Artificial intelligence (AI) is undeniably reshaping search experiences, yet its complexity and rapid evolution make it challenging to grasp how these advancements directly improve business outcomes and search experiences. Part 1 of this article explored crucial aspects of AI’s expanding role in modern search experiences. In this follow-up piece, we’ll dive into how AI transforms search from basic queries into natural, extended conversations.
The impact of generative AI on search experiences
In just a year, ChatGPT has significantly impacted the search world. Today, consumers expect search engines to comprehend their queries in conversational language, understand their preferences, offer alternatives, and even engage in follow-up interactions. Businesses not embracing this conversational search trend will be at a distinct competitive disadvantage.
This next generation of conversational search will require new interactions between two relatively recent AI innovations: mainstream generative models and semantic vector search engines. In a typical conversational search application, semantic vector search provides the generative model with the information and context to interpret user intent, produce relevant responses in natural language, and ask insightful follow-up questions, guiding users to their desired outcomes. In other words, the semantic vector engine provides essential information — facts, context, and meaning — for the generative model to craft a natural, conversational experience.
Advanced conversational search is still in its early stages. But generative AI continues to build momentum and shift shoppers’ search experiences — and expectations. This evolution highlights the urgent need to merge semantic vector search, generative AI models, and other related technologies into practical and business-ready search solutions.
The importance of context and situational awareness in conversational search experiences
Human conversations are inherently unpredictable and complex, marked by unpredictable topic shifts, non-sequiturs, interrelated questions, and a contextual comprehension of the broader discussion. So how do you recreate that dynamic (or at least come close) in a search experience?
It’s an important question because people bring different roles and contexts to every search experience. Consider a shopper seeking specific apparel online – the context, be it for work, a vacation, a special occasion, or as a gift, profoundly impacts their search. Without that context, it’s much more difficult for a conversational search engine to return accurate and relevant results. Leveraging AI to decipher contextual cues around searches empowers data scientists and engineers to transform the search process into an authentic conversation mirroring an interaction with a real person.
Of course, that’s much easier said than done. Data scientists are exploring various techniques to determine context and add situational awareness to search experiences. This includes monitoring search sequences within specific timeframes to identify contextual clues — and then carrying over the relevant contextual information from one related query to another. A related technique involves comparing multi-query search sequences to similar sequences to predict the desired outcome and generate more accurate results.
The science used to accurately determine the context behind multiple queries in conversational search experiences is extremely complex. But building context into search experiences is a major focus for AI developers because it is an essential component of conversational search.
Choose a search partner that embraces the latest search science
Modern search experiences depend on complex AI science. Lucidworks is prepared to guide you through the implications of these cutting-edge advancements on your search encounters. Our Lucidworks AI solutions are designed to translate the latest search science and technology into improved experiences and tangible advantages for your business.
This article consists of two parts. Explore part 1 to dive into the critical and expanding role of AI in modern search experiences.
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