3 Key Lessons Learned from Using GenAI to Scale Content Marketing
Generative AI (GenAI) is one of the most talked-about innovations in the marketing world, and it’s no surprise why. While it’s not entirely new, many businesses are still in the early stages of exploring how GenAI can support their marketing efforts and enhance customer engagement. According to recent research from Enterprise Strategy Group, over half of organizations are either considering, planning, or piloting GenAI solutions. At MarketingVogue, our marketing team has been actively investigating how GenAI can help address specific challenges, particularly in scaling our content engine to support our demand generation efforts. Through this process, we’ve gathered valuable insights that we believe will help others navigate their own GenAI adoption journey. Here are three key lessons we’ve learned over the past year.
1. Define Your GenAI Goals and Align Your Team
Like any new initiative, the first step in successfully adopting GenAI is aligning your team around clear goals. At the outset, we asked ourselves: “What critical outputs will help us achieve our goals?” and “Where are we currently spending most of our time?” For our team, the primary focus was scaling our content engine without expanding our team size. As a B2B marketing team, we’ve invested significant resources into creating diverse content formats, with a strong emphasis on webinars. In the past year, we produced over 80 thought leadership webinars, which were then repurposed into e-books, blogs, and infographics.
Our challenge was how to scale this process and extend the ROI of each webinar we created. To tackle this, we aligned on our goals and identified the key use cases for GenAI, including the creation of derivative content from webinars. We then mapped out specific use cases, set timelines for testing, and held regular check-ins to evaluate progress and refine our approach. Keeping the team aligned and focused on these goals has been critical to staying on track and maximizing GenAI’s impact.
2. Treat GenAI as a New Team Member: Training and Iteration Are Key
While GenAI holds great promise, it’s important to approach it with realistic expectations. A common misconception is that GenAI can instantly generate perfect, ready-to-publish content at the push of a button. In our experience, that’s not the case. While we can generate drafts quickly, the output still requires human oversight. This is especially crucial when it comes to maintaining brand tone, messaging, and style, which GenAI doesn’t automatically get right.
For our team, we treat GenAI as a partner that helps us create content faster, but still requires training, refinement, and input. GenAI can draft content in a fraction of the time, but we always review and edit each piece to ensure it aligns with our brand’s voice and quality standards. By using GenAI to produce first drafts and then refining them, we’ve been able to scale our content production without sacrificing quality.
It’s also worth noting that our research shows 91% of tech buyers trust expert content over AI-generated content. This means that while GenAI can support content creation, it cannot replace the need for human expertise and thought leadership. So, we use GenAI to enhance our content output while maintaining a high level of trust with our audience.
3. Be Flexible and Creative When Testing GenAI Use Cases Across Your Organization
When adopting GenAI, flexibility and creativity are key. The most intuitive path might not always yield the best results, and the process often involves trial and error. For us, the first use case we tested involved creating long-form content, like e-books, from webinars. However, we quickly realized that there was an even greater opportunity to create derivative blog content from the same webinars. This required us to pivot and experiment with different prompts in our GenAI tool to get the best output for blogs. We tried multiple iterations—over five different prompts—before landing on one that consistently produced strong first drafts.
This experience taught us that innovation often requires thinking outside the box and being willing to adjust your approach. Whether you’re testing new use cases or refining existing ones, maintaining an open mind and being adaptable will help you find the best solutions for your business.
Final Thoughts: GenAI Success Takes Time, Alignment, and Creativity
The journey to success with GenAI isn’t a quick one. It requires clear goals, regular testing, iteration, and—perhaps most importantly—collaboration between human creativity and AI-powered efficiency. Over the past year, we’ve learned a lot about what works and what doesn’t when integrating GenAI into our content creation process. We’re excited about the opportunities GenAI offers, but we also recognize that it’s not a cure-all for every challenge.
By following these lessons, we’ve been able to scale our content efforts, improve efficiency, and maintain high standards of quality. We hope that by sharing our experience, other teams can accelerate their own GenAI adoption and achieve greater success.
For more insights on how to leverage GenAI to scale your content engine, stay tuned for more updates and expert tips from MarketingVogue.
