Generative AI is here to stay: Where advertisers are spending their money

By Nicole Perrin | March 5, 2024

Reading time: 4 minutes

Generative Ai Is Here To Stay Where Advertisers Are Spending Their Money — Generative AI is here to stay: Where advertisers are spending their money.

Abstract

We are continuing to see advertisers increase their use of generative AI to maximize performance, but which AI tools are they using the most? A majority of advertisers are spending money on text-based tools but many hesitate to incorporate image-based AI tools to their toolkit. Advertisers are continuing to discover which AI tools work best for them while continuing to create brand safe content.

Research Topics:: Advertising Research | Artificial Intelligence / AI | Brand/Image Development | Branded Content Research | Text Analytics
Industry/Market Focus:: Advertising Agencies | Research Industry
Content Type: Research Industry Voices

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How generative AI is used in advertising

Editor’s note: Nicole Perrin is the vice president of business intelligence at Advertiser Perceptions.

2023 was the year of generative AI, with tools like ChatGPT and Google Bard hitting the mainstream. Given their prevalence in the marketplace, advertisers started experimenting with these tools, using them to create content or to help with business development. While these tools might be new to the market, the concept of using machines isn't new to advertisers, as analytics and machine learning (ML) have been a part of their toolkit for years.

With 2024 slated to be the year that generative AI grows and develops, will advertisers make room in their budgets for this technology?

The top AI tools for advertisers

According to an analysis of 155 advertisers conducted in October 2023 by Advertiser Perceptions, most ad dollars in the AI/ML marketplace are going to text-based generative AI tools (39%) and performance-optimization tools (37%). These investments make sense from a time and cost saving perspective. Advertisers might use text-based generative AI to help with brainstorming new ad copy or sales and marketing collateral while they use performance optimization tools to adjust ad copy based on how it’s performing mid-campaign.

Larger advertisers are planning to spend more on average on text-based generative AI, while smaller advertisers will spend more on performance tools. This discrepancy is largely a result of the budgets available to advertisers, as larger companies have the budgets to experiment more while smaller companies have fewer employees so are more keenly focused on maximizing their performance.

Advertisers are less likely to invest in image-based generative AI, as only 29% of ad dollars are going to these tools. Image-based generative AI can help with ad creation or brainstorming new campaigns, serving as a starting point for new collateral. Advertisers are more hesitant to invest in these tools as their quality is not as good as human-produced work, which can lead to larger problems for the work they do for clients. Since generative AI is still in its early stages, many images have an uncanny valley appearance, which can lead to a negative perception among consumers. It can also lead consumers to think less of a brand that is willing to outsource its advertising collateral to AI, as they feel it leads to fewer jobs for humans.

Generative AI budgets

In terms of where the budget is coming from, half of advertisers are using their general advertising budget to fund AI/ML technologies, while 24% have a dedicated AI budget. Marketers are significantly more likely than agencies to have a dedicated AI budget. Marketing teams at brands are largely leading AI exploration or initiatives, as two-thirds of respondents left these responsibilities to the marketing department. Larger spenders at both brands and agencies are more likely to involve research and insights teams, newly created roles and the C-suite in their AI exploration. This suggests that smaller, more nimbler agencies are likely to leave it to marketers themselves to use and adopt AI and are giving them the dedicated budget to do so.

Creating brand safe generative AI content

While enthusiasm for using AI/ML among advertisers is high, many still have questions about brand suitability. Three-in-four advertisers agree that AI-generated content can result in the rapid spread of false but persuasively written information. Seven-in-10 also agree that AI-generated content has the potential to infringe on intellectual property rights, risking brand safety violations. Advertisers are more comfortable when suitability can be verified, as two-in-three advertisers are willing to advertise within AI-generated content in this context.

As the technology matures, deep fakes and misinformation will continue to be an issue until changes are made to how existing material is used, and more regulation is enacted to protect intellectual property. Recently, celebrities like Tom Hanks and Gayle King have had their images used unwillingly in advertisements, illustrating some of the issues that occur with using AI in ad creation. While regulating the use of AI was part of the new SAG-AFTRA deal, most industries still lack protections for how existing images and content are being used. Until then, there will be some hesitancy among advertisers to use AI unless they can properly verify that using it will not lead to any copyright or IP issues.

The future of AI in advertising

Overall, AI/ML tools provide advertisers with endless possibilities on how to use this technology to enhance their work. There is a budget for them to experiment and use different tools to see which ones suit their needs best. However, it’s important for them to verify that they’re creating content that is brand safe. For technology providers, this will be the key to driving more adoption in the advertising community and the world at large.