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Advertising Week New York 2023’s key generative AI takeaways

With an ability to create new content and ideas like never before, generative artificial intelligence (AI) has captured the widespread attention and imagination across the advertising and marketing industry. In fact, by the close of 2025, less than two and a half years from now, three of every ten outbound marketing messages from enterprises will be the result of generative AI.

This is certainly an exciting inflection point in the widespread adoption of machine learning. However, there’s still a lot left to be learned about generative AI—including how it will impact and drive the future advertising landscape.

New York Advertising Week is a gathering of marketing, advertising, technology, and brand professionals tackling the biggest issues shaping) the industry. At the event, Tia White, General Manager for Artificial Intelligence/Machine Learning at Amazon Web Services (AWS) hosted a panel that included Jay Pattisall, VP Principal Analyst at Forrester, and Credera’s Chief Data Scientist Vincent Yates, to discuss recent questions and concerns about the transformative force of generative AI.

The session, “Generative AI and the Changing Advertising Landscape” takes a deep dive into advertising and marketing use cases for generative AI. It helps viewers learn about (and anticipate) the biggest impacts generative AI will have on businesses, from personalization and customer experience use cases, to content and creative development.

For those who were unable to view the session live, or for attendees looking for a refresher, our experts have compiled key points and takeaways about generative AI. They can not only help you understand this dynamic, everchanging technology a bit better, but also help you become more successful within your own generative AI journey, wherever that may be.

Generative AI, what is it?

Before we discuss generative AI’s influence on advertising, let’s start with the question “what is generative AI?”

First and foremost, generative AI is a type of artificial intelligence. Like most AI, generative AI is powered by machine learning models. But unlike traditional machine learning, generative AI takes large amounts of data used to pre-train large foundation models and applies one model to many use cases.

Thanks to generative AI, companies can produce anything from images to music, to conversations, all at a rapid speed. Because of this, generative AI has had a profound impact on businesses. For engineering companies, generative AI has made code smarter and more secure. For marketing companies, generative AI can be used for things like text summarization or image generation. But what does generative AI look like in advertising and marketing? How did we get here? These are the types of questions our panel tried to answer for audiences at Advertising Week. Here are the takeaways:

Marketing content development will be key for generative AI in 2023

“We started tracking the adoption of generative AI as a technology in Q1,” says Pattisall. “In Q1, 19 percent of marketers had adopted and were implementing generative AI as part of their marketing executions. By Q2 that jumped to 60 percent.” That’s a significant increase; not only illustrating the adoption rate of generative AI, but it’s potential as well. According to Pattisall, content is the area in which marketers seem to have the most interest for generative AI. That’s because companies can quickly produce content results based on text prompts.

“Roughly 44 percent of marketers are using generative AI for marketing automation and email. About 30 percent are using generative AI in advertising creation, and another 30 percent are using it for briefs and insights,” says Pattisall. Other applications include search, search engine optimization (SEO), and web content development.

“We also see a lot of marketers indicating that they’re using generative AI as part of media planning and buying. There’s a problem with that.” The problem, Pattisall explains, is that there’s not a lot of generative AI use cases for media. “What they’re actually doing is mistaking the broad label AI for what is traditional predictive AI, which has been powering media and optimizing media now for the better part of 10 years. Really, the center of gravity in 2023 for generative AI is marketing content development.”

Generative AI is largely misunderstood, but it doesn’t need to be

After generative AI made waves in mainstream media, there was concern among many about this technology eliminating jobs. “That fear is very well founded,” says Yates. “But it’s a misconception. When you look back at previous generations of companies, the ones that failed didn’t fail because of something they did wrong. They failed because they did the right thing for too long. I’m worried that some people believe that they can just keep doing what they’re doing.” According to Yates, people don’t need to be worried about generative AI taking away jobs and one reason for that lies in a historical example: automated teller machines (ATMs).

“The idea behind ATMs was to automate the job of a teller. But if you think about banks today, there are still human tellers at the bank. ATMs actually were widely successful, and the number of tellers increased at the same time. Why? Because it meant that you could open up more banks. The profession grows because the cost of doing that has decreased and I think that’ll end up being true here too for a lot of the things that we automate.”

There are ways to ensure ethical and responsible use of generative AI

The philosophical question of “should we be doing this?” (should we be doing AI?) is a massively important discussion happening both inside and outside the tech community. But it doesn’t mean companies can’t use generative AI ethically and responsibly,

“My advice is to learn your trade, relearn your trade, and upskill yourself”, says Pattisall. “Recognize the advertising tools that are being built and that have, at times, been abused. Spotting opportunities to negate these issues, raising your hand and bringing forward ideas to create a more ethical and privacy safe advertising environment is paramount.”

Pattisall suggests doing (consistently) things like recording the prompts that you’re using or creating a prompt library so that you can track what is effective and what is not effective. “This makes a paper trail for your company that will be inevitably very necessary. It also demonstrates human involvement. These things won’t be automated away, so you need to be ready to deploy your generative AI skills as a part of your job, especially in the next 18 to 24 months when issues around liability and regulation will manifest themselves,” he says.

Advertisers and marketers should run to generative AI, not from it

Depending on a company’s maturity or state, Pattisall believes there are three basic steps marketers and advertisers should follow when it comes to living in this new world of generative AI: create a vision; create a council; and create a playbook. “There’s a lot of human anxiety built up in the concept of automation,” says Pattisall. “So, the vision is emotional safety and to illustrate how the company intends to use AI and automation in a way that benefits you and helps meet not only the company goals but meet your individual goals.”

Though he agrees with Pattisall, Yates has just one piece of advice for advertisers and marketers: run to generative AI, not from it. “I would encourage anyone to run to generative AI. Have fun with it, don’t make it seem so overwhelming. Research shows time and time again as new technologies come out, that playing around with technology is the key to success. Have fun and build the muscle,” he says. “It’s only been six months. Nobody expects you to have the answer yet. So, start playing and exploring. A year or two from now it may be too late.”

In summary, from infrastructure to applications and solutions, we know generative AI will have a profound impact across the advertising industry.

It is important that advertisers and marketers engage generative AI now, to begin the process of training and refining their foundational models, enabling them to build the integrations they need to evolve to this changing landscape.

Reach out to learn how AWS can help you build a strong foundation to start your generative AI journey. AWS enables enterprise level generative AI workloads with services such as Amazon Bedrock, a fully managed service that offers a choice of high-performing foundation models from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a single API, along with a broad set of capabilities you need to build generative AI applications.

Contact an AWS Representative to know how we can help accelerate your business.

Further Reading

Steve Kondonijakos

Steve Kondonijakos

Steve Kondonijakos specializes in Advertising & Monetization for the Media, Entertainment, Games, & Sports Industry Marketing team at Amazon Web Services.