Google’s new A.I. search could squeeze traffic to web sites, publishers worry
On Wednesday, Google previewed what could be one of the largest changes to the search engine in its history.
Google will use AI models to combine and summarize information from around the web in response to search queries, a product it calls Search Generative Experience.
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Instead of “ten blue links,” the phrase that describes Google’s usual search results, Google will show some users paragraphs of AI-generated text and a handful of links at the top of the results page.
The new AI-based search is being tested now for a select group of users and isn’t widely available yet. But website publishers are already worried that if it becomes Google’s default way of presenting search results, it could hurt them by sending fewer visitors to their sites and keeping them on Google.com.
The controversy highlights a long-running tension between Google and the websites it indexes, with a new artificial intelligence twist. Publishers have long worried that Google repurposes their verbatim content in snippets on its own website, but now Google is using advanced machine learning models that scrape large parts of the web to “train” the software to spit out human-like text and responses.
Rutledge Daugette, CEO of TechRaptor, a site focusing on gaming news and reviews, said that Google’s move was made without considering the interests of publishers and Google’s AI amounts to lifting content.
“Their focus is on zero-click searches that use information from publishers and writers who spend time and effort creating quality content, without offering any benefit other than the potential of a click,” Rutledge told CNBC. “Thus far, AI has been quick to reuse others’ information with zero benefit to them, and in cases like Google Bard doesn’t even offer attribution as to where the information it’s using came from.”
Luther Lowe, a longtime Google critic and chief of public policy at Yelp, said that Google’s update is part of a decades-long strategy to keep users on the site for longer, instead of sending them to the sites that originally hosted the information.
“The exclusionary self-preferencing of Google’s ChatGPT clone into search is the final chapter of bloodletting the web,” Lowe told CNBC.
According to SearchEngineLand, a news website that closely tracks changes to Google’s search engine, the AI-generated results are displayed above the organic search results in testing so far.
SGE comes in a differently colored box — green in the example — and includes boxed links to three websites on the right side. In Google’s primary example, all three of the website headlines were cut off.
Google says that the information isn’t taken from the websites, but is instead corroborated by the links. SearchEngineLand said the SGE approach was an improvement and a “healthier” way to link than Google’s Bard chatbot, which rarely linked to publisher websites.
Some publishers are wondering if they can prevent AI firms such as Google from scraping their content to train their models. Companies such as the firm behind Stable Diffusion are already facing lawsuits from data owners, but the right to scrape web data for AI remains an undecided frontier. Other companies, such as Reddit, have announced plans to charge for access to their data.
Leading the charge in the publishing world is Barry Diller, Chairman of IAC, which owns websites including All Recipes, People Magazine and The Daily Beast.
“If all the world’s information is able to be sucked up into this maw, and then essentially repackaged in declarative sentences, in what’s called chat, but it isn’t chat — as many grafs as you want, 25 on any subject — there will be no publishing, because it will be impossible,” Diller said last month at a conference.
“What you have to do is get the industry to say that you cannot scrape our content, until you work out systems where the publisher gets some avenue towards payment,” Diller continued, saying that Google will face this problem.
Diller says he believes publishers can sue AI firms under copyright law and that current “fair use” restrictions need to be redefined. The Financial Times reported on Wednesday that Diller is leading a group of publishers “that is going to say we are going to change copyright law if necessary.” An IAC spokesperson declined to make Diller available for an interview.
One challenge facing publishers is confirming that their content is being used by an AI. Google did not reveal training sources for its large language model that underpins SGE, PaLM 2, and Daugette says while he’s seen examples of quotes and review scores from competitors repurposed on Bard without attribution, it’s hard to tell when the information is from his site without directly linked sources.
Google didn’t respond to a request for comment. “PaLM 2 is trained on a wide range of openly available data on the internet and we obviously value the health of the web ecosystem. And that’s really part of the way we think about how we build our products, to ensure that we have a healthy ecosystem where creators are a part of that thriving ecosystem,” Google VP of Research Zoubin Ghahramani said in a media briefing earlier this week.
Daugette says that Google’s moves make being an independent publisher tough.
“I think it’s really frustrating for our industry to have to worry about our hard work being taken, when so many colleagues are being laid off,” Daugette said. “It’s just not okay.”
CNBC’s Jordan Novet contributed reporting.
Jensen Huang, co-founder and chief executive officer of Nvidia Corp., left, and Masayoshi Son, chairman and chief executive officer of SoftBank Group Corp., during a fireside chat at the Nvidia AI Summit Japan in Tokyo, Japan, on Wednesday, Nov. 13, 2024.
Akio Kon | Bloomberg | Getty Images
SoftBank is selling its entire stake in Nvidia — but not for the reasons you might think.
In its earnings statement released Tuesday, the Japanese group said that it had sold 32.1 million Nvidia shares in October for $5.83 billion.
At first blush, this could be read as a sign that Nvidia’s high valuations are causing SoftBank some unease. And if SoftBank — which infamously pumped $18.5 billion into WeWork only to value it at $2.9 billion eventually — is tamping down on its usual optimism regarding its investments, then retail traders should probably pay attention.
Adding to such worries are comments by Michael Burry — who bet against subprime mortgages before they caused a whole financial crisis in 2008 — on major artificial intelligence companies.
Burry wrote Monday in a post on X that those firms are “understating depreciation” of AI chips, which “artificially boosts earnings — one of the more common frauds of the modern era.” CNBC could not independently confirm that companies were practicing this.
This doesn’t seem to be SoftBank’s concern, however. A person familiar with the group’s sale told CNBC that it had nothing to do with AI valuations. On the contrary, cash from offloading Nvidia chips will be redirected to SoftBank’s $22.5 billion investment in OpenAI, the person said.
Burry said in his post that he will reveal “more details” on Nov. 25, and exhorted readers to “stay tuned.” That might not be enough enticement for SoftBank CEO Masayoshi Son.
— CNBC’s Yun Li, April Roach and Dylan Butts contributed to this report.
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Lisa Su, chair and chief executive officer of Advanced Micro Devices Inc. (AMD), during a Bloomberg Television interview in San Francisco, California, US, on Monday, Oct. 6, 2025.
David Paul Morris | Bloomberg | Getty Images
AMD CEO Lisa Su said on Tuesday that the company’s overall revenue growth would expand to about 35% per year over the next three to five years, driven by “insatiable” demand for artificial intelligence chips.
Su said that much of that would be captured by the company’s AI data center business, which it expects to grow at about 80% per year over the same time period, on track to hit tens of billions of dollars of sales by 2027.
“This is what we see as our potential given the customer traction, both with the announced customers, as well as customers that are currently working very closely with us,” Su told analysts.
Ultimately, Su said that AMD could be able to achieve “double-digit” share in the data center AI chip market over the next three to five years.
AMD shares fell 3% in extended trading.
The AI chip market is currently dominated by Nvidia, which has over 90% of the market share, according to some estimates, and which has given the company a market cap of over $4.6 trillion, versus AMD’s roughly $387 billion valuation.
AMD is holding its first financial analyst day since 2022, as the company has found itself at the center of a boom in data center spending for AI.
While companies are spending hundreds of billions of dollars in total on graphics processing unit (GPU) chips to build and power artificial intelligence applications like OpenAI’s ChatGPT, they are also looking for alternatives to increase capacity and control costs. AMD is the only other major developer of GPUs aside from Nvidia.
In October, AMD announced a partnership with OpenAI in which it would sell the AI startup billions of dollars in its Instinct AI chips over multiple years, starting with enough chips in 2026 to use 1 gigawatt of power.
As part of the deal, OpenAI could end up taking a 10% stake in the chipmaker. Su also highlighted long-term deals with Oracle and Meta on Tuesday.
AMD shares have nearly doubled so far in 2025.
OpenAI is also helping AMD set up its next-generation systems based around its Instinct MI400X AI chips, which ship next year.
AMD has said that its chips will be able to be assembled into a “rack-scale” system where 72 of its chips work together as one, which is essential for running the largest AI models.
If AMD succeeds at its rack, it will catch up with Nvidia’s AI chips, which have been offered in rack-scale systems for three product generations.
Su said that the company now sees the total market for AI data center parts and systems hitting $1 trillion per year in 2030, representing 40% annual growth per year. AMD reported $5 billion in AI chip sales in its fiscal 2024.
That’s up from the company’s previous forecast of a $500 billion market in 2028 for AI chips. But the updated AMD figure also includes central processors (CPU), an important kind of chip that sits at the heart of a computer, but isn’t a pure AI accelerator like the GPUs made by Nvidia and AMD.
AMD’s Epyc CPUs are still the company’s most important product by sales. It primarily competes with Intel and some smaller Arm-based processors in the CPU market. AMD also makes chips for game consoles, networking parts, and other devices.
On Tuesday, although AMD focused much of its focus on its growing AI business, it told shareholders that its older businesses were growing too.
“The other message that we want to leave you with today is every other part of our business is firing on all cylinders, and that’s actually a very nice place to be,” Su said.
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