weren't possible before."