How AI Is Changing The Way Customers Search For Businesses
Jay Sen, CEO of JV Capital & HireCoder AI– Expert in AI, tech startups, VC & recruiting.
Traditional search volumes are expected to drop 25% by 2026 due to AI chatbots, according to Gartner. Meanwhile, websites already ranking high on Google are losing nearly 50% of traffic because of Google's AI Overviews.
It's not just a trend but an actual shift. The way people find businesses is changing rapidly—and I believe this change necessitates that we as business leaders modify our strategies to remain visible and competitive.
Traditional search engines like Google initially relied on exact-match keywords to answer user queries. But this method was generally inefficient. To improve the search quality and user experience, they started incorporating large language models (LLMs) into their algorithm. For example, in 2019, Google came up with BERT, which helps the search engine understand user queries better and offer more relevant search results.
But things have completely changed now. Google is losing its market share to AI chatbots like ChatGPT. To compete, Google released their own chatbot—Gemini. These AI chatbots are really good at leveraging user data to provide tailored recommendations, which directly impact how individuals find businesses. Google also released AI Overviews for information retrieval, providing users with the answers to their queries without even clicking on any search results.
All these combined have reduced the organic search traffic by up to 50% for the top three ranking websites. And these numbers could continue to increase with time. But there is still some good news for marketers and businesses: Although the organic search traffic has reduced, it has not completely vanished, and some of it is now coming in the form of referral traffic from AI Overviews and AI chatbots.
Businesses need to adapt to these changes to stay competitive. One such step is changing your SEO approach to go beyond keywords and account for user intent. Since search engines can now understand user intent beyond keywords, they can provide more accurate and contextually relevant results to these voice queries. That's why it's important to optimize your webpages for long-tail conversational keywords.
The next thing you can do is leverage your first-party data, such as customer reviews, behavior, preferences, past purchases, etc. Use this information to make hyper-personalized content for your audience, and implement structured data and FAQ schema into your webpages. Structured data helps search engines understand and categorize content more effectively and increases the chances of appearing in rich results. FAQ schema allows voice assistants to pull direct answers from web pages and, in my experience, can improve overall visibility in voice search queries.
This personalized content, when paired with structured data markup, can not only rank you for long-tail queries to drive organic traffic but also increase your chances of being cited by AI chatbots and AI Overviews.
Users don't always find your business on search engines, so it's important to be present on the platforms where your prospects can find you. These platforms analyze multiple factors before putting your business in front of your potential audience. For instance, Google Maps and Yelp rank businesses based on AI's assessment of your service quality, response times and review scores. Ecommerce platforms like Walmart and Amazon, on the other hand, leverage machine learning to predict and recommend products. An Omnisend survey of U.S. respondents shows that nearly 31% of users like recommendations made by AI, as it speeds up the shopping process.
And these are just a few examples. AI is being used almost everywhere, and that's why a number of businesses are opting for a holistic marketing approach. By being digitally available on all the platforms where their audience is, leveraging reviews and engaging with users, businesses can show they're active and improve their visibility on such platforms.
Business discovery goes beyond traditional text-based searches. Along with voice, image-based and multimodal searches allow users to find businesses in new ways.
For example, there were already platforms like Google Lens, Pinterest Lens and Bing Visual Search that could be used for image-based searches. Now, we have platforms like ChatGPT and Gemini that allow users to combine text, voice and images to refine their queries.
While visual and multimodal searches are not as common today as voice and text-based searches, these are not the concepts of the far future. In my experience, people are already switching to them, and that's why optimizing for these channels can be a worthy investment for businesses.
I've found that the best way to optimize for this type of search is to properly use alt-tags, descriptions, metadata and schema for your visual content. Also, make sure that your business has consistent branding across platforms to make it easy for users and search engines to recognize your brand.
AI isn't changing search to create obstacles; it's refining it to be more intuitive. Instead of just matching keywords, AI is used to understand intent, predict user needs, and deliver value—sometimes before the customer even realizes they need it.
This shift creates opportunities for businesses to build trust and authority across multiple discovery channels. The better AI understands your business, the more it can recognize your expertise and credibility. And the stronger this association, the more frequently AI should surface your brand when potential customers search.
There's no shortcut or algorithm trick. The key is to create valuable, discoverable and AI-friendly content that genuinely helps people—because when your content is useful, AI will distribute it naturally.
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