Content creation is one of the leading use-cases for AI in marketing today, but it’s also one of the most misunderstood. The process seems simple: you input a request and get an immediate output. Many marketers, however, report that AI-generated content often feels generic, impersonal, and out of touch. And to make matters worse, the more complex the subject matter, the more questionable the output is likely to be.

There’s some good news for marketers looking to bring AI into the content creation process. With a few key strategies and the right amount of knowhow, you can start generating content that’s both accurate and engaging.  

This guide offers practical steps to improve the quality of AI-driven content, regardless of the tools you choose. Whether you're using large language models like ChatGPT or specialized marketing tools like Jasper, these principles apply across the board.

1. Give AI a voice

Content creation revolves around three key elements: who you’re talking to, what you’re talking about, and how you say it.

—  WHO: Identifies your target audience.
—  WHAT: Comes from your core messaging.
—  HOW: Defines your tone of voice or brand personality.

Before generating any content, your brand voice needs to be clearly defined. If your brand has strong copywriting examples and well-established tone of voice guidelines, your first step should be to plug them into your AI model.

The main reason AI produces generic content is that it lacks human flare and creativity. As a result, it can often fall back on bland language and tired turns of phrase. But if you incorporate your brand’s unique voice into your AI tool’s settings, you can train it to use the kind of language your marketing team would use when they write content.

2. Keep your audience in focus

Like any real-life conversation, it’s always important to know who you’re talking to. You likely have detailed profiles of your ideal customers or marketing personas—so why not use these to inform your AI-generated content? The more specific you are about your target audience, the more personalized and effective your content will be.

Most AI tools offer a way to input audience details, but if you’re using LLMs directly, be sure to provide this information up front in your prompts or create a custom setup so the AI can strike the right tone consistently.

3. Make sure AI gets the message

Combining tone of voice, audience insights, and messaging ensures your AI-generated content aligns with your overall brand. Whether you brief the AI for each project or save this information within the tool, it’s crucial to define your key messaging early.

That might mean including specific taglines, calls to action, or preferred language around products and services—anything that makes it easy to your AI tool to capture the key details of the topic at hand.

4. Good content comes from good context

You wouldn’t set a colleague loose on a task without giving them a solid brief to work with, and AI is no different. Treat your AI assistant like you would treat a team member, provide context to guide the creation of any new content. Without it, the AI might produce content that seems valuable on the surface but doesn’t quite hit the mark.

Specify the content’s purpose, where it will be used, and any preferences for its style or format. The more context you give, the better the output will be.

5. Strong outlines make better outputs

AI struggles with storytelling because it lacks human creativity and intuition. But if you provide a framework for the story you’re trying to tell, AI is great at filling in the gaps.

Outlining is a powerful way to improve AI-generated content. The longer or more complex the content, the more essential it is to map out the journey you want to take your reader on. By providing a detailed outline, you guide the AI to create more structured and coherent content.

6. Never accept the first draft

As great as AI tools are, they rarely get things right on the first attempt. That’s why you should always ask for iterations. AI can quickly refine outputs based on your feedback, whether that’s by tweaking specific wording or altering the angle of a story.

Once you’ve refined the content to your liking, ask the AI to format it in a reader-friendly way with clear line breaks, which will help during editing.

7. Always edit twice

Editing is crucial, especially for text-based content. Here’s a bulletproof process:

—  Refine the AI output until it’s close to what you need.
—  Perform a first edit on the text.
—  Feed the edited version back to the AI for further refinement.
—  You can also use a different AI tool for a second round of refinement.
— Complete a final touch-up to ensure the content meets your standards.

This approach ensures a polished final product, and while it may seem a little long-winded, if you’ve prepared the AI with the right briefing it’s surprisingly efficient.

8. Pick the right tool for the job

While it’s tempting to use free or general tools like ChatGPT, investing in specialized AI tools can significantly improve your content production. These tools often offer extra features tailored to specific needs, such as content optimization or brand consistency.

Just as a CRM tool is more effective than a spreadsheet for managing leads, specialized AI tools are worth the investment for scaling content production.

9. Be prepared to make an initial investment

Think of AI as a new team member—you need to onboard, train, and mentor it to achieve its full potential. While training an AI is faster and cheaper than training a human, the initial effort is crucial for consistent, high-quality output.

It’s important to recognize that working with AI requires an initial investment in time as well as money. Skipping this step can lead to poor results and frustration down the line.

10. Process makes perfect

To maximize the benefits of AI, it’s crucial to establish clear workflows that integrate AI into your content production process. These processes should include:

—  AI finetuning: Continuously update the AI with new data and insights from your campaigns.
—  Content production workflow: Develop a step-by-step process, from briefing the AI to final editing.
— Automation integration: Link AI tools with other software to streamline updates and ensure the AI stays informed about your latest activities.

Creating and managing these processes effectively will ensure that your AI will be productive, useful, and scalable for the long-term.

The goal of using AI in content creation is simple: to do more with less. By investing time and effort into training your AI, setting up proper workflows, and refining your processes, you can create a scalable solution that augments your marketing team and dramatically increases your content output.  

AI can drastically improve efficiency, save time, and accelerate your content production—making it easier to scale your business.

If you’d like to find out how to integrate AI into your content marketing workflows, get in touch with a member of our team.