How Generative AI is Changing B2B Content Production

Recently a colleague of mine sent me an article about how generative AI was causing problems for some SEO folks in various industries. There were several complaints that newly published AI-generated content was starting to push down their rankings. They were having a hard time keeping pace with the stream of content being produced by people leveraging AI to create that content. 

It got me thinking about the state of B2B content production as it relates to SEO and confirmed some of my initial thoughts about the use cases of generative AI after the first time I used ChatGPT. The biggest takeaway for me, when I saw what ChatGPT could do, was that B2B marketers were going to have to use this tool to accelerate their production of high-quality content to keep pace with competitors who would be doing the same. Additionally, institutionalizing AI to ensure consistent production that mapped to an SEO content strategy was going to be critical to future success.

I got even more validation for this way of thinking recently when Google updated its Google Search Central Blog with the following: 

It is interesting to note that the last sentence in this screenshot references Google’s helpful content system which just recently had an update. One of the things that happened during the update was that Google made some changes to its guidelines for content.

Here is the original text:

Here is the updated text:

Notice that the newly updated guidelines do not specify written by people. Rather the emphasis is for people. 

By the way, if you want more information about the latest helpful content system update from Google, check out this article from Roger Montti. 

The point is that Google recognizes that AI is going to be used to create content, or at least write part of it. Google’s main concern is that content is useful to people and that it is accurate. The last part of the sentence is really important because if you have any experience with generative AI you know that it is prone to inaccuracies. Cue in the human editor. 

If you are using generative AI to create content, you need an expert to review and edit the copy before you publish it.  In many cases, you might find the content will need significant revisions before it has the kind of unique value that would make it stand out and be consistent with your brand voice. However, I can say from experience and from the experience of people I work with, using generative AI to augment the content production process greatly improves efficiency if you leverage it correctly. 

The question of how to leverage it correctly really varies a lot depending on what you are creating. For example, in the case of this blog post, I used ChatGPT to write an article about this topic and I used various concepts from the article but none of the actual text from the article made it into this post. That said, reading the initial output helped me to start the article and gave me a lot of ideas about what to talk about.

I have written other articles where the outline and even some paragraphs were incorporated into the published blog post. The same is true for internal documents like POV documents, SOW language, and of course an occasional email here and there. In all of those instances, the output of ChatGPT needed to be edited and slightly modified but it always saved me a lot of time. 

In some cases, I have needed to pull in research from various Websites to write the article or document I was working on. Because I have ChatGPt4 with the Webpilot plugin, which allows me to pull in content from the Web, I was able to get that content or a summary of the content much faster. 

The point is, that there are many ways to use generative AI tools to improve efficiency. You need to find the best ways that work for your workflow and more broadly, in a way that works for your organization to create efficiencies at scale for B2B content production. 

Another important thing to note is that AI doesn’t replace writers, it just makes them more efficient. Google uses the concept of E-E-A-T (expertise, experience, authority, and trust) to train its algorithm. Authorship is one such signal that should not be ignored, especially as the acceleration of AI-generated content expands at an exponential rate. 

Having experts with experience write your content maps with accuracy, helpfulness, and uniqueness. This is one of the best ways to distinguish your content, even if a lot of what is written is produced by generative AI. The added layer of expert editorial review is likely to be a difference in quality that Google and other search engines prefer. Make sure to use Schema markup to attribute authorship to your experts.

AI is significantly accelerating the ability of people to create high-quality content. Page one search engine results are becoming increasingly competitive and harder to obtain. 

It is critical for every B2B organization that wants to rank well in Google for non-brand keywords that could drive high-intent traffic to integrate generative AI into their content production workflows and experiment with how to leverage that technology to improve quality and quantity. If you don’t, your competitors will. Many of them already are. 

Talk with the BOL content and creative team to discover the right approach to AI for your organization.