The landscape of online search is shifting QUICK, and businesses that want to stay ahead should understand generative AI-based search. But what exactly is generative AI-based search, how does it compare to traditional SEO, and what should your business be doing to stay visible in this changing environment?
What is generative AI-based search?
Generative AI-based search is quickly becoming the norm. Imagine a scenario where you’re searching online for detailed information on “best practices for writing case studies.” With traditional search, you’d typically click through several results, sifting through ads, irrelevant content, and fragmented information to piece together an answer. But with generative AI-based search, platforms like Google’s Gemini, Bing/Copilot, or Perplexity summarize multiple sources into one concise, accurate, and ad-free response.
This new search approach is booming because users prefer convenience and efficiency. According to a recent Wall Street Journal article, traditional websites are seeing up to a 40% drop in traffic due to generative AI tools. These tools reduce friction, offering immediate answers without the bombardment of ads and irrelevant content.
Why is generative AI-based search growing?
There are two major factors driving the growth of generative AI-based search:
1. Improved user experience: Traditional search often involves clicking through multiple pages to locate specific information buried among distracting advertisements. AI-generated summaries drastically simplify this process, offering immediate, clear answers.
2. Efficient content aggregation: Generative AI doesn’t just simplify individual pages—it synthesizes information across multiple sources into one cohesive summary. Users no longer need to mentally compile information from numerous sources; AI does this automatically, enhancing overall usability.
Understanding generative AI’s knowledge base
Generative AI models derive their responses from three main sources:
- Long-term memory: Training data (web archives, books, code repositories).
- Short-term memory: The user’s input or prompt.
- Real-time data: Live search results and current information from the web.
Tools like ChatGPT, Copilot, and Gemini seamlessly blend these data sources, creating highly relevant responses.
Influencing generative AI and visibility
For businesses, the rise of generative AI search means shifting from traditional SEO alone to broader visibility strategies. To influence AI recommendations:
Focus on brand visibility: Brand recognition significantly affects user prompts. If customers specifically search for your brand, generative AI tools will naturally deliver your content. Thus, building a strong, memorable brand presence becomes even more essential.
Increasing training data presence: AI models are trained on massive text databases like Common Crawl, a comprehensive archive of the public web. To impact these models’ recommendations, your brand needs extensive, consistent visibility online. This means creating high-quality content regularly, across multiple platforms and formats (text, podcasts, videos, transcripts).
Unlike traditional PR strategies prioritizing high-profile media placements, generative AI-based visibility rewards widespread and frequent content placements—even in smaller, less prestigious outlets. Quantity matters because AI models weigh each content piece equally. However, maintaining content quality is critical, as AI developers increasingly favor curated, high-quality sources to improve accuracy and relevance.
Traditional SEO is still crucial
Despite the shift to AI-based search, traditional SEO remains critically important. Why? Because generative AI platforms like Bing and Gemini still depend on real-time search data. When a user interacts with generative AI tools, behind-the-scenes searches are performed to gather current information, feeding into AI-generated summaries. Therefore, your content must still rank highly in traditional search engines to ensure visibility within AI-driven summaries.
Optimizing content for Bing Webmaster Tools (powering Copilot and ChatGPT) and Google Search Console (powering Google’s Gemini) ensures your website continues to perform well across all search platforms.
How should your content marketing evolve?
Businesses must adapt their content marketing strategies to thrive in this AI-driven search ecosystem:
1. High quantity and quality content: Create consistently valuable content across multiple platforms and media formats. Your content strategy should emphasize frequency, depth, and relevance, ensuring your brand becomes a significant part of generative AI models’ training data.
2. Multimodal content: Embrace transmedia strategies, creating interconnected content across video, audio, blogs, and social media, always including accurate transcripts or subtitles. AI models heavily utilize multimedia content platforms like YouTube, making multimodal visibility essential.
3. Explicit brand references: Ensure each piece of content explicitly references your brand name and targeted keywords. This practice reinforces your brand’s association with relevant topics within AI-generated summaries and model training datasets.
Preparing for the future
Generative AI search isn’t just a passing trend—it’s rapidly becoming the standard. Businesses slow to adapt risk losing visibility. To summarize the key points for a strong strategy right now:
- Recognize generative AI as essential, not optional.
- Maintain and enhance traditional SEO practices.
- Aggressively expand your digital footprint with diverse, quality content.
- Clearly integrate your brand into every content piece.
By proactively adapting your marketing strategy, your brand can not only stay visible but also thrive in the rapidly evolving world of AI-driven search.
