How AI Should (and Shouldn't) Influence Your Keyword Strategy

How AI Should (and Shouldn’t) Influence Your Keyword Strategy

Content marketing managers are rethinking keyword selection strategies. Particular focus is on how to stand out amidst the heavy saturation of AI-generated content in search results.

Does AI Change Which Keywords You Should Target?

AI’s impact on search algorithms and user behavior is undeniable. Marketers are now reworking their keyword strategies to navigate this reality.

The Rise of AI-Driven Content Competition

Generative AI has significantly increased the amount of content available for certain keywords by automating content creation. AI tools like ChatGPT or Jasper can generate hundreds of keyword-rich pieces within days, saturating the digital space.

By leveraging advanced language models, companies can now create a variety of content around high-volume keywords quickly and at scale. Analytics show that 13% of the top-rated content on Google is now AI-generated. Brands can easily produce large volumes of text optimized for specific high-volume search terms.

Which, in turn, leads to heightened competition for those keywords in search engine results pages (SERPs). More websites are targeting the same popular keywords, making it harder to accomplish high rankings.

This influx impacts SEO strategies and places a higher value on originality and relevance. Search engines now prioritize content that provides genuine value to users, and high-volume keywords are more contested than ever. Adapting to this shift requires crafting keyword strategies that appeal to search engines and your target audience.

Identifying AI-Friendly Keywords

Certain keywords, especially factual or generic phrases, are increasingly dominated by AI-generated content in search results. Keywords that are common in straightforward, well-defined topics are particularly easy for AI to handle. Certain keywords don’t require unique insights or the complex perspectives that humans provide. As a result, AI models are flooding search engines and content platforms.

The saturation of AI-generated material is making it challenging for individual pieces to stand out. Similar phrases and structures often dominate across multiple articles. Search engines are responding by refining algorithms to prioritize content demonstrating genuine authority and originality over repetitive AI outputs. A major issue is that AI-generated content may include plagiarized information yet rank higher than the original.

Even after Google’s policy updates in 2023 to try to combat this, it is still occurring. Users will have less incentive to click through different search results if all results appear similar (due to them all being AI-generated), which, ultimately, will narrow the amount of information reaching people.

Assessing AI’s Vocabulary: Should It Influence Keyword Choice?

AI models rely on a limited vocabulary shaped by their training data, which influences the keywords they frequently use and contributes to repetitive content.

Understanding AI’s Vocabulary and Tone

AI models like ChatGPT generate content by drawing on datasets containing patterns of vocabulary and phrases commonly used in online content. However, the quality of AI models and their output depends heavily on the data used in their training. So, AI models generate content using a specific set of vocabulary and phrases.

As a result, these models tend to rely on predictable language and familiar phrasing to create fluid, readable outputs. While this makes AI-generated content easy to understand and widely applicable, it can lead to repetitive or generic keyword targeting. That’s especially true when producing content around popular or high-volume keywords.

When generating content on “how to improve SEO,” AI might rely on generic phrases like “optimize keywords” or “create quality content.” These terms are universally associated with SEO practices, so AI models will recycle these well-known expressions across various pieces.

Ultimately, this creates a saturated content market filled with similarly worded articles targeting the same broad keyword topics. None of these recommendations are particularly helpful, as they are circular and insubstantial.

This trend poses challenges for marketers or brands relying solely on AI-generated content for keyword strategy. As AI’s overuse of generic language reduces each article’s uniqueness, it becomes difficult to differentiate one piece from another. There needs to be a renewed focus on originality, expertise, or niche keywords, offering value that generic AI-generated content lacks.

Finding Unique Keywords and Variations

In response, effective content strategies are shifting to include innovative language and distinct perspectives. Moving beyond standard AI language patterns differentiates human-created content from the sound and tone of AI-generated content.

Marketers can select keywords that are less likely to overlap with AI-driven content by opting for unique phrases, synonyms, or nuanced long-tail keywords.

Should You Compete with AI or Go Niche?

With the rising number of AI-driven keywords and content, marketing managers face a strategic choice: compete for popular, high-volume keywords or focus on niche topics where human creativity and expertise are fundamental.

Evaluating High-Competition AI Keywords

Competing for AI-driven keywords means engaging in a crowded space with vast amounts of quickly generated, formulaic content.

If you have a well-established brand with high domain authority, you may be able to compete for high-competition keywords more effectively. Similarly, if your content is exceptionally unique and significantly outperforms existing content for a high-competition keyword. Otherwise, there is a risk of being overshadowed by generic AI outputs.

There are a number of ways to assess the level of keyword competition in AI-saturated areas:

  • Analyze content quality: Review top-ranking articles to see if they’re repetitive or lack depth—signs of AI-driven saturation. High-quality, unique content can still stand out.
  • Examine SERP trends: Use SEO tools to identify keywords with high competition from AI-generated content, focusing on those dominated by generic, factual phrases.
  • Prioritize niche or long-tail keywords: Opt for more specific or less obvious terms where human expertise and creativity shine, reducing direct competition with AI-generated content.
  • Leverage user intent:  Focus on keywords that meet nuanced user needs or complex questions, as AI-generated content often struggles with deeper insights.
  • Stay updated on algorithm changes: Monitor search engine updates that reward originality and authority and choose keywords where unique content is more likely to succeed.

However, in some cases, it might be best to adjust your strategy to a more niche approach, avoiding high-competition keywords. If your website is new or has low domain authority, targeting high-competition keywords will likely result in minimal ranking success. Other reasons to seek different approaches are if ranking requires high effort or if the return on investment is limited.

Advantages of Targeting Niche and Hyper-Specific Keywords

Alternatively, prioritizing niche areas allows marketers to highlight unique insights, specialized knowledge, and a distinct brand voice. Identify a smaller, more specific niche within your industry where competition is less intense. Incorporate specialist industry jargon, acronyms, and specific terminology relevant to your niche that AI might not readily identify.

Offering content that’s harder to replicate with AI is an increasingly valuable choice in content strategy. Studies show that 20% of consumers feel brands are lazy and uncreative when their content appears to be AI-generated.

By targeting niche and hyper-specific keywords, brands will benefit from several advantages:

Less Competition

Catering to a smaller group of consumers often makes it easier to get their business. Brands or individuals should leverage their specialized expertise and research to identify the specific concerns of their target audience. Choosing keywords niche customers will be looking for means you’ll be more likely to find them.

Example: Targeting “Chinese food” as a keyword, targeting “msg free Chinese food.”

Better Understanding of Customers

Narrowing focus allows for devoted time and research to really understand those customers on a deeper level. Learn all about their pain points, challenges, goals, values, where they go for information, motivations, etc. Those customer insights will lead to specifically tailored content that resonates with them and anticipates their needs.

Example: A manufacturing technology company focused on SMB woodworkers. Knowing a major pain point is the skill gap between retiring and novice woodworkers, support specified content and keywords.

Generate Higher Conversion Rates

When brands target a very niche audience, leads are much more likely to convert as an increased percentage will already be well-qualified.

Example: A bookstore specializing in secondhand books with inscriptions. An audience searching related keywords will already likely be ready to buy.

Establishes Thought Leadership

Becoming a recognized authority and positioning yourself as a thought leader in your niche is a powerful way to establish credibility. Eventually, this expert reputation will also translate to organic exposure.

Example: Bob Ross had a very niche painting technique he taught on PBS decades before keywords were even a concern. However, due to years of being established as the expert in this, Bob Ross’s content still posthumously dominates social media.

This approach can often lead to longer-lasting results and a solidified expert reputation. While niche strategy might not provide the same artificial, instantaneous boosts as AI-generated content, it does make for a stronger foundation.

Integrating AI Insights into Your Keyword Research Process

There are actionable steps for content marketers to adapt their keyword research process in response to AI-driven changes. AI insights can be integrated into keyword research without getting lost in the sea of content built around AI-driven keywords.

Analyzing AI Trends in Keyword Tools

SEO tools provide the clarity needed to assess keyword competition. These will aid in understanding content saturation and identifying strategic keyword opportunities.

  • Analyze top-ranking competitors: Platforms like Ahrefs or Semrush analyze for specific keywords and phrases, helping identify if AI-driven content is prevalent.
  • Identify AI content: Plagiarism detection tools like Copyscape or Originality.ai detect duplicate or AI-generated content within top search results. Helping you assess the level of AI saturation for a keyword.
  • Analyze keyword difficulty: SEO tools like Moz and Google Keyword Planner provide metrics on keyword difficulty and competition level, gauging if a term is oversaturated.
  • Track user engagement metrics: Tools like Google Analytics and Hotjar can demonstrate trends, such as whether AI-driven content affects click-through rates, bounce rates, or session duration, which indicates potential keyword fatigue.
  • Analyze shifts in search intent for keywords: Leverage tools like Google Trends to discover what people are searching for in real-time. If high-volume keywords show limited variation over time, this could signal AI-driven saturation, prompting you to focus on emerging, nuanced topics instead.

Refreshing Keywords Regularly Based on AI Trends

Regularly updating keyword lists is crucial as AI trends shift. This allows marketers to stay ahead of content saturation and avoid keyword dilution in a crowded digital space.

With AI models generating content at scale, popular keywords quickly become oversaturated. By periodically refreshing keyword lists, marketers can pivot toward emerging trends, niche phrases, or long-tail keywords with lower saturation, helping content maintain visibility and relevance in search results.

This proactive approach allows marketers to adapt to shifting search algorithms and maintain a competitive edge by targeting terms that align with current user intent and search behavior. To stay ahead of emerging trends, it’s recommended that you review and update your keyword lists at least once a month.

Balancing Human Expertise with AI Influence

Human insight and creativity are still crucial in keyword selection, even as AI becomes more prevalent in content generation. They provide unique perspectives and strategic nuance that AI alone cannot achieve, even as automated content continues to grow.

Leveraging Brand-Specific Language

Leveraging unique perspectives and brand-specific language makes content more memorable. This strategy is especially important in a market filled with AI-generated material. AI often relies on standardized vocabulary and predictable formatting structures. In contrast, brand-specific language conveys personality, values, and, most importantly, expertise that will resonate more authentically with audiences.

Brand-specific language provides personality, so relying on AI to mimic human persona is always going to fall short. Using a more conversational tone, even when you are portraying expert information, is key.  If someone read your content back to you, would it sound awkward? If so, it’s probably not the path you want to take.

Leave out generic words that consumers will assume naturally about your product, like “high-quality” or “optimum.” Research competitor’s content or relevant content. If you see repeated generic words across all of them, like “quality,” “elevated,” and “dynamic,” the content is likely AI-generated. If you want to differentiate your content, avoid these overused words.

Look at how your target audience speaks on their social media, on LinkedIn, and in forums. Using similar language will help you appeal to them, show that you understand them, and communicate on their level.

Creating Value-Driven, Authentic Content

Value-based content that showcases genuine insights, expertise, and a distinctive brand voice is essential to stand out from AI-generated material. While AI can produce informative content, it often lacks the depth, nuanced understanding, and personal touch that human creators bring.

An NP Digital study revealed that human-generated content receives 5.4X more traffic than AI-generated content. So, while it may be tempting to rely on AI to produce quick content, creating authentic content does pay off.

A good example of this is Last Crumb, a luxury cookie brand based in Los Angeles. A customer will receive around five emails per order. However, the content and copy are the work of Cole Schafer, who champions a uniquely human writing style. The emails entail the brand story, how orders are prepared, and content that is valuable for a niche luxury cookie audience. They receive an explanation of what makes the cookies luxurious. But, the brand voice is imbued with a particularly human style of humor that AI would simply struggle to replicate.

Successful Keyword Strategy Requires Balance

A successful keyword strategy balances AI insights with human creativity. It stays up-to-date with keyword trends while still ensuring that content is original and stands out amongst AI-generated creations.

About the Author: Rhianmôr Thomas

Rhianmor Thomas

I am a freelance writer living in Los Angeles. With an undergraduate in Screenwriting and an MBA, I write for a variety of mediums.

Most days, you can find me working on client blogs, articles, website copy, product descriptions, and more. Currently, I write on a range of topics, specializing in B2B & B2C marketing, fashion, film, social media, higher education, and ecommerce.

I always aim to write copy that makes the reader think – about a better way to do something, the future of an industry or just about their opinion on the topic. When you can blend the goals of the client with the ability to make the intended (or unintended!) audience think – that’s successful copywriting.

To learn more about Rhianmôr, check out her writing profile here: Rhianmôr Thomas