What AI Generated Content Can Do For Your Organization

**With the launch of ChatGPT bringing AI in general – and large language models (LLMs) in particular — into mainstream discourse, you've probably heard the term "AI content generation" floating around. But what does it really mean — and how does it impact your business? What is content generation? If you take a look at the Harvard Business Review's definition, content generation refers to the process by which: "large language and image AI models can be used to automatically generate content, such as articles, blog posts, or social media posts. This can be a valuable time-saving tool for businesses and professionals who create content on a regular basis." Essentially, AI models today are powerful enough to serve as advanced "writing assistants," creating informative, readable copy in a matter of seconds — provided they have the right inputs. (You probably already know this if you've ever played around with the likes of Jasper or ChatGPT). That said, there are several important considerations for organizations looking to adopt an AI content generation strategy. Two key starting points are:

• Determining the types of content that suit an AI approach, and
• Ensuring that you're basing content generation on fact-based inputs that you control Types of content best suited for AI enhancement Talk of "computers" writing their own articles might make your head spin. But if you take a moment to think beyond the "I, Robot" of it all, it's easy to see how valuable content generation can be. If your organization or business needs to spin up simple, digestible content quickly — but lacks the bandwidth or resources to do it the "old-fashioned" way — AI content generation is an incredible asset: it's quick, cost-effective, and scalable. Further, it can work with your current approach creating content as an accelerator or supplement — not a replacement. There are certain types of content that are best suited for AI content generation. Content generation works wonders for creating copy for bios, event descriptions, FAQs, and sometimes even blog posts. (Essentially, shorter, informative assets that are fact-based, rather than opinion-based.) With content generation, it's possible to stop spending valuable hours on the simple — but important — content you need to have on your site. You can keep the "human touch" for your longest or most complex projects. "Content is king in any digital experience. We've seen time and time again that the more content you have, the better you perform across search engines, websites, mobile apps, and other digital touchpoints," explains Marc Ferrentino, President and Chief Operating Officer at Yext. "However, many teams lack the in-house resources to produce high-quality content at scale." The second piece of the equation is that the inputs used to generate the content — the names, dates, essential facts, and more — need to be 1. controlled by your business and 2. intelligible to AI systems. It's with both of these pieces in mind that we're officially announcing the addition of Content Generation to Yext's Knowledge Graph product. Content generation at Yext After a year-long pilot with several customers, we're launching Content Generation in the Knowledge Graph as part of our Spring '23 release. The addition of Content Generation transforms the Knowledge Graph into a CMS that can create — and proactively suggest – its own content. Yext customers will be able to use these features to easily create descriptions, blog posts, biographies, FAQs, and more, automating what could otherwise be manual and resource-intensive content creation tasks. Further, content can be generated according to a specific set of inputs that are determined by the business — solving for the second key to generating content in an accurate, responsible way. For example, a healthcare system could choose to generate biographies for professionals based on known values for name, education, specialty, and work history. Since content is generated with information from a customer's Knowledge Graph, outputs are more accurate and less susceptible to the "hallucinations" that often plague general-purpose large language models. (As an added layer of quality control, organizations can use Yext's Suggestions workflow to review and approve new content as it gets created.) All of this will give Yext customers a new way to leverage the information they already have in their Knowledge Graph — helping them save time, create more content, and deliver value to their customers. Content Generation is the Knowledge Graph is just the beginning. Yext plans to infuse Content Generation throughout the entire platform to simplify workflows, drive efficiency, and scale content creation. Interested in learning more about the opportunities — and pitfalls — of AI and content generation? Click here to tune into our virtual event with Fabrice Canel from Microsoft Bing.**