"You're not competing with AI. You're competing with other marketers using AI."

Whether it’s helping craft high-quality copy, monitoring the effectiveness of ad performance, or simply dashing off a quick email to other team members, generative AI is quickly finding a home in most stages of the marketing funnel.

Still, while gen AI adoption continues to rise, especially in marketing functions, widespread implementation is yet to be realized. According to a recent McKinsey report, even the most commonly reported marketing use case was reported by no more than 16% of organizations, indicating that gen AI usage remains rather narrow despite the huge potential marketing organizations stand to gain.

As extraordinary as gen AI capabilities may seem, there’s no magic button to make them materialize in existing workflows and processes. Like any other technology, gen AI comes with its own set of nuances that organizations must understand and navigate.

Recognizing the value, though, many marketing executives are still actively working to surmount hurdles to AI understanding and adoption.

As Alison Wagonfeld, Google Cloud’s chief marketing officer, put it in a recent episode of the podcast “AI That Means Business,” hosted by Custom Content by WSJ, “Last year, people had a little bit of this ‘wow’ mindset. What we're seeing now is much more focused on what we're calling ‘the how and the now’ — and this opportunity to immediately start engaging.”

In the episode, Wagonfeld, along with Marie Gulin-Merle, global VP of Ads at Google, sat down with host Raakhee Mirchandaniat at the 2024 Cannes Lions Festival to talk about how gen AI is already transforming marketing and what leaders need to do to catch this next wave of innovation. (At the event, they also unveiled a new framework for gen AI in marketing, which you can read more about here.)

Reset your AI mindset

Despite apprehension about the impact gen AI will have on future roles, not only in marketing but across every business function, both Wagonfeld and Gulin-Merle emphasized that it’s important to recognize that gen AI is not replacing marketers. Rather, it’s enabling them to work faster, more efficiently, and at a much greater scale.

“The mindset of not being afraid of the technology is very important. We say, ‘You're not competing with AI. You're competing with other marketers using AI.’ It is really an assistance to the work. It's that complement to the work,” Guilin-Merle said. “If we zoom in and look at the marketing function, I think what feels different is the velocity. You can iterate very fast, you can produce. If you just take content, you can produce what I call the three Vs: Volume, velocity, and variations of content.”

One practical example of this concept at work is an opportunity Wagonfield referred to as “a flywheel,” where AI is incorporated into the cycle of building, measuring, and optimizing marketing campaigns. As marketers measure campaigns and learn from those results, they can use gen AI to quickly apply those adjustments to assets in real time.

Furthermore, gen AI models like Google’s multimodal model Gemini can help reduce the less joyful aspects of marketing and give marketers more time to do what they actually love.

“We're working with one leading retailer who was talking about how soul sucking it was to write product descriptions for everything on the website, and they were able to use Gemini and be able to talk, get inspiration, and find ideas,” Wagonfeld said.

Think of the seconds, minutes, and hours you can save when marketers can get a helping hand with the things they don’t necessarily like but have to do. How much extra time would they have to think or create if they could outline a blog post, summarize a 30-slide presentation, or adapt the same social post for different audiences in seconds?

“What I see is the nature of work will change. Some of the drudgery in all of our jobs, not just marketing, will be able to work with AI agents to be able to help us,” Wagonfeld said.

Focus on cultural foundations, not just technical ones

When asked what critical components are needed to support gen AI, Wagonfeld said beyond building strong data and technology foundations, a big part of getting it right is creating a culture of learning around gen AI.

“For marketers to really take advantage of this technology, you have to get your hands dirty, you have to play with the technology,” she explained. “A lot of AI right now has prompting aspects. We’ve set up working groups where people are sharing about what they’re learning every single day, so that we’re sharing all of the best practices.”

Within Google, Wagonfeld said her team is encouraged every day to try and use gen AI in some way, whether it’s searching for information or generating specific briefs for projects. The main goal is for people to get comfortable with the ins-and-outs of prompting to generate the results they want and gain a better understanding of how models behave.

Gulin-Merle echoed the importance of experimentation for building a strong AI culture in marketing, saying, “You can play with content, you can play with creativity. I would get it in the hands of everybody. Not be so focused on the headlines and the predictions. The predictions are just out there. It's really about what we're going to do with the work.”

Put AI guardrails in place

Another key step when implementing AI is ensuring that marketers can use it responsibly and ethically in their work.

“A few things that marketers can do immediately. Define what we call the brand profile, the brand guardrails, and make sure that the brand codes are going to be respected and the content generation is going to be done according to the brand codes,” Gulin-Merle said. “Also, making sure you double check, you have human reviews when necessary, that the information is correct.”

In addition to brand guardrails to ensure AI-generated content adheres to tone, message, and style in marketing activities, it’s also critical to establish clear guidance for AI use, not just in marketing but across your entire organization. This includes publishing clear principles for responsible AI and implementing comprehensive AI governance policies to help minimize risks, empowering teams to harness opportunities with confidence.

Gulin-Merle stressed that every organization — no matter where they are in their journey — needs to make a commitment to responsible AI.

“Overall, each company, and we did it ourselves when we started in AI almost a decade ago, is to declare that you can innovate with responsibility at your core — at the core of everything you're doing,” she said.

Opening image created with Imagen 3 and Vertex AI using the prompt: A cartoonish illustration of a diverse group of workers running through an office that looks all electric, like it's from a sci-fi movie, and they're in a race with suits and sweat bands and running shoes and they're jumping over hurdles that look like they're made out of computer code.