AI Use Cases for Enterprise SEO & Digital Marketing Teams

As an SEO and marketing manager at MeasureMinds Group, a digital marketing agency that’s been in the space for 20+ years, I’ve worked with many enterprise clients to improve their SEO. 

With the widespread adoption of new artificial intelligence (AI) tools and new AI-powered search features, enterprise SEO strategies are changing rapidly. But I’ve noticed that many SEO teams at enterprise companies still struggle to make the most of these advancements in AI. 

If you’re ready to get up to speed with the latest AI developments impacting SEO and digital marketing — and start taking advantage of the potential opportunities in this space — you’ve come to the right place. Here, I’ll outline the latest AI trends in enterprise SEO and enterprise marketing more broadly — and provide some actionable tips and tool recommendations for SEO teams to get the most from our increasingly AI-powered digital marketing landscape.

 

Article summary:

• AI and machine learning have long been a part of how search engines work — Google introduced its first deep learning system, Rankbrain, a decade ago. 
• In recent years, the adoption of AI and machine learning in online search platforms has increased, with multiple search engines introducing new features like AI Overviews directly in the SERPs. 
• Enterprise SEO professionals should stay up-to-date with the latest AI search features, as these developments will likely impact your website’s traffic and performance. 
• Digital marketing and SEO leaders should also evaluate newly available AI tools to help make their workflows more efficient and effective. 

 

The evolution of AI in search & SEO 

The presence of AI in SEO isn’t anything new. Artificial intelligence and machine learning have played a role in both search engine algorithms and the tools that power our optimization strategies for some time. Web analytics platforms also use machine learning to spot trends in user engagement. Keyword research tools use AI to help identify high-ranking keywords. The list of use cases for AI in organic search and SEO goes on and on. 

The early days of search: manually curating the web

Taking things back to the start (and I mean the start!), Yahoo! actually hired real people to hand-pick a curated index of the internet, and they organized it into folders/categories. But as the internet grew (and so did their backlog of sites to add), the need for algorithms in online search became apparent.

The introduction of ranking algorithms and AI in search

Google created and introduced search engine ranking algorithms that considered various factors, such as backlinks, keyword usage, and density, amongst many others. We still see these core ranking factors today, just through hundreds of iterations.

Understanding — and adapting to — the latest search algorithm changes has always been an important aspect of SEO. 

Nearly ten years ago, Google introduced its first deep learning system, Rankbrain. Rankbrain is a GoogleAI model that uses machine learning to help the search engine ‘understand’ search intent. The point of machine learning is that it becomes better as time goes on.

Advances in AI were reflected in further iterations to Google’s machine learning and natural language processing (ML/NLP) search algorithms, including the BERT update introduced back in 2019.

AI in search today

In recent years, of course, there has been an explosion in AI development. Innovations such as generative AI tools (like ChatGPT, DALL-E, and Midjourney), predictive analytics, and AI automation have impacted almost every area of business. 

This brings us to the latest Google AI implementation for search: Multitask Unified Model (MUM). This again builds upon previous ML/NLP models and introduces new features such as the ability to analyze all media formats instead of just text.

Other search engines quickly adapted to the introduction of powerful ML/NLP models such as ChatGPT 4+ by implementing it within their SERPs. Google has caught up by implementing its own version of generative AI in search: AI Overviews powered by its own custom AI model, Gemini.

These developments have made AI both a friend and enemy to SEO marketers. They provide newer, more targeted ways of climbing the search results. However, they have also removed a lot of the real estate that organic search previously occupied in the SERPs. And let’s not forget to mention, in many cases, completely removing the need to click through to a website at all, which could tank some domains’ traffic — especially for simple informational searches.

But Google drawing select information from websites into the SERPs isn’t a new thing. Google’s enhanced SERP features have been around for years and have long aggregated multiple websites’  data into overviews, similar to today’s popular AI tools.

SEOs, just as they did when Google first released ‘rich snippets,’ will have to adapt to today’s AI SERP invasion.

To produce successful enterprise SEO strategies in 2025 and beyond, you cannot sleep on the latest trends in AI. 

 

7 AI trends & use cases for enterprise SEO and digital marketing teams

Here are 7 AI trends for enterprise SEOs and digital marketers to pay attention to this year. 

 

1. Using generative AI for content creation and optimization

Generative AI has been at the forefront of many of the latest AI innovations, allowing users to quickly create images, videos, and text from a simple prompt. Since its release, the technology has advanced rapidly. AI-generated images, for instance, have gone from low-resolution graphics to high-quality visuals.  

Marketing leaders are excited about new generative AI capabilities:

• 98% of executives stated that Gen AI was a ‘hot topic’ of discussion with their boards, according to research published by CapGemini.
• 58% of marketers reported that generative AI had increased their performance, according to eMarketer. 

For enterprise SEO teams, generative AI tools like ChatGPT have many use cases. One option could be to ask AI to write blog posts for you — though this approach may yield poor-quality results if not properly managed. Purely AI-generated content isn’t perfect and can have issues with both flow and factual accuracy.  

Fo example, when CNET launched AI-generated articles on its site back in late 2022, more than half of the articles contained factual errors, according to reporting from The Verge — and the publication faced quite a lot of public criticism for the way it used AI. (Note: CNET’s parent company has since sold the tech magazine for a loss…)

Google’s preference for human-first content means that web content managers should focus on creating content based on real people’s opinions and unique use cases and methodologies. Stuff that AI just can’t do yet. Use generative AI instead as a tool to support your content creation process rather than expecting these tools to produce publishable text.

Spend time learning how to write prompts that get your AI-generated output closer to your goals — or consider additional layers of AI tools — like an “AI text humanizer” tool that, somewhat ironically, uses AI models that are trained to try and make other AI-generated text sound more ‘human’. Or try tools like Grammarly or Wordtune, which can help you by having AI reword your own sentences to make them more concise or elaborate on certain points.

Some generative AI tools also allow you to train AI on your own brand materials to produce outputs that are more in line with your own messaging and brand language. Some can even capture your voice and face to create video content in your likeness.

If that’s all a bit too dystopian for you, here are a few ways I like to use AI to support content optimization without expecting a fully publishable content piece to be generated in one go:

• Creating article briefs and layouts before writing.
• Coming up with FAQs to help improve user experience.
• Sorting through lists of keywords to find those most appropriate to your audience.
• Finding quick definitions and fact-checking
  • (Be careful with new concepts as AI might not fully understand them yet.)
• Identify grammatical and structural issues.

The great part about AI is that you can be really creative in your prompt engineering and your application of it.

 

2. Speeding up SEO admin at scale with AI tools

SEO platforms like Lumar have introduced new time-saving, AI-powered tools that help SEO teams work more efficiently and reduce the hours spent on necessary but time-consuming admin tasks. 

For example, Lumar’s generative AI tool for dev ticket creation takes your website crawl data and the SEO issues identified on your site to create actionable dev tickets for you to assign to your engineering team in seconds. 

 

3. Using predictive analytics for SEO forecasting

Predictive analytics is a subset of machine learning that can help you predict future trends. This form of SEO AI can enhance your approach to SEO in many different ways. You can start experimenting with predictive analytics tools to:

• Develop more engaging content using behavioral data – Google Analytics already uses AI to analyze behavioral data and show you your most engaging pieces of content. Understanding what increases engagement allows you to create better content targeted for your audience.
• Using historical data to help guide future SEO strategies – Predictive analytics can use historical data to look at how users reacted to previous pieces of content. Based on this information, it can project how posts covering similar topics will likely perform.
• Find the trending topics of the future – It’s possible to use AI APIs with existing keyword research tools in order to constantly monitor keyword clusters and growing topics/trends within those clusters. Think of having AI monitor AnswerThePublic keywords along with Google Trends data.
• Predict competitors’ SEO strategies – To stay ahead in SEO, it’s important to know what your competitors are doing. With predictive analytics, you can analyze your competition, and predict their future keyword usage, and the types of content they might produce in the future. 

 

4. Optimizing your website content for Google’s AI Overviews

Google has recently improved its search functionality to provide AI-generated overviews directly in its search results.  Google’s AI Overviews use generative AI to pull information directly from web pages and then display a summary of this information in the search results.

With Google’s AI Overviews, searchers no longer have to click through to a website to get information. This improves the user experience, helping people get the information they need more quickly. 

This poses a challenge, however, for SEO teams. Users won’t need to click on your site if the answers they seek are relatively simple and easily summarized by AI. And how can you ensure Google picks up your website for inclusion in the AI-generated results? 

Start by assessing the quality of your content. Higher-quality content is likely to rank better in search engine results pages. Brush up your articles and ensure they provide real value to your human readers. This should always be a priority.

Secondly, content creators should create highly unique content that focuses on real-life use cases. Make it actionable and provide first-hand experience and insights. (Remember, Google’s Search Quality Raters Guidelines were updated to include an extra ‘E’ — for experience — in its ‘E-E-A-T’ recommendations for evaluating content quality.) 

Creating unique, highly differentiated content gives your team an advantage because AI struggles to create truly unique content. This is because AI is trained on existing content and it is likely to regurgitate information that already exists on the web. 

So, building your website as a reputable source for unique content will encourage people to click through to your site and read more, even when there is a summary of your content in Google’s AI overviews.

Part of preparing your website content for the increasing prevalence of Google’s AI Overviews in the SERPs should also include producing content built around ‘user intent.’ Consider the different questions that users are asking online. Then, produce content that answers those questions. We will probably see very specific, ‘longer’ long-tail keywords become more important in SEO as people look for answers to more specific questions that AI overviews cannot easily summarize. 

 

5. Using AI to enhance user experience (UX) and personalization

AI can help you analyze the patterns associated with your user journeys. You can then also use AI tools to create more personalized content to match the users’ perceived preferences. 

For example, Algolia uses machine learning to understand what a user likes and then serves up tailored, dynamic e-commerce recommendations at multiple stages of the user’s journey on your site based on those preferences.  Implementing a similar model could keep users engaged with key pages on your site by suggesting content based on their preferences and user journey stage, eventually leading them on a conversion path.

AI personalization is a technique that many brands are already embracing; 73% of brands agree AI will transform personalization and marketing strategies, according to Segment’s State of Personalization Report. Below are some examples of how AI tools can help produce more tailored user experiences: 

• Create user interfaces that adapt to the needs of each user. 
• Ensure that users find the information they need on a page more quickly. 
• Draw users to product categories that they are more likely to enjoy. 
• Identify areas where different types of customers are encountering friction. 

 

6. Creating omnichannel marketing strategies with AI tools

A recent GWI study shows that the average social media user visits 6.7 platforms monthly. To cater to this wide spread of platforms, enterprises try to be present on as many channels as possible. 

Modern customers want seamless interactions with your brand. When customers go from one platform to the next, their experience should feel the same. This requires embracing an omnichannel approach. Luckily, AI can help you analyze these channels to create better omnichannel marketing strategies.

Firstly, you can use AI tools to look at how different audience segments interact with your brand. What kind of content do they enjoy? What tone of language are they more responsive to? You can tailor your marketing with this information to create more targeted and relevant content for each segment of your audience. 

The modern chatbot is another example of how AI can assist with omnichannel marketing. The latest chatbots utilize natural language processing (NLP). This allows AI to interpret human language and provide intelligent responses. 

AI-powered chatbots can be used for tasks such as lead generation and qualification. Instead of filling out a monotonous form, a user can have a more interactive experience with an AI-powered chatbot. AI-powered tools can even look at a customer’s previous brand interactions so that a customer doesn’t have to repeat certain information.  

 

7. Leveraging schema markup / structured data at scale

Schema markup (also known as structured data), although not necessarily a direct search ranking factor, is necessary to help search engines understand your website content — and serve it to users with enhanced SERP features. In our developing AI landscape, I believe schema markup will become even more critical for website managers to implement.

If your site is easier for crawlers to understand, search platforms can better deliver the content users are looking for in both standard search results and AI-augmented SERP features.

We will likely see more AI-assisted schema markup generator tools come out which will help marketers leverage it at scale across their websites. This will be especially helpful for large enterprise-size sites with lots of URLs.

Learn about schema markup if you’re still unfamiliar with how it works, and make sure to start applying it on your site. Keep an eye out for new tools that can help do a lot of the heavy lifting for you. 

 

AI challenges and ethical considerations

AI can bring many advantages to enterprise SEO. It’s no secret, however, that AI is a contentious topic. To avoid enterprise SEO mistakes, you should be mindful of several factors when implementing any large-scale AI changes. 

Your marketing team may have concerns about switching to AI-based tactics. Emphasize that AI is a tool to support your SEO tactics rather than replace marketing professionals. 

AI also brings several ethical questions, as tools need to be trained with large amounts of data. It’s important to be transparent about how you’re collecting and using this information. Depending on the location of your customers, you may also be legally required to gather consent before collecting data.

 

Tools for enterprise SEO and website optimization

We’ve explored some of the latest AI trends that professionals are thinking about in the enterprise SEO and digital marketing space. But what tools and platforms should enterprises be investing in to improve their websites today? Consider implementing the following types of website optimization tools and platforms to streamline your optimization efforts in the AI age:

• Optimization tools – Where should you focus your website optimization efforts? The right website optimization platform can help you easily uncover opportunities to optimize your site across multiple disciplines like SEO, site speed, accessibility, and your website’s overall technical health. The best solutions also come with in-depth reports to support your SEO strategy.
• Monitoring tools – It’s important to spot the latest SEO trends before they strike. Website monitoring tools can alert you to the latest trends so that you can react quickly. 
• Automation tools –  Automated website optimization tools can help you streamline your SEO and site improvement efforts via use cases like automated website quality assurance tests and customizable controls that let you prevent potentially harmful code from being published to your live site to begin with.
• Accessibility tools – To ensure maximum user experience, it’s important that all users can access and use your website. A website accessibility platform can help you identify user barriers and improve accessibility on your website. What’s more: AI-assisted web accessibility tools can suggest tailored solutions to resolve accessibility issues uncovered on your site.  

 

Future outlook: what to expect in 2025 and beyond 

We’ve explored some of the AI trends at the forefront of enterprise SEO and digital marketing today, but what’s next? Without a crystal ball, we can’t predict the next stage of enterprise AI development. What we can say, however, is that the AI revolution will continue to accelerate. Enterprises must prepare now to avoid being left behind. 

For a comprehensive, enterprise-scale website optimization solution, marketing teams should look no further than Lumar. Complete with technical SEO, web accessibility, and site speed analytics, QA testing automation, and much more, the Lumar platform provides everything you need to embrace the future of website optimization. 

Try it for yourself: book a Lumar platform demo today.