The News: On August 2, Google provided some updates to the Google Search Generative Experience, a new program launched in May through testing/sandbox group Search Labs. Google Search Generative Experience was set up to enable a limited number of web developers to leverage Google Generative AI capabilities in search. The project started with three AI overview features: (1) step-by step instruction summaries for complex questions, (2) collective tips to specific questions, and (3) important factors to particular buying decisions. The update introduced three enhancements.
Here are the pertinent details:
- Images and videos are included in more AI overviews. Google says sometimes it is more powerful to understand something by seeing it, so more images and videos will be included in AI overviews.
- Cut time to generate AI overviews in half. Google did not share how long it took to generate the AI overviews originally.
- Publish dates have been added to links. AI overviews are published alongside related links. Now those links will include publish dates to better understand how recent the information is.
Read the full blog post about the Google Search Generative Experience Update on The Keyword blog.
Google Search Generative Experience: Will Gen AI Impact Search?
Analyst Take: There has been a great deal of speculation about how generative AI will impact search, but to date, there have not been any significant breakthroughs. When ChatGPT exploded on the marketplace, Google, a longtime leader in AI research and use, was roundly criticized for its lack of generative AI applications. Was Google asleep at the wheel or does Google know something about Generative AI search the rest of us do not know? The smart money says the company does indeed know what next-generation search will look like. Here are key takeaways related to Google’s strategic moves in generative AI-fueled search:
How much impact will generative AI have on search?
The early visions for generative AI search anticipated that users could ask a question and literally get it answered, or that perhaps large language models (LLMs) could understand queries better and therefore return less-vague results. In theory, users could ask any assistant, be it ChatGPT, Bard, Claude, Bing, etc. a question and those results are “search” results. That utopia has not materialized for a few reasons.
First, LLMs are proving to have issues with accuracy, particularly around hallucinations. They tend to have issues with bias as well. User confidence levels are pretty low, and justifiably so.
Second, the monetization model of search return results does not fit into these “just ask a question and get the answer” frameworks, and the search engine players obviously are not excited about losing the search engine revenue stream.
Which means, the reality of generative AI search looks like what Google SGE and Bing are doling out – Overviews/summaries tied to link results, but importantly using conversational AI to better understand what users are looking for. Importantly, that includes more two-way communication between the search engine and users to help users get what they are looking for.
Will search engines go away and be replaced by the Gen AI assistant?
Perhaps a hybrid. IF (and that is a big if) LLMs become more accurate, hallucinate less and are not biased, and assuming the revenue streams of search remain intact in some form, then anytime, anywhere AI assistants could become the form for search engines instead of a web UI.
Google has the upper hand in next-generation search
The reality in all of this is that Google has the advantage in figuring out what is next in search. They are not asleep at the wheel. Search is the company’s top priority — Google/Alphabet revenue for 2022 was $282 billion, and $162.4 billion of that, or 57.5%, came from search. Google completely dominates search market share. The company is a world-leader in AI innovation and research, and it has been for more than 10 years. The company has all the AI experience, expertise, and resources to figure out how to best do next-generation search, including the data to make it work. In a blog post published on June 26, Eze Vidra of Remagine Ventures said this:
“Like any tech advancement at scale, to succeed in this endeavor requires deep pockets: cloud resources and costly GPUs, expensive AI engineers, and a working business model, all of which Google already has. But more than anything, it requires a huge amount of data, which is perhaps Google’s biggest competitive moat.”
I strongly anticipate that Google will lead the world forward in the AI-driven search space.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
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Author Information
Based in Tampa, Florida, Mark is a veteran market research analyst with 25 years of experience interpreting technology business and holds a Bachelor of Science from the University of Florida.
