Can Gen AI-Powered Search Overtake Google?

For the last two decades, Google Search has been the go-to for online inquiries. However, generative AI (gen AI)-powered search, such as OpenAI’s ChatGPT Search and Perplexity.ai, is beginning to challenge Google’s dominance in the market. This has resulted in an evolving search landscape and prompted Google to integrate AI-powered features into search.

As part of a digital marketing and social media strategy course, teams of MBA students from Carnegie Mellon University’s Tepper School of Business examined how generative AI (gen AI)-powered search engines compare to traditional engines like Google Search, shedding new light on the potential disruption gen AI-powered search could bring to the broader online search market. 

Unpacking the Technology: How Gen AI-Powered Search Differs from Google Search

Gen AI-powered search has created a fundamental shift in how search works. Traditional engines deliver a ranked list in response to queries, requiring users to sift through web pages for answers. In contrast, gen AI-powered search engines use algorithms to generate curated, conversational responses, lowering the user’s time and effort.

The twist: gen AI-powered search engines rely on traditional search engines like Google. They use a method called retrieval-augmented generation which queries conventional engines, like Google or Bing, and synthesizes content from top-ranking results into a single response. This dependency creates a paradox: If users migrate to gen AI-powered engines, the quality of traditional engines – which rely on user engagement data to improve – could degrade and impact gen AI results.

MBA Student Experiments: Real-World Insights into User Experience

The Tepper School MBA teams conducted two experiments to compare gen AI and traditional search experiences. One project team asked participants to plan a trip to Spain. Half used Google Search, while the other half used gen AI platforms like ChatGPT, Perplexity.ai, and CoPilot. The findings were striking: gen AI users reported a 17% higher satisfaction rate and achieved their goals faster. Specifically, 88% of gen AI users found what they needed on the first try, compared to 79% of Google users.

Another experiment examined how efficiently users found information such as “best laptops for MBAs” and “top fall vacation spots for students.” Participants using gen AI search completed their tasks in less than half the time. Despite Google’s attempts to integrate AI snippets, most users ignored these features or found them ineffective. 

A closer look at user behavior revealed that gen AI-powered searches are driven by prompts which are often context-rich and detailed, and traditional search queries are simpler and keyword-based. The inherent reliance on keyword-driven queries in traditional search limits performance when used for gen AI-powered queries. 

Will Gen AI Replace Traditional Search? The Answer is Complex

One student team categorized searches into three levels of complexity: simple (factual or navigational), medium (instructional or simple comparisons), and high (complex comparisons or creative queries). Their research showed that users preferred gen AI platforms for more complex queries and traditional search remains the choice for simple tasks. 

These insights suggest that gen AI is unlikely to completely replace traditional search engines. Instead, the future of search may be segmented, with each platform serving different needs.

The Monetization Dilemma: How Will Gen AI Make Money?

Another key focus of the course project was monetization, a challenge that looms large for gen AI-powered search engines as they work toward becoming a viable long-term solution. Gen AI search is more expensive for companies than traditional search and can consume four to five times more energy. This creates a need for gen-AI powered search to become financially sustainable. 

Google’s monetization success comes from an ad-based model where sponsored links generate revenue per click. Gen AI platforms provide direct answers, leaving little room for traditional ad placements. Student teams explored various monetization strategies ranging from sponsored follow-up questions, embedded content, or subscription models. However, these come with risks – if sponsored content disrupts the seamless user experience, platforms could lose users. Further, subscription models may also deter people who are used to free search options.

This research highlighted an age-old dilemma: for gen AI search to be sustainable, any monetization effort must enhance the user experience, not detract from it. The right balance will be crucial for these platforms’ survival and success. 

What Lies Ahead: The Future of Search in a Digital Marketing Context

This research demonstrates that gen AI search is not just a technological upgrade. Instead, it has catalyzed a shift in the behavior, results, and expectations that come with traditional, keyword-based search results. Gen AI will shape the future of search, but the question is how the landscape will evolve as both established and emerging players redefine the rules. As this space evolves, the findings from this project could potentially be a reference point for discussions on what comes next.