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Artificial intelligence is transforming the world of social media advertising—and fast. But when it comes to a channel where backlash can be particularly swift and unforgiving, just how fast should brands adopt these new technologies?
Social advertisers are seeing a boom in AI-powered advertising tools, and teams are facing increased pressure to embrace them to harness the speed and efficiency they promise. At the same time, some of these tools—particularly those powered by generative AI—have come accompanied by new concerns around both quality and brand safety, as the race to bring new AI solutions to market has resulted in many of them feeling like they’re still works in progress.
Advertisers worry about the quality of AI-generated ads, given events like Google’s recent suspension of its Gemini AI chatbot’s ability to create images of people after it generated historically inaccurate images. And a recent study found that only 38% of consumers have a positive view of AI, calling into question how AI-generated ads will be received.
A healthy dose of skepticism is, well, healthy. But these concerns, while well-founded, don’t mean advertisers should avoid testing and learning with AI-powered tools that fit their goals. There are a variety of ways advertisers can begin adopting these technologies to tap into their benefits while maintaining caution around things like brand safety. As automation- and AI-led solutions become the new normal in digital advertising, it’s critical that teams start developing their skill sets and increasing their familiarity with these tools to ensure they can use them with confidence and enjoy the increased efficiencies they provide.
AI has already started to change how advertisers target audiences on social media. Many platforms—including Meta, TikTok, and LinkedIn—are beginning to pull back on the number of manual controls they’re giving advertisers to connect with target audiences. Instead, they’re moving advertisers towards AI-powered tools that identify the most appropriate target audiences for their campaigns. For instance, Meta’s Advantage+ Targeting feature automatically identifies targetable audiences based on factors like performance data, consumers’ interactions with other ads in the same vertical, and the content consumers are looking at across Instagram, Messenger, and Facebook.
In some ways, this is a very exciting development. We’re seeing solid results from our own use of these tools, so the numbers are speaking for themselves. On the other hand, it’s a bit nerve-wracking: Advertisers aren’t used to letting platforms take the wheel like this, and if you have a very specific target audience in mind—and you're spending an enormous amount of money trying to reach them—you want to know that you're serving ads to the right people. The shift toward AI-powered audience targeting may end up creating yet another black box to baffle and frustrate advertisers desperate for transparency.
However, this is the direction these platforms are going in, which means we’ll eventually reach a point where advertisers won’t be able to revert to those very specific, manual settings they’d grown accustomed to. Because of this, it’s critical for advertisers to at least begin testing and learning with these tools to grow more comfortable with this shift.
Of course, having AI handle the targeting doesn’t mean advertisers should just set and forget these campaigns. It’s critical to review performance data and assess whether the AI-powered tools are actually accomplishing their goals. For example, if an advertiser is running a lead gen ad, and Facebook is recommending some fairly broad targeting settings, is that actually driving quality leads? Maybe… or maybe not. In this new, AI-driven social world, advertisers will need to carefully assess and adjust their strategies accordingly.
Social platforms are also empowering advertisers to create assets like copy, images, and entire ads via AI. There are a number of significant benefits to these tools, the biggest being simplicity, speed, and ease of launch. This type of built-in efficiency could radically transform how advertisers develop and scale their social campaigns. Advertisers can generate and test new creative variants across different audience segments for more fine-tuned campaigns, or even experiment with entirely different creative approaches to see which resonates more strongly with consumers.
However, efficiency without effectiveness is ultimately inadequate, and many advertisers have real concerns around this shift towards AI-generated content. Without sufficient quality control and campaign monitoring, advertisers using AI-generated ads run the risk of wasting money on ineffective creative—or, worse yet, garnering some serious backlash from consumers.
There’s also some concern that we’re going to get to the point where most (if not all) of the ads on social are generated by AI, and we may well hit a point where consumers don't want to see AI-generated assets, but will instead desire something that feels a little more authentic. Considering this, advertisers should start to think about how they can strike a balance and find the right opportunities to use these tools, but not necessarily allow them to dictate all their social media advertising and messaging efforts.
Social listening is an increasingly key advertising tool, providing insights that can significantly impact a brand’s strategic approach. Manual social listening can be time-consuming and tiresome, but new AI-powered social listening tools can review and process huge amounts of data and sentiment and automatically pull out the top takeaways for advertisers’ immediate use. For instance: What are the top concerns of consumers in a certain category? What does overall sentiment look like? And why is it negative or positive?
Comparatively speaking, these AI-powered social listening tools are also a safe and impactful way for social teams to leverage AI, as they aren’t generating anything that is subsequently going out to consumers. As a result, this is a solution that’s seeing a high rate of adoption: In Q4 2023, social listening was the third-most popular use of AI (after chatbots and copy generation) among brands and retailers, with 40% saying they use AI-powered social listening tools.
All in all, social listening offers even the most AI-averse advertisers a low-risk, high-reward avenue for harnessing the power of AI.
The best ways to leverage artificial intelligence-powered tools for social media advertising will differ from agency to agency and brand to brand: Some are ready and willing to go all-in on generative AI, for instance, while others may approach adoption at a slower pace. Whatever pace you choose, the important thing is to test and learn in some way on tools that fall into each of these three categories. The future of social advertising is AI-driven, and advertisers who don’t start getting comfortable with these technologies will lack a competitive edge as these solutions grow more commonplace and become more advanced in the coming years.
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Curious about how your peers feel about generative AI, which GenAI advertising tools they’re leveraging, and how often they’re using them? We surveyed over 200 marketing professionals from top agencies, brands, non-profits, and publishers to get a pulse check on the industry’s sentiment towards and use of GenAI. Read all about it in our report, Generative AI and the Future of Marketing.