Google & Meta Are Racing to Replace Your Creative Team

The emergence of generative AI has opened up new possibilities for marketers, promising to revolutionize the way ads are created and delivered. Two tech giants, Google and Meta (formerly Facebook), have separately announced plans to integrate generative AI into their advertising platforms, which together make up over 1/5th of global advertising spend.

With this news, advertisers are concerned about losing control of what will be shown to the user, which may contain hallucinations or be off-brand. There are also fears that the rise of generative AI will eliminate many jobs for marketers, copywriters, and designers, as the capabilities of AI models accelerate exponentially.

In this blog post, we will explore the race between Google and Meta to harness the power of generative AI in advertising. We will delve into their approaches, the benefits and challenges associated with AI-generated content, and the potential impact on marketers' roles. Let's dive into the fascinating world of generative AI and its implications for the future of advertising.

The Rise of Generative AI in Advertising

Generative AI refers to the use of artificial intelligence algorithms to create new content, such as images, text, or videos, based on patterns and data it has learned. In the context of advertising, generative AI holds immense potential to transform the industry. By leveraging vast amounts of data and sophisticated algorithms, AI can generate tailored ad variations that resonate with specific target audiences and optimize campaign performance.

The goals and capabilities of generative AI in advertising are multifaceted. AI-powered systems can analyze vast datasets to identify patterns, preferences, and trends, enabling marketers to create highly personalized and engaging ads. By automating the ad creation process, generative AI tools can save time and resources for marketers, allowing them to focus on more strategic aspects of their campaigns.

Moreover, generative AI has the potential to enhance creativity and unlock new possibilities. With AI algorithms generating content, marketers can explore innovative ad concepts and experiment with different variations that they may not have otherwise considered. This opens up avenues for unique and fresh creative ideas that can capture the attention of audiences and drive higher engagement. We’ve talked before about how tools like ChatGPT might change the search landscape, which explains Google’s renewed focus on the area.

However, alongside these opportunities, there are concerns and reservations about the use of generative AI in advertising. One key concern is the potential lack of control and brand consistency. Marketers may feel uneasy about fully entrusting the creative process to AI systems, fearing that the output may not align with their brand identity or messaging. They may prefer to have the opportunity to review and edit the variations created by AI systems to ensure they are on brand and free from errors.

Additionally, there are ethical considerations regarding biases and fairness. AI algorithms learn from vast amounts of data, which may inadvertently contain biases present in the training data. This raises questions about the potential replication of biases in AI-generated ads, potentially perpetuating stereotypes or excluding certain segments of the audience, as well as the potential legal implications of potentially violating copyright laws.

The Growing Demand for AI-Driven Advertising Solutions

The demand for generative AI tools has exploded in the past year, with ChatGPT reaching 100m users in 2 months, faster than any previous consumer product. With the rapid advancements in AI technology, marketers are exploring new possibilities for harnessing the power of AI to optimize ad performance, automate content creation, and drive higher engagement with their target audiences.

The surge in demand for AI-driven advertising solutions has prompted major tech companies, such as Google and Meta, to invest heavily in the development and implementation of generative AI tools. Google was instrumental in the birth of the current AI solutions, having published the “Attention Is All You Need” paper that introduced the transformer model ChatGPT is built on. However they are scrambling to catch up to OpenAI and Microsoft, with Google’s own Bard solution being derided based on its relative quality compared to ChatGPT.

Google's Approach to Generative AI in Advertising

Google has long been a pioneer in the realm of AI and has made significant strides in incorporating AI into its advertising solutions. The company's approach to AI in so far has centered around enhancing the campaign optimization process by offering tools that automate targeting and audience selection to optimize campaign performance.

Google's suite of AI-driven advertising solutions includes features such as responsive search ads and automated ad suggestions. These tools leverage machine learning algorithms to analyze data on user preferences, search behavior, and ad performance to create ad variations that are tailored to specific target audiences. The almost fully automated Google Performance Max ad campaigns have gained a lot of traction amongst advertisers, though there are questions about their incrementality as Measured’s own research has shown.

Furthermore, Google is continually investing in research and development to enhance its generative AI capabilities. The company is exploring the integration of AI-generated content into its ad formats, such as display ads and video ads, to provide marketers with a wider range of creative options and drive higher engagement.

Meta's Approach to Generative AI in Advertising

Meta, formerly known as Facebook, has also been investing heavily in AI research and development, with a particular focus on generative AI for advertising. Meta's approach to generative AI involves leveraging its vast trove of user data, social posts and images as well as ads to automatically generate highly personalized and engaging ad experiences.

The company's suite of AI-driven advertising solutions includes tools like Dynamic Ads and Automatic Placements, which use AI algorithms to create tailored ad variations and optimize ad delivery across its platforms. Mark Zuckerberg has announced Meta is also exploring the integration of AI-generated content, such as images and videos, into its ad formats to provide marketers with a broader range of creative options and drive higher engagement, likely falling under Advantage+, Meta’s closest corollary to Google’s PMax campaigns.

In addition to its suite of AI-powered advertising tools, Meta is investing in research and development to advance its generative AI capabilities. The company is actively exploring the use of AI-generated content in virtual and augmented reality environments for the Metaverse, opening up new possibilities for immersive and interactive advertising experiences.

The Evolving Role of Marketers in the AI-Driven Advertising Landscape

As generative AI becomes more integrated into advertising solutions, the role of marketers is expected to evolve. I’ve seen this play out before in past roles, where all of the manual bidding that we used to do in Excel got automated away, as did the targeting when we moved from likes and interest based audiences to lookalikes. With AI automating many aspects of the ad creation process, marketers can shift their focus to more strategic tasks, such as campaign planning, creative ideation, and performance analysis.

While AI will do a lot of the heavy lifting, if we want campaigns to be uniquely performant we need to provide the AI guidance through prompt engineering. With no ‘secret sauce’ our ads are destined to be average, and we don’t stand a chance of beating the auction. To find a powerful concept or insight to drive your campaigns, I recommend getting good at what I call ‘meme mapping’. This involves absorbing all of the examples in a domain, for example look at all of your competitors longest running ads in the Facebook Ads Library, and spot patterns you can use when you provide the base advertising assets for generative AI to work from.

Moreover, the adoption of generative AI in advertising may lead to a more collaborative relationship between marketers and AI systems. Marketers will still play a critical role in guiding the creative direction and ensuring that AI-generated content aligns with brand identity and messaging. Marketers will likely want to train their own AI models that are ‘on brand’ and use them in their campaigns, over what Meta and Google provide. There will also likely be a role for traditional split testing of important creative concepts in instances where we need to learn what works strategically. By working in tandem with AI tools, marketers can harness the power of AI to create more effective and engaging ad campaigns.

Conclusion

The race between Google and Meta to harness the power of generative AI in advertising is reshaping the industry and transforming the way ads are created and delivered. By leveraging AI-powered tools, marketers can streamline the ad creation process, enhance personalization, and drive higher engagement with their target audiences.

While there are concerns and challenges associated with the use of generative AI in advertising, the potential benefits are immense. As AI continues to advance, the advertising landscape will continue to evolve, with marketers playing a crucial role in navigating this brave new world. In the end, the companies that successfully harness the power of generative AI will be better positioned to captivate audiences and stay ahead in the competitive world of advertising.