Is AI the Future of Search? Here’s Why I’m Sticking with Google (for now)

Unpopular opinion: I’d still revert to Google’s 2023 version despite the adoption of AI and growing ChatGPT usage (and other LLMs).

1. Google is still the best Yellow Pages out there. I don’t care that ChatGPT searches are way up. People looking for tutorials and DIY is one thing; looking for commercial and transactional terms is what Google suppliers are all about (services, product, partners, anything).

2. Google SERP has no competition. Gemini is good in certain things, but so are Claude, or Grok, or ChatGPT, or DeepSeek.

And the Search landscape includes Google News, Discover, Shopping, and other questionable tangible features like their booking platform. Still, that used to work for the most part – to a certain extent.

3. Google Ads would perform significantly better in traditional SERP vs. a prompt interface. The chat UI is well-positioned for raw text/analysis/code/generation. Stuffing tons of links won’t be as efficient.

4. Google Display will die if users don’t visit websites. Keeping SERP will keep this alive (from AdSense to DFP to any other flavor).

5. AI Overviews are only as good as the data fed to the search engines. Providing no benefits to content providers will result in noise and lack of new, original, creative content in the future.

6. Gemini or the AI mode can co-exist in parallel as standalone products. Doesn’t mean that traditional search should disappear.

7. I don’t trust any research derived by AI right now. Other than hallucinations, sifting through data has tons of nuances: brand authority, EAT, trust and reputation of individuals and brands, reliability with their narrative (think left/right, liberal/conservative, corporate/startup). The way research is done in Google is different than any chat-driven summary search.

8. Summarizing and synthesizing content is often off. Simple example – looking for comfortable shoes (I did that for an injury last month). Chatbots are trying to figure out what the core assignment is and fail consistently. Runners and crossfitters write comprehensive reviews based on a myriad of factors, tested in practice, and summarized based on context. An aggregated search pulling mixed data from random sources delivers poor results.

9. Data freshness is a problem with AI. Searching in Google for “last 7 days” or “last month” delivers specific results that are more relevant in different cases.

10. Brand analysis and due diligence. Would you trust a chatbot to run competitive research or analyze a business you want to acquire or invest in? Plenty of reasons to dive into sites, press releases, case studies, partner stories, G2, TrustPilot, Google Business, social accounts, and run the analysis yourself – something that chatbots selectively do.