In the rush to deploy generative AI for marketing, organizations have ignored one thing: Training.
People may assume marketers don’t need it because genAI uses natural language. However, having the ability to communicate with a technology and knowing how to use it are very various things.
A 2024 report from The Marketing AI Institute found that although 99% of marketers say they’re using AI, 67% say an absence of training stays a barrier to its adoption at work. Without company support, the training is up to you. So, what skills do you need, and the way can you learn them?
The excellent news is you are already an authority in the most vital thing you need to know.
“If you are a marketer, the No. 1 skill you need is expertise in whatever branch of selling you’re in,” said Chris Penn, chief data scientist and co-founder of TrustInsight. “As models get smarter, they’re making mistakes which might be harder to detect if you don’t have expertise.”
GenAI isn’t any longer generating what Penn calls “ChatGPT’s weird word vomit.” The old saying that “to err is human, but to really mess up, you need a pc” is more relevant than ever. Your marketing expertise and understanding of your organization’s goals are key to avoiding those messes.
Beyond that, what you need is a basic knowledge of how genAI works. Fortunately, there are loads of superb, free resources.
Start with the basics
Start off by getting grounded in the basics of AI and enormous language models with introductory articles from OpenAI and Google.
YouTube has many video tutorials, so many who we won’t pretend to know which of them are the best. Here are three Reddit Subreddits where you can search for recommendations:
- r/Artificial
- r/ArtificialIntelligence
- r/ChatGPT
Go to MIT or Harvard without spending a dime
There are also free introductory AI courses from a few of the best institutions in the world.
- MIT’s many offerings include:
- Understanding the World Through Data
- AI 101
- Artificial Intelligence
- Harvard: AI with Python
- Microsoft: AI for Beginners
- Google: Introduction to Large Language Models
Dig deeper: The top 50 genAI use cases in marketing
Next up, you’ll want to deal with optimizing your requests or, in other words, prompt engineering. Again, many world-class organizations are offering free courses on this:
- Vanderbilt Prompt Engineering for ChatGPT
- OpenAI: ChatGPT Prompt Engineering for Devs
- edX: AI Applications and Prompt Engineering
It’s value noting that many institutions offer paid courses that provide certification in all these skills. A fast Google search will reveal courses that concentrate on AI for marketers.
It’s time to get messy
While all that information is useful, there’s one thing that you can start doing now: Play around with the different AI models. Kick the tires. Ask questions — that’s what it’s there for.
Here are some things to take into account as you do that:
- When working with AI-generated content, it helps to experiment with different prompt styles to see how the responses change. You can go broad with something like “Write a blog post,” or get specific with “Write a 500-word blog post on AI in B2B marketing with bullet points.”
- Try role-based prompts, like asking the AI to act as a content strategist and create a LinkedIn post on AI trends. You may also refine responses step-by-step—starting with a general request and tweaking it based on follow-ups.
- Pay attention to how AI adjusts based on tone, style, and structure. For example, asking for an off-the-cuff vs. formal tone can completely change the feel of the response. Giving specific instructions—like “Follow this format: X, Y, Z”—helps guide the output, while revision requests reminiscent of “Rewrite this with a stronger CTA” could make the content more practical.
- AI tools also let you tweak settings to fine-tune responses. The temperature setting controls creativity—lower values keep it focused and precise, while higher values make it more creative. Top-P (nucleus sampling) filters out words which might be less likely to be used, affecting coherence and variety. Token limits impact response length and detail. Playing around with these settings may help you get AI-generated content that matches your needs.
Dig deeper: Is your marketing team AI-ready? 8 steps to strategic AI adoption
This knowledge is crucial for marketers and just about anyone else who does knowledge work.
“We need a much more AI-literate workforce, people who find themselves comfortable with what it’s able to doing,” said Paul Roetzer, founder and CEO of The AI Marketing Institute. “How can I find things I do daily and discover ways to use AI in those things? And if you have that literate workforce, then those people who find themselves domain experts, they’ll work out how to apply it.”
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