7.2 What Makes Generative AI Different?

Generative AI tools like ChatGPT and Midjourney can craft human-like conversations, write marketing copy, or produce visual campaigns that feel tailor-made for specific audiences. Unlike traditional AI, which requires marketers to manually define every feature or rule, generative AI allows you to simply describe the outcome you want and then let the model do the creative work. This flexibility empowers marketers to scale personalized content and iterate rapidly. Even better, these tools improve over time, learning from company-specific data so their outputs align seamlessly with your style and workflows.

In this section, we will go through a few examples that illustrate how to describe desired outcomes in practice so you can leverage AI as a true marketing partner.

Generating a Marketing Email

Before Generative AI: Your manager would say something simple like,

“We need a short promotional email for our new eco-friendly water bottle.”

Your job? Spend an hour (or more) manually drafting multiple versions and going back and forth for edits.

With Generative AI: You provide an AI with a context-rich prompt like this,

Then send a final message:

“Okay, go ahead and draft a short, friendly promotional email under 150 words. End with a gentle call to action to shop. Give me two variations to choose from.”

And voilà—the AI will help you generate a polished draft, already aligned with your brand voice and marketing goals. Instead of wrestling with blank screens and vague directions, you’ve guided the AI with real-world context, examples of what worked and failed before, and clear expectations for tone and style.

Your Role as a Marketer?

Set the stage thoughtfully, review the draft critically, and fine-tune where needed. This process allows the marketer to focus their creativity and strategy where they matter most. Succeeding with AI requires thoughtful, back-and-forth iteration. Think of AI as a capable team member, not a robot: someone who can quickly do the heavy lifting if you give them great direction and collaborate toward the final result.

You don’t need to instruct exactly how to write each sentence. Focus on what outcome you want (tone, length, goal) and let the AI supply the specifics.

Designing a Social Media Post Image

Before Generative AI: Your manager says something vague like,

“We need a social media image—make it a sunny park scene with someone drinking from a reusable water bottle. Include our logo in the corner and use green tones for our sustainability message.”

You’d probably jot this down, pass it to a designer, then wait days for drafts. When the drafts come back, they might not match the style or energy you hoped for, and you’d go back with rounds of feedback before landing on a final version.

With Generative AI: Here’s what an effective back-and-forth process looks like—one that you can practice on your own.

Then send a final message:

“Okay, go ahead and generate a bright, modern social media illustration showing a happy college student drinking water from our bottle in a green, sunny park. Make the style minimalist, energetic, and fun—something they’d want to share. Give me three variations to choose from.”

After choosing an image:

“Great—let’s make a couple of small tweaks. Also, can you provide me with the image settings you used—like style prompts, color choices, and any repeatable parameters—so I can store them for future reference? That way, we can recreate a consistent look and feel across all our social media posts.”

And there you have it: with rich prompts like these—ones that include clear goals, background on the audience, style guidance, examples of what’s worked or failed, competitive context—generative AI tools like Midjourney, DALL·E, or Canva’s image generator can produce creative options in minutes.

You describe what you want—style, mood, colors, and tone—and the AI handles all the specifics like composition, layout, and detail. The better your context, the better your results.

And remember: you’re not just “giving commands,” you’re briefing a creative teammate. That means good context, examples, and guidance make all the difference. Treating AI as a capable partner you can iterate with will help you design faster, more creatively, and with more impact.

Personalizing Product Recommendations

Before Generative AI: Your manager might say,

“We need tailored emails with personalized product descriptions for different customer segments.”

That usually means you’d spend days manually:

  • Pulling lists of customers who purchased sports gear last month

  • Writing separate product copy for each segment

  • Personalizing the tone manually in every draft

With Generative AI: You work smarter and faster by describing the outcome you want and letting the AI do the heavy lifting.

Here’s what your collaborative prompting process could look like:

Then send a final message:

Okay, go ahead and generate 2–3 personalized product descriptions tailored for our sports gear customers. Make sure they feel enthusiastic and encouraging. End with a friendly call to action like “Get yours today and keep moving!”

Then follow up with:

Great—these look good. Let’s adjust one to focus more on durability. Also, can you give me the key style parameters (tone, keywords) so we can save them for future campaigns?

That last part is super important: Asking the AI to output its style settings (e.g. tone of voice summary, repeatable parameters, prompt setup) so that it can easily reproduce a similar style next time.

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