Ad Agencies Are Weary of Half-Baked AI Tools

In the past nine months, ad agencies have been inundated with pitches from new generative AI companies, as well as incumbent tech giants like Meta and Google.

However, as agencies delve deeper into the practicalities of existing generative AI tools, a growing sense of skepticism is taking hold based on frustrations with where the tools still need to improve, as well as a worrying homogenization of work that uses AI, tempering the mass excitement of the tech, according to eight agencies.

“Not a lot of attention [is] paid to [the] fit and finish of these tools,” said Adam Buhler, svp of creative technology at Digitas. “Everyone is trying to get their feature into the market before others and the implementation is not fully baked in.”

Keeping up with the flurry of new tech is just one challenge. There are over 360 generative AI companies in 2023, according to CB Insights, and funding for the sector has increased fivefold in the first half of 2023 compared to the full year of 2022.

These companies offer generative AI solutions to revamp sometimes dreary marketing tasks like ad copywriting, generating ad visuals at scale and query-based campaign recommendations like media planning.

Take digital marketing agency Winclap, which received 40 new pitches for generative AI tools across various use cases in Q3 alone. After testing, the agency discarded over 60% of them due to issues like hallucinations, according to Leandro Santos, head of creative studio, Winclap.

Performance agency Tinuiti’s practice lead, emerging tech, Nirish Parsad, reviews every new generative AI pitch at least three times. Despite initial variations, subsequent evaluations reveal uncanny similarities in creative output across all demos, including similar product backgrounds and ad copy, regardless of the brand category.

For some agencies, demos appear effective in providing marketers with recommendations to improve campaign performance, but when the tools are queried multiple times, these tools often produce hallucinatory results.

“Over the past year, we’ve seen a shift from back-room testing and caution to a bit of a tech arms race to launch new AI features and new AI tools,” said Brian Yamada, chief innovation officer at agency VMLY&R. “Many of the tools come with a warning sign that they won’t always get things right and are looking for feedback to improve.”

Generative AI’s awkward reality