How marketers are working smarter, not harder with generative AI

In a recent report, McKinsey called 2023 “AI’s breakout year.” It was a year when professionals in many industries, in many different parts of the world, and with a wide range of seniority gave generative AI a try. Seventy-nine percent of respondents in the McKinsey survey said they’d had at least some exposure to generative AI, while 22 percent said they’re regularly using it in their work.

Among job roles and industries, marketing and sales professionals are demonstrating early adoption of generative AI, for a few good reasons. First, marketers are skilled at adopting new technology, whether that’s embracing social media advertising at its advent, shifting to mobile-first strategies, or maintaining fluency with an ever-growing MarTech stack.

Secondly—and most importantly—marketers have quickly adopted generative AI because of the myriad of ways it can help them work faster, smarter, and more strategically. Simply put, generative AI’s capabilities align with marketers’ needs. In this article, we’ll outline five main ways marketers are putting generative AI to work for them and provide tips for getting started if you’re not yet an early adopter (it’s not too late!).

‍Defining generative AI

Before diving in, let’s define generative AI. There are many terms swirling around the AI space, so aligning on what we mean by generative AI is important. Whereas AI is an umbrella term for machines mimicking human intelligence to learn, make decisions, and solve problems, generative AI is a specific type of artificial intelligence that creates novel content. Generative AI can create text, images, video, or code. ChatGPT is the best-known example of a generative AI tool.

5 ways marketers are using generative AI

While generative AI is still in its infancy, there are already plenty of use cases that are being put to work by savvy marketers.

1. Synthesizing research: One of generative AI’s biggest superpowers is its ability to quickly summarize data from a wide range of sources. That makes it a great research tool, whether you’re looking to gain working knowledge of a marketing trend, create personas based on publicly available data, do a deep dive on competitor content, or optimize keywords for SEO success.

2. Unblocking writer’s block: Most marketers wear a lot of hats, including content creator. But writing isn’t always an easy task, especially on a deadline. Generative AI can help with initial ideation and topic generation, outlining content, writing first drafts, and adapting existing content for use on other channels. Some more advanced generative AI tools can even be trained to write in your brand voice, using existing brand content as its language model. Avoid the temptation to publish generative AI-created content without a thorough review, though.  

3. Creating graphics, images, and video: Some generative AI tools can help you quickly and easily create graphics, images, and video without the need for heavy design work, a photo shoot, or a video editor. While this is a promising use case, it’s still evolving. Today, it’s still relatively easy to spot AI-generated imagery, so quality and accuracy should always be overseen by a human.  

4. Delivering highly personalized experiences: Audience segmentation is every marketer’s secret weapon, but more often than not, segmentation is limited by time and bandwidth. Generative AI lets marketers quickly generate and implement highly personalized content based on customer data. This has practical applications in everything from customized, curated email marketing content to hyper-specific, targeted advertising.

5. Enriching chatbot experiences: Great customer service boosts brand loyalty, yet many traditional chatbot experiences leave much to be desired. Generative AI enables more responsive and helpful chatbot interactions, with the ability to both deliver content from a wealth of sources and evolve over time.‍

‍Tips for starting with generative AI

Because generative AI is still relatively new, many marketers are experimenting with it without the guidance of specific company or department policies. In this case, be sure to keep an eye on potential risks.

Here are a few specific areas to be aware of:

• Inaccuracy: Generative AI synthesizes information with the assumption that the source content is accurate, but this isn’t always the case. An incorrect or false response presented as factual is known as a hallucination. Always take what AI produces as a starting point, then layer on your knowledge of your customer, industry, and brand—doing additional research of your own as needed.

• Intellectual property infringement: When creating content, images, or video with generative AI, it can be hard to know what’s generated versus copied from an original source. Utilizing an online plagiarism checker can be a helpful tool in ensuring the originality of visual and written content.

• Regulatory compliance: Even if your company doesn’t yet have policies specific to generative AI, it likely has policies in place around data privacy. Industry-specific regulations may also apply. As you’re leveraging owned data with generative AI, be aware of the risks related to sharing customer and company data online.

Want to learn more?

If your marketing team needs more guidance with using generative AI, OneMagnify is happy to help. Reach our team at [email protected] or check out our full Practical AI for Marketers program for more AI content.