We used to write for consumers, then search engines and, now, we find ourselves creating content for artificial intelligence (AI).
Lately, generative search experience — a cutting-edge AI-based search feature — has been reshaping how search engines work, making them more intuitive, responsive and context-aware than ever before.
For businesses, this means a whole new way of being discovered — or overlooked.
In this article, we’ll explore how generative search experience is disrupting search engine optimization (SEO) for business owners, marketers and professionals as well as how businesses can leverage enterprise generative AI to stay ahead of the game.
• The Role of Generative AI in Enhancing Search Engines
• How Generative AI Is Transforming Enterprise Search
• Personalized and Contextually Relevant Search Experiences
• Generative AI’s Impact on Content Creation
• Leveraging Generative AI for Improved SEO Strategies
• Risks and Ethical Considerations of AI in Search
The Role of Generative AI in Enhancing Search Engines
Generative artificial intelligence (GenAI) has quickly gone from being an exciting idea to a groundbreaker in how we interact with technology.
GPT-4, for example, uses machine learning to crunch massive amounts of data and come up with insightful, context-aware responses. But that’s just the beginning of AI’s permeation in the applications we rely on.
Let’s look at the Google generative AI search, also known as AI Overviews. Gone are the days of sifting through endless search results and clicking on multiple blue links to piece together an answer. Instead, Google now serves up a concise AI-generated snippet of information directly at the top of the search results, making search more conversational and responsive to what you actually need.
Google AI Overviews also has a follow-up feature (currently only available in the U.S.) that allows you to interact with search results conversationally. Need more details or want to dig deeper? Simply click on the “follow-up” and ask related questions. It’s as simple as that.
The Google generative AI search feature makes finding answers much easier, especially when you’re unsure where to start or need to dive into specifics.
It’s like chatting with someone who gives you the answers rather than someone who guides you to them.
How We Search, Shop, and Consume Information Will Never Be the Same
Google AI Overviews introduced an updated version of Google Shopping, which, again, is driven by AI to personalize the online shopping journey. This revamped experience launched in the U.S. in October 2024, providing shoppers with improved tools for product discovery, price comparison and even virtual try-ons for clothing.
By delivering detailed product snapshots, complete with reviews, ratings, prices, and images at a glance, generative AI is revamping shopping into a faster, more informed, and highly personalized experience — eliminating the need for endless browsing.
But it’s not just eCommerce that is being transformed.
“Several industries stand to gain immensely from AI-powered features like Google’s AI Overviews,” said Don Gruspe, Thrive’s Demand Generation SEO Strategist.
“In healthcare, for instance, AI can streamline diagnostics and personalized treatment, while in finance, it helps analysts make informed investment decisions by quickly analyzing market trends. Retailers can enhance customer experiences through tailored recommendations, and educators can access valuable insights to improve teaching strategies.
Overall, any sector that relies heavily on data analysis and decision-making is likely to see significant benefits from these advanced AI tools.”
In essence, Google Generative AI Search is redefining how we interact with search engines. Unlike traditional search algorithms that rely heavily on keyword matching, generative AI algorithms can interpret the broader context behind search queries using advanced language models.
For SEO professionals, this means a fundamental shift from investing all their efforts in ranking on the first page to optimizing for AI-driven context and intent. Instead of just ranking for specific search terms, content must now be structured to provide authoritative, in-depth answers that AI can recognize, summarize, and surface in search results. In essence, this pretty much calls for a complete 180 in the way we approach digital marketing.
How Generative AI Is Transforming Enterprise Search
Employees in large enterprises often rely on corporate search software to find both structured and unstructured data — everything from product images to internal business metrics.
According to Coveo, an employee spends about 3.6 hours per day searching for information on enterprise websites, knowledge bases and customer service apps. Integrating this software tool with generative AI for enterprises can empower teams to precisely access business info, documents, tech components and data logs.
Additionally, if you add an AI powered enterprise search functionality to customer-facing apps, like a website search bar, it can greatly enhance the user experience by helping them find what they need faster.
AI enterprise search is capable of understanding nuanced user requests and delivering answers that feel conversational and relevant. The integration of AI powered enterprise search allows search engines to generate more accurate responses by drawing on vast datasets, offering users the information they need without requiring multiple searches. For businesses, though, this shift could imply restructuring their content in a way that AI algorithms can understand and present it effectively.
Image: AISERA AI-based enterprise search dashboard screenshot
Integrating AI With Existing Systems Can Be Complex but Worth It
Traditional search often struggled with industry-specific jargon and context, but now, with AI enterprise search and large language models (LLMs), search tools are more adaptive and smarter than ever. One of the standout advancements is the ability of enterprise AI search to understand and interpret domain-specific terms.
Imagine searching for something complex like “quantitative easing.” An AI powered enterprise search doesn’t just bring up documents; it intuitively understands related concepts like “expansionary monetary policy” and gathers insights from multiple sources, presenting you with a clear summary.
Add to this the support for multiple languages, secure access controls and personalized user experiences that grow more intuitive over time, and it becomes clear how generative AI for enterprises is revolutionizing business search. But adopting AI can get complicated.
“Enterprises face challenges like integrating generative AI with fragmented or unstructured data while ensuring consistency and quality,” said Ken Romero, Thrive’s Demand Generation SEO Strategist.
“Scalability is another issue, as generative models demand significant resources, which can strain budgets. Ensuring user trust is crucial, requiring validation mechanisms to avoid misleading results.”
Partnering with an AI-powered enterprise search provider can help you navigate this challenge.
Personalized and Contextually Relevant Search Experiences
An AI-based generative search experience can transform enterprise search in numerous ways. It can deliver results tailored to individual needs and preferences by considering user profiles, search history and real-time interactions. Over time, this personalization deepens, with AI becoming increasingly adept at predicting what information will be most useful for each unique user.
Traditional search engines treat every query as independent, but generative AI remembers the context of previous searches, allowing users to refine their questions without starting over.
Imagine an employee searching for information on a company portal, first asking: “Leave policy for international employees.” Then, a follow-up query asking: “How do I check my leave balance?”
Contextual search allows AI to understand that these queries are related. Recognizing that the employee is an international one and is likely in the process of planning time off, it provides information about the international paid time off policy and leave balance.
AI, however, is not entirely flawless and can face challenges in navigating intricate questions from users.
“Generative AI often struggles with maintaining context in complex user queries due to limitations in understanding long-term dependencies or nuanced relationships across multiple interactions,” Romero said.
“It can lose track of prior context in lengthy conversations, leading to inconsistent or irrelevant responses.”
Results Based on User Intent as Opposed to Keyword Matching
Now, imagine four different employees searching for information on a company portal: “How can I apply for leave?”, “What is the process to apply for time off?” “Steps for leave application,” and “How do I request a vacation?” Despite the different phrasing, the core intent is the same — applying for time off from work.
Enterprise generative AI search understands that all these questions are focused on leave application processes, recognizing that terms like “apply,” “time off,” “leave” and “request” are related. By focusing on the intent, semantic search delivers content that directly addresses the employees’ needs, enhancing their experience with the enterprise knowledge base.
This makes search engines not just tools for finding information but adaptive systems that anticipate user needs and streamline the process of accessing the right data.
Generative AI’s Impact on Content Creation
Enterprise generative AI can be particularly useful for automating repetitive content creation tasks, allowing employees to focus on more strategic activities.
Consider an online shoe retailer that sells a wide range of footwear for men, women and kids. Using generative AI, the company can create a more personalized and engaging email marketing campaign by analyzing customer data, such as past purchases, browsing history, preferences and even recent interactions.
Leveraging these insights, the shoe retailer can segment customers into specific groups, for example:
• Group A: Women who bought running shoes last year.
• Group B: Men who frequently browse dress shoes but haven’t made a purchase.
• Group C: Parents who recently bought children’s sneakers.
So now, instead of creating a generic email, generative AI can generate customized content for each group, along with dynamic subject lines and greetings.
For example, a subject line for Group A could be: “Ready to Upgrade Your Running Shoes, [Customer Name]?” while for Group B might say: “Step Up Your Style Game, [Customer Name]!”
This has at least three apparent benefits: You save time, you generate more engagement and you get more conversions!
Having said that, as advanced as generative AI is, we are still at the stage where we need final human intervention to approve the AI copy. While generative AI has made impressive strides in content creation, it still lacks the accuracy, human intuition, emotional intelligence and nuanced understanding required for truly compelling and brand-aligned messaging.
Leveraging Generative AI for Improved SEO Strategies
Can generative AI produce optimized, targeted content that ranks better in search engines?
While there is no straightforward answer to this, a more accepted view is that AI-generated content does rank well in search engines, provided it meets Google’s quality guidelines and adds value to users.
It should meet the E-E-A-T (expertise, experience, authoritativeness and trustworthiness) criteria and have the right context. Then again, there are multiple parameters involved, such as backlinks and domain authority — something SEO marketers are already aware of.
But with AI search engine optimization changing SEO rules, digital marketing experts can no longer rely on the current idea of Google-friendly writing strategies to rank on the search results pages. The content now has to be written so that AI considers it worthy.
According to Neil Patel, websites that ranked first for informational queries recorded a 2.86% decrease in click-through rate (CTR) on desktop, while on mobile, the drop was even higher, equaling 3.53%.
What this means is that the what, where, when and how questions are being answered by AI right at the top of the search results without the user having to click on any link.
Adopt Generative Engine Optimization (GEO)
To make up for these shifts in the generative AI search landscape, brands should work on three main areas:
• Distributing content to high-ranking publications instead of trying to rank their own individual articles or pages.
• Creating new value as AI emphasizes authenticity when compiling its response.
• Investing in generative engine optimization (GEO) to combine SEO best practices with an understanding of generative AI to align strategies with the expectations of AI-driven search engines. This helps to ensure your content is discovered and favorably ranked.
By analyzing search trends and user behavior, AI search engine optimization can identify content gaps and opportunities, helping SEO professionals create pages that are more likely to meet user expectations.
Risks and Ethical Considerations of AI in Search
One persistently looming concern about using GenAI is the potential for misinformation. Since generative AI creates new content based on training data, there’s a risk that the generated responses could be inaccurate or misleading, particularly if the AI has been trained on flawed or biased data.
Privacy comes next, especially when AI-driven personalization relies on extensive user data. Search engines need to ensure that user data is handled responsibly, with transparent privacy policies and options for users to control their data usage.
Not to mention, the risk of over-reliance on AI-generated content might stifle creativity or lead to homogeneity in online information. While AI may be highly efficient, it often lacks the unique human perspective that drives engagement and diversity in ideas.
And then there’s the pending doom lurking over content creator jobs.
“AI is unlikely to replace content creators entirely in the near future but will serve as a powerful assistive tool. While it excels in generating drafts, brainstorming ideas or automating repetitive tasks, it lacks the human touch needed for creativity, emotional resonance and cultural nuance,” Romero said.
Addressing these risks and concerns requires a thoughtful approach to AI implementation, including human oversight, ethical training datasets and transparent AI practices that prioritize accuracy and user privacy.
GenAI: From Search Engines to Solution Engines
As generative AI continues to evolve and revolutionize enterprise search, one thing is certain: Embracing the power of generative AI is no longer just an option, but a necessity for staying competitive.
The way we search, shop, and consume information is being reimagined, and businesses that adapt early will reap the rewards. With the right digital marketing strategy and insights, you can harness generative AI to not only meet today’s challenges but also seize tomorrow’s opportunities.
At Thrive Internet Marketing Agency, we’re strategically redefining what’s possible in the digital sphere. Reach out, and let’s explore what’s next for your business.
