AI Search from Google: Will it Help or Hurt Web Traffic?

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Blink, and you’ll miss it.

That’s the era we’re living in these days, where many people feel like it’s easier to miss technological advancements than it is to keep up with the pace. Startups and big players alike are eager to grab a piece of the proverbial pie, racing to innovate and accelerating the adoption of AIWhat is AI? Artificial Intelligence (AI) refers to the simulation of human intelligence processes by computers in an aim to mimic or exceed human cognitive abilities across a range of domains.... tools.

Not one to be left in the shadows, Google arrived on the scene in early 2023 hoping to make up for ‘lost time’ by launching Bard, a competitor to OpenAI’s ChatGPT. Bard is Google’s AI chatbot, promising to help generate content, write code, answer math problems, support users in brainstorming ideas, and more. Initially available on a waitlist in March 2023, Bard is now openly available to anyone who wants to use the chatbot.

Since Bard pulls information from the web, conversations have been raised about the trajectory of this and other GPT models: what will this mean for search? Will browsers have staying power? How will this change the way we access information? And, how will this change the aims of content publishers when it comes to SEO and rankings?

It didn’t take long for another announcement to arrive on the Google stage, perhaps bringing more questions than answers for web publishers.

Search Generative Experience (SGE)

In May, Google announced the next phase of AI: search generative experience (SGE). With this generative AIWhat is Generative AI Generative AI is a subset of artificial intelligence that focuses on creating new content. Unlike traditional AI, which typically analyzes or classifies existing data, generative AI... experience, Google offers what they consider a more complete and helpful method of returning search results. When a user queries, the SGE will provide an AI-powered snapshot, and offer suggested follow-up questions to gain even more information.

SGE responses are generated by a large language model (LLM) trained on a massive dataset of text and code. This allows the model to understand the nuances of human language and generate responses that are accurate and relevant to the user’s query.

Users will interact with SGE similarly to how they interact with traditional search results. When performing a search, end users will not only see a generative AI response but will also see the traditional search results. Users can then click on the AI response to view more details.

SGE is still under development, but Google has ambitions to revolutionize the way users search for and access information. By generating more comprehensive and informative search results, SGE can help users find the information they need more quickly and easily.

The user experience on SGE may look something like this:

• A user searches for “how to make a cake.” SGE generates a response with a step-by-step recipe and helpful tips and tricks.
• A user searches for “the history of the United States.” SGE generates a response that includes a brief overview of American history and links to more detailed resources.
• A user searches for “the best restaurants in New York City.” SGE generates a response with a list of highly-rated restaurants, complete with reviews and photos.

By generating more comprehensive and informative search results, SGE promises to help users to find the information they need more quickly and easily.

Concerns from Site Publishers

Of course, with the fanfare comes some trepidation, particularly from website publishers and SEO experts. SGE replaces Google’s famous ten blue links – a phrase referring to the search results displayed on the first page when a user performs a query – in favor of a new format.

Naturally, website publishers have their concerns. Not only does SGE eliminate the display of links with site previews, prompting users to click to find more of the information they’re looking for, but it also provides more rich information in the results themselves without the need to navigate elsewhere. While that may offer more to the end-user experience, site publishers worry that this will dramatically decrease page traffic and keep users on Google.com instead.

SGE adds a new layer of tension to the AI discussion, as site publishers have already voiced concerns about the origin of content provided by the Bard chatbot. LLMs are “trained” on previously created content and use this information to provide answers to users. While large datasets can inform responses, writers, in particular, have worried about the fruits of their labor – the content they create – being provided verbatim in other contexts and the impacts of plagiarism.

The Waiting Game

These tremors in the tech and content space can easily create a divide, particularly as content creators lose trust and faith in sites like Google. Understanding the Google algorithm has been foundational to content strategies for many years as organizations shape their content and user experience to find favor in search results. Naturally, as Google’s AI-infused search evolution marches on, publishers wait anxiously to see how things play out.

In this waiting game, publishers and users alike look toward the horizon; a blend of hopes and uncertainties (and a touch of doomer concern) are at the forefront of many people’s minds. The internet has offered boundless opportunities in the past few decades. What will AI offer in the decades to come?

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