Using Generative AI in Advertising: Insights from an Agency CTO

Artificial intelligence (AI) has made significant strides in recent months, capturing the attention and curiosity of the public with the realization of the potential impact on various industries, including advertising. Much of the recent buzz is due to the emergence of generative AI computer systems that can create new content based on a massive training process to understand patterns that exist in text and images.

Generative AI systems, such as ChatGPT and Bard, hold promise for assisting creativity, streamlining content generation, and even personalizing campaigns. It’s important to understand how generative AI could impact the industry and the work produced. In this article, I’ll dive into the possibilities, challenges, and potential effects of integrating generative AI in advertising agencies.

The Power of Generative AI in Advertising

Generative AI offers exciting possibilities. By leveraging these vast amounts of training data and hugely complex neural networks, it can assist an agency in generating content and streamlining processes.

For example, generative AI can act as a helpful tool during brainstorming sessions, offering inspiration and suggesting innovative concepts or visual elements. It can provide an automated means of supplementing “spitballing” sessions to provide an unlimited set of ideas that can inspire new avenues for exploration.

Conceivably, agencies may be able to harness generative AI to create highly tailored and targeted ad campaigns. By analyzing customer data and behavior, AI algorithms could generate personalized content that resonates with individual audiences, leading to more effective campaigns.

AI-powered tools, when guided by appropriate human prompting, can automate simple content creation processes, such as generating social media posts, designing basic graphics, or, soon, even creating video ads. This automation has the potential to save time and resources for agencies while consistently maintaining quality standards.

Generative AI can analyze extensive datasets, potentially uncovering valuable patterns, trends, and audience insights and communicating them in a way that enables faster, more objective analysis of the data for optimization of campaigns and understanding of engagement.

The Limitations and Challenges

While generative AI offers exciting opportunities, it’s crucial to understand and acknowledge the limitations and challenges of the technology– both to better utilize it as well as to address its impact on the necessary training and investment that will be required by agencies.

AI-generated content often lacks the depth and authenticity that human creativity brings– it is generic content synthesized from thousands of examples. Striking a balance between generative AI and human touch is vital to maintain content quality and align with the client’s unique brand identities. The key ingredients of these identities are often too subtle or contextual for the AI to understand without constant human attention and refinement.

Because generative AI relies on massive amounts of training data and purely computational algorithms, it can reflect the biases or questionable content hidden in that training data and the algorithms themselves. Agencies must establish processes that ensure that AI-generated content adheres to ethical guidelines, avoiding any discriminatory or otherwise inappropriate content.

Finally, there’s no free lunch. Agencies will need to invest in people, resources, data, and infrastructure to keep up with AI advancements, ensuring that their models stay up-to-date and aligned with evolving industry trends. Over-dependence on a few monolithic providers will result in generic content that doesn’t change over time as human-generated content does.

Impact on Employees

At the top of the list of concerns about AI is the impact that integration of generative AI in advertising agencies is likely to have on the roles of employees.

The adoption of AI will, necessarily, lead to a shift in job responsibilities. For example, employees may transition over time from purely manual content creation to overseeing AI-powered systems, curating and refining the output, and focusing more on strategic aspects of campaigns. This collaboration between AI systems and human professionals will hopefully result in more efficient and impactful creative workflows.

In order to retain the most talented employees, agencies will need to provide opportunities for them to acquire new skills related to these technologies, analysis of their output, and effective utilization of the tools. The best employees will embrace the advantages that these tools provide and will want to work where their upskilling is supported and encouraged.

Conclusion: AI is Another Tool in the Agency Toolbox

Generative AI holds considerable promise for advertising agencies, enabling enhanced creativity, greater efficiency, personalized campaigns, and streamlined content creation. However, agencies must navigate the challenges of maintaining content quality, addressing ethical considerations, and leveraging the skills of their employees to apply these technologies appropriately and effectively.

While AI will inevitably automate certain tasks, human expertise will remain invaluable. Agency professionals play a critical role in strategy development, critical thinking, and leveraging emotional intelligence to create compelling campaigns that resonate with audiences. These generative AI systems blindly recombine and generate variations of whatever data they’ve been fed based on their training algorithms, which often leads to errors, bias, and low-quality, generic output.

The real power of the agency is in the ability of the people to understand all of the subtle contextual pieces that make up a great campaign and meaningful interpretation of data to drive results for their clients.

This article is featured in Media Impact Report No. 45. View the full report here.