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It’s nearly impossible for marketers to get through a day without encountering a conversation, article, or social post about AI—how it can help businesses drive revenue, how governments may regulate its use, how it might transform the search landscape, its environmental impact, and more. Most advertisers feel the technology will revolutionize our industry, with a 2024 Basis survey finding that 87.9% of marketers believe AI will radically transform digital advertising in the next three to five years. However, the newness of generative AI, the risks associated with it, and the influx of AI-driven applications and tools flooding the market can make crafting an adoption strategy a daunting task.
Indeed, the prominence of AI in today’s marketing conversations is in part due to advertising leaders' thirst for guidance on how to effectively adopt the technology, particularly when it comes to paid solutions. Most brands and agencies recognize the significant potential for cost and time efficiencies offered by AI, and that early adoption may provide a competitive edge and drive success for their businesses as the industry transforms. However, they’re also wary of the risks associated with AI—particularly generative AI—as well as the trend of AI-washing, and know they must select paid solutions with care.
The tension between this desire to adopt and uncertainty around how to adopt is evident in the current rates of industry use and investment. While an overwhelming 92% of US advertising agencies are currently using generative AI, exceeding the general business population, only 44% of marketers and advertisers say their employers currently pay for generative AI tools.
These statistics demonstrate that the industry is in a transition period, with many marketing teams using free solutions like ChatGPT as well as older AI-driven technologies that have already been integrated into their work (such as programmatic advertising), but still figuring out how to navigate the adoption of newer paid AI solutions. To make informed investment decisions about these types of solutions, marketing leaders must understand AI’s risks as well as how their peers are approaching paid AI tools.
Marketing teams who have yet to invest in paid AI solutions seem to have some common concerns about the technology, mostly stemming from its risks.
A 2023 Gartner survey found that concerns around inaccuracies and bias in AI-driven software and AI-generated content were the top reasons marketing leaders were hesitant to onboard new AI solutions, along with concerns around relying too heavily on the emerging technology. Marketers are also concerned with how AI-generated content will land with consumers: 60.3% of industry professionals feel that consumers will find a brand less authentic if its marketing and advertising efforts include AI-generated content.
Many of these concerns intensified over the past year as advertisers witnessed controversies related to AI-generated content making headlines. Early in 2024, advertisers saw the risks of bias and inaccuracies in AI-generated content play out when Google had to take its Gemini AI tool offline after it portrayed white historical figures, such as the US Founding Fathers and German soldiers from the Nazi era, as people of color. Ironically, the tool generated the content because of safeguards Google developers put in place to reduce bias, which inadvertently resulted in offensive inaccuracies. And in June, advertisers saw how Toys“R”Us’ AI-generated commercial was met with both backlash from creatives and a drop in consumer sentiment. These well-publicized controversies have likely made many advertisers a bit more wary of genAI’s content creation abilities.
Considering the very real risks associated with AI, it’s critical for marketing leaders to understand what safeguards they can implement to mitigate liabilities associated with any AI tools they consider adopting. For example: Human staff should always review all AI-generated content for bias and inaccuracies before it goes live, legal teams should review any AI solutions under consideration for possible data privacy and security threats before they’re onboarded, and some brands may even choose to forego releasing fully AI-generated advertisements given developments like the consumer response to the Toys“R”Us commercial.
To a majority of marketing teams, AI’s risks still appear to be outweighed by its alluring potential benefits, and budgets are increasingly making room for new paid AI solutions. But with so many new tools and applications on the market, how are advertising leaders prioritizing those tools in which they feel confident enough in to invest?
One August 2023 survey found that data analysis was most commonly listed as a focus for the next 12 months for US and Canadian CMOs, followed by strategy, creative, and content development for media use and audience targeting and segmentation. Digital marketing teams have already benefited from AI’s data analysis capabilities for many years, as it drives programmatic advertising and programmatic optimization tactics like bid shading and machine learning optimization. And AI tools that can assist in the organization and synthesis of first-party data for audience targeting and segmentation are helping advertisers grapple with signal loss and the shift towards a privacy-first advertising model.
Marketing teams are also investing in AI to increase efficiency and streamline workflows. Sixty-one percent of industry professionals say their organization has invested in technology to automate or streamline processes in the past year, and 66% say their organization plans to invest in the technology in the coming year. While not all these tools are AI-driven, AI is opening many new opportunities for workflow automation and streamlining. For example, marketing teams are leveraging AI copilots that work alongside their tech stacks to streamline operations, as well as advertising platforms equipped with digital advertising automation features that simplify various aspects of the campaign process.
Because the technology is so new, most marketing teams are still in the process of optimizing their generative AI usage and investments. And they’re not alone: Only 11% of global companies across industries are using generative AI at scale.
More than 90% of marketers and advertisers say they use generative AI as part of their digital marketing efforts, primarily leveraging the technology to ideate/brainstorm and to draft content/creative, as well as for research and optimization purposes. While AI-led ideation and brainstorming are relatively risk-free, using genAI to draft content and creative comes with distinct risks, and marketers should ensure they are setting up fact checking and quality control systems to avoid AI-generated bias and inaccuracies in their marketing content.
Additionally, though unpaid tools are the most popular, many marketers are recognizing that premium tools offer can more than their free counterpoints. As marketers continue to explore and expand their use of generative AI, balancing its potential benefits with careful management of risks will be crucial for maximizing effectiveness and achieving strategic goals.
Ultimately, while most marketing teams are still working through their approach to newer, paid AI tools, they are readily embracing free tools like ChatGPT. Due to the risks associated with AI, marketing teams will want to invest meaningful time and effort in evaluating which paid solutions will drive the most success for their teams, and what protections they must put in place to use them safely. This will require a significant time and energy investment up-front—but doing so may well help organizations to get ahead of their competitors in the long run.
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Want to learn more about how advertisers are approaching AI, as well as how they’re thinking and feeling about an AI-driven future? Get all the latest insights in our report, AI and the Future of Marketing.