The 2024 AI Revolution in Content Strategy: What’s Changed and What Hasn’t

To say that AI has had a massive impact on content strategy is a bit like describing Harvard as a small private college in Massachusetts. Advancements in AI change how content is made and how people find it. This also affects our worries about who can see the content and how users search for information.
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Keeping up with these developments (let alone writing about them, as this author can attest) can feel like the ultimate exercise in futility: as soon as you feel like you have a grasp on one change or update, there’s a new release or update that upends everything.

However, since “sitting in AI-induced paralysis” isn’t a recommended AI content strategy, let’s take a look at what AI has changed in content generation, what is fundamentally the same, and some suggestions on where to focus your content marketing efforts.

Search engines are now answer engines 

What’s different: the types of content Google values and learns from

Google undoubtedly has been responsible for driving a lot of the content strategy discussions lately. In March, they declared a war against spammy, low-quality content, and instead now (supposedly) reward non-keyword-stuffed, high-quality (in line with their E-E-A-T guidelines valuing expertise, experience, authority, and trustworthiness).

In the middle of May they released AI Overview…and then almost immediately issued an apology for AI Overview. Oh, and in the midst of all this, we can’t forget a massive documentation leak that is one of the deepest looks into Google’s ranking systems as the public has ever gotten.

Despite the controversy, admission by Google of its AI overview generating questionable answers, and combating erroneous-yet-viral results, Google said that these AI-generated recaps are here to stay, no matter the worries about organic traffic plummeting.

That's because search engines are becoming answer engines. 

Users are choosing LLMs like ChatGPT, Perplexity, and other AI interfaces first instead of Google. AI-powered language models are often seen as giving more thought-out, detailed answers. This lets people feel their questions are answered more carefully, instead of having to click and scroll through keyword-stuffed content that could be bad, but still ranked high in the SERP. 

From the leak, it seems that user satisfaction scores are also being considered when Google decides what to rank (or what to summarize and link in its overview). These scores seem to be calculated by how users act after the site, as well as how easy it is to navigate and how good the user experiences are. Simply put: Google wants people who get to the pages to come away satisfied with the result they were served. And it’s up to us to make that content.

What’s the same: we’re still competing for eyeballs

If you’re in the organic traffic game, these latest changes might feel terrifying, and the numbers are starting to show that. Google has made it clear that mass producing lots of AI-generated, unedited, low-quality content isn’t the way to earn ranking results.

People who use your content should feel like they get something from it that helps them or helps the community where it is. The content should be produced by experts or authority figures. Since we know that readers are looking for answers, it’s up to us to provide them with the best ones out there. Any good content strategy should base itself on this fundamental principle, regardless of AI.

Suggestions for answer engine content strategy

• Focus on user-centered content that’s on brand and produced by experts and authorities in the space
• Answer questions that audiences are asking. There’s a reason many searches now often end with the word “Reddit” and that’s because it’s seen as a great knowledge repository with answers to specific questions.
• Begin to consider new metrics for organic traffic success (and if the clicks coming in are more qualified).

AI Generated content worth reading

What’s different: we have AI to help us

Since LLMs came to the public, what little patience readers had for any sort of fluff content vanished completely. Suddenly we were confronted with a barrage of what can only be described as content’s “Uncanny Valley”: while not technically wrong, just very…not right, either. 

On the bright side, this has meant that the quality content you’ve invested in (or will) is now more visible in a sea of “blah.” And while AI-generated content might not be able to produce original insights, it can help lighten the load immensely.

While we know Google is punishing AI-created content, there are ways AI can help us in the content strategy, such as:

• Outlining
• Brainstorming & ideation
• Research & citations
• Copy editing
• Brand voice consistency edits
• Repurposing content for other channels
• Refreshing old content with more recent information
• Auditing for old/underperforming content

These are all parts of the content strategy puzzle that can take a lot of time. With AI, these parts can be made much easier and faster. This can let you spend more time creating the good content you (and your audience) want.

What’s the same: we’re striving for quality content

It might seem disheartening to know that the very company responsible for demanding high-quality content is then using that content to write overview summaries that decrease the chance of that person visiting your site (where, again, your reward for the content production are lead generations). However, it could also inspire something else.

These changes on what types of content are rewarded could allow us to feel a bit hopeful. If usability, satisfaction, and usefulness scores are built into the rankings and rewarding better-written, audience-centered, helpful content…that feels like a good thing for the internet as a whole. Let’s just hope it works out that way.

Suggestions for content strategy with AI

• Do not use AI only to create your content or insights. Use it as one of the tools in your content toolbox, like research summaries, ideation, outlining, editing, etc.
• Utilize AI to perform some of the more mundane tasks related to content strategy, like transforming the content into different channels or formats.
• AI can also help repurpose old content and refresh it with the updated brand voice and new information/updates.

Summary

Content creation is in a period of flux right now in this period of transition in AI adoption. However, both users and the Google ranking algorithms have quickly become tired of any kind of fluff content when used for marketing. This has made content creators focus on good content that answers our audiences' specific questions or needs. 

Luckily, AI can help power every step of the way, and with humans in the loop of the content strategy process, lighten the load significantly in any marketer’s content strategy.