Intel CEO Pat Gelsinger speaks while showing silicon wafers during an event called AI Everywhere in New York, Thursday, Dec. 14, 2023.
Seth Wenig | AP
Intel’s long-awaited turnaround looks farther away than ever after the company reported dismal first-quarter earnings. Investors pushed the stock down 10% on Friday to their lowest level of the year.
Although Intel’s revenue is no longer shrinking and the company remains the biggest maker of processors that power PCs and laptops, sales in the first quarter trailed estimates. Intel also gave a soft forecast for the second quarter, suggesting weak demand.
It was a tough showing for CEO Pat Gelsinger, who’s early in his fourth year at the helm.
But Intel’s problems are decades in the making.
Before Gelsinger returned to the company in 2021, the company, once synonymous with “Silicon Valley,” had lost its edge in semiconductor manufacturing to overseas rivals like Taiwan Semiconductor Manufacturing Company. Now, in a high-risk quest, it’s spending billions per quarter to regain ground.
“Job number one was to accelerate our efforts to close the technology gap that was created by over a decade of under-investment,” Gelsinger told investors on Thursday. He said the company is still on track to catch up by 2026.
Investors remain skeptical. Intel is the worst-performing tech stock in the S&P 500 this year, down 37%. Meanwhile, the two best-performing stocks in the index are chipmaker Nvidia and Super Micro Computer, which has been boosted by surging demand for Nvidia-based AI servers.
Gelsinger is betting the company on a risky business model change. Not only will Intel make its own branded processors, but it will act as a factory for other chip companies that outsource their manufacturing — a group of companies that includes Nvidia, Apple, and Qualcomm. Its success acquiring customers will depend on Intel regaining “process leadership,” as the company calls it.
Other semiconductor companies would like an alternative to TSMC so they don’t have to rely on a single supplier. U.S. politicians including President Biden call Intel an American chip champion and say the company is strategically an important part of the U.S. processor supply chain.
“Intel is a big iconic semiconductor company which has been the leader for many years,” said Nicholas Brathwaite, managing partner at Celesta Capital, which invests in semiconductor companies. “And I think it’s a company that is worth trying to save, and they have to come back to competitiveness.”
But the company isn’t doing itself any favors.
“I think everyone has been hearing them say the next quarter will be better for two, three years now,” said Counterpoint analyst Akshara Bassi.
Intel has fumbled the ball for years. It missed the mobile chip boom with the unveiling of the iPhone in 2007. It’s been largely on the sidelines of the artificial intelligence craze while companies like Meta, Microsoft and Google order as many Nvidia chips as they can.
Here’s how Intel ended up where it is today.
Missed out on the iPhone
The late Apple CEO Steve Jobs unveiling the first iPhone in 2007.
David Paul Morris | Getty Images News | Getty Images
The iPhone could have had an Intel chip inside. When Apple developed the first iPhone, then-CEO Steve Jobs visited former Intel CEO Paul Otellini, according to Walter Isaacson’s 2011 biography “Steve Jobs.”
They discussed whether Intel should power the iPhone, which had not been released yet, Jobs and Otellini told Isaacson. When the iPhone was first revealed, it was marketed as a phone that ran the Apple Mac operating system. It would’ve made sense to use Intel chips, which ran on the best desktops at the time, including Apple’s Macs.
Jobs said that Apple passed on Intel’s chips because the company was “slow” and Apple didn’t want the same chips to be sold to its competitors. Otellini said that while the tie-up would have made sense, the two companies couldn’t agree on a price or who owned the intellectual property, according to Isaacson.
The deal never happened. Apple chose Samsung chips when the iPhone launched in 2007. Apple bought PA Semi in 2008 and introduced its first homegrown iPhone chip in 2010.
Within five years, Apple started shipping hundreds of millions of iPhones. Overall smartphone shipments — including Android phones designed to compete with Apple — surpassed PC shipments in 2010.
Nearly every modern smartphone uses an Arm-based chip instead of Intel’s x86 technology which was created for PCs in 1981 and is still in use.
Arm chips built by Apple and Qualcomm consume less power than Intel’s processors, making them more desirable for small devices like phones that run on batteries.
Arm-based chips quickly improved due to the enormous manufacturing volumes and the demands of an industry that needs new chips every year with faster performance and fresh features. Apple started placing huge orders with TSMC to build its iPhone chips, starting with the A8 in 2014. It gave TSMC the cash to upgrade its manufacturing equipment annually and surpass Intel.
By the end of the decade, some benchmarks had the fastest phone processors rivaling Intel’s PC chips for some tasks while consuming far less power. Around 2017, mobile chips from Apple and Qualcomm started adding AI parts to their chips called neural processing units, another advancement over Intel’s PC processors. The first Intel-based laptop with an NPU shipped late last year.
Intel has since lost share in its core PC chip business to chips that grew out of the mobile revolution.
Apple stopped using Intel in its PCs in 2020. Macs now use Arm-based chips based on the ones used in iPhones. Some of the first mainstream Windows laptops with Arm-based chips are coming out later this year. Low-cost laptops running Google ChromeOS are increasingly using Arm, too.
“Intel lost a big chunk of their market share because of Apple, which is about 10% of the market,” Gartner analyst Mikako Kitagawa said.
Intel made efforts to break into smartphones. It released an x86-based mobile chip called Atom that was used in the 2012 Asus Zenphone. But it never sold well and the product line was dead by 2015.
Intel’s mobile stumble set the stage for a lost decade.
All about transistors
US President Joe Biden holds a wafer of chips as he tours the Intel Ocotillo Campus in Chandler, Arizona, on March 20, 2024.
Brendan Smialowski | AFP | Getty Images
Processors get faster with more transistors. Each one allows them to do more calculations. The original Intel microprocessor from 1971, the 4004, had about 2,000 transistors. Now Intel’s chips have billions.
Semiconductor companies fit more transistors on chips by shrinking them. The size of the transistor represents the “process node.” Smaller numbers are better.
The original 4004 used a 10-micrometer process. Now, TSMC’s best chips use a 3-nanometer process. Intel is currently at 7-nanometers. Nanometers are 1,000 times smaller than micrometers.
Engineers, especially at Intel, took pride in regularly delivering smaller transistors. Brathwaite, who worked at Intel in the 1980s, said Intel’s process engineers were the company’s “crown jewels.” People in the technology industry relied on “Moore’s Law,” coined by Intel co-founder Gordon Moore, that said the amount of computing power would double and become cheaper at predictable intervals, roughly every two years.
Moore’s Law meant that Intel’s software partners, like Microsoft, could count on the next generation of PCs or servers being more powerful than the current generation.
The expectation of continuous improvement at Intel was so strong that it even had a nickname: “tick-tock development.” Every two years, Intel would release a chip on a new process (tick) and in the subsequent year, it would refine its design and technology (tock.)
In 2015, under CEO Brian Krzanich, it became clear that Intel’s 10nm process was delayed, and that the company would continue shipping its most important PC and server processors using its 14nm process for longer than the normal two years. The “tick-tock” process had added an extra tock by the time the 14nm chips shipped in 2017. Intel officials today say that the issue was underinvestment, specifically on EUV lithography machines made by ASML, which TSMC enthusiastically embraced.
The delays compounded at Intel. The company missed its deadlines for the next process, 7nm — eventually revealing the issue in a bullet point in the small print in a 2020 earnings release, causing the stock to plunge, and clearing the way for Gelsinger, a former Intel engineer, to take over.
While Intel was struggling to keep its legendary pace, AMD, Intel’s historic rival for server and PC chips, took advantage.
AMD is a “fabless” chip designer. It designs its chips in California, and has TSMC or GlobalFoundries manufacture them. TSMC didn’t have the same issues with 10nm or 7nm, and that meant that AMD’s chips were competitive or better than Intel’s in the latter half of the decade, especially for certain tasks.
AMD, which barely had market share in server CPUs a decade ago, started taking its slice. AMD made over 20% of server CPUs sold in 2022, and shipments grew 62% that year, according to an estimate from CounterPoint Research last year. AMD surpassed Intel’s market cap the same year.
Missing on the AI boom
Nvidia founder and CEO Jensen Huang displays products on stage during the annual Nvidia GTC Conference at the SAP Center in San Jose, California, on March 18, 2024.
Josh Edelson | Afp | Getty Images
Graphics processor units, or GPUs, were originally designed to play sophisticated computer games. But computer scientists knew they were also ideal for running the kind of parallel calculations that AI algorithms require.
The broader business community caught on after OpenAI released ChatGPT in 2022, helping Nvidia triple sales over the past year. Companies are spending money on pricey servers again.
AI-oriented GPU-based servers sometimes pair as many as eight Nvidia GPUs to one Intel CPU. In older servers, the Intel CPU was almost always the most expensive and important part. In a GPU-based server, it’s Nvidia’s chips.
Nvidia recently announced a version of its latest “Blackwell” GPU that cuts Intel out entirely. Two Nvidia B100 GPUs are paired with one Arm-based processor.
Almost all Nvidia GPUs used for AI are made by TSMC in Taiwan, using leading-edge techniques to produce the most advanced chip.
Intel doesn’t have a GPU competitor to Nvidia’s AI accelerators, but it has an AI chip called Gaudi 3. Intel started focusing on AI for servers in 2018 when it bought Habana Labs, whose technology became the basis for the Gaudi chips. The chip is manufactured on a 5nm process, which Intel doesn’t have, so the company relies on an external foundry.
Intel says it expects $500 million in Gaudi 3 sales this year, mostly in the second half. For comparison, AMD expects about $2 billion in annual AI chip revenue. Meanwhile, analysts polled by FactSet expect Nvidia’s data center business — its AI GPUs — to account for $57 billion in sales during the second half of the year.
Still, Intel sees an opportunity and has recently been talking up a different AI story — it could eventually be the American producer of AI chips, maybe even for Nvidia.
The U.S. government is subsidizing a massive Intel fab outside of Columbus, Ohio, as part of $8.5 billion in loans and grants toward U.S. chipmaking. Gelsinger said last month that the plant will offer leading-edge manufacturing when it comes online in 2028, and will make AI chips — perhaps those of Intel’s rivals, Gelsinger said on a call with reporters in March.
Intel’s death march
US President Joe Biden (C) stands behind a table, next to Intel’s CEO Pat Gelsinger (L) as they look at wafers while touring the Intel Ocotillo Campus in Chandler, Arizona, on March 20, 2024.
Brendan Smialowski | AFP | Getty Images
Intel has faced its old failures since Gelsinger took the helm in 2021, and is actively trying to catch up to TSMC through a process that Intel calls “four nodes in five years.”
It hasn’t been easy. Gelsinger referred to its goal to regain leadership as a “death march” in 2022.
Now, the march is starting to reach its destination, and Intel said on Thursday that it’s still on track to catch up by 2026. At that point, TSMC will be shipping 2nm chips. Intel said it will begin producing its “18A” process, equivalent to 2nm, by 2025.
It hasn’t been cheap. Intel reported a $2.5 billion operating loss in its foundry division on $4.4 billion in mostly internal sales. The sums represent the vast investments Intel is making in facilities and tools to make more advanced chips.
“Setup costs are high and that’s why there’s so much cash burn,” said Bassi, the CounterPoint analyst. “Running a foundry is a capital-intensive business. That’s why most of the competitors are fabless, they are more than happy to outsource it to TSMC.”
Intel last month reported a $7 billion operating loss in its foundry in 2023.
“We have a lot of these investments to catch up flowing through the P&L,” Gelsinger told CNBC’s Jon Fortt on Thursday. “But basically, what we expect in ’24 is the trough.”
Not many companies have officially signed up to use Intel’s fabs. Microsoft has said it will use them to manufacture its server chips. Intel says it’s already booked $15 billion in contracts with external companies for the service.
Intel will help its own business and enable better performance in its products if it regains the lead in making the smallest transistors. If that happens, Intel will be back, as Gelsinger is fond of saying.
On Thursday, Gelsinger said demand was high for this year’s forthcoming server chips using Intel 3, or its 3nm process, and that it could win customers who had defected to competitors.
“We’re rebuilding customer trust,” Gelsinger said on Thursday. “They’re looking at us now saying ‘Oh, Intel is back.'”
Elon Musk looks on as U.S. President Donald Trump meets South African President Cyril Ramaphosa in the Oval Office of the White House in Washington, D.C., U.S., May 21, 2025.
Kevin Lamarque | Reuters
The Elon Musk-owned social media platform X experienced a brief outage on Saturday morning, with tens of thousands of users reportedly unable to use the site.
About 25,000 users reported issues with the platform, according to the analytics platform Downdetector, which gathers data from users to monitor issues with various platforms.
Roughly 21,000 users reported issues just after 8:30 a.m. ET, per the analytics platform.
The issues appeared to be largely resolved by around 9:55 a.m., when about 2,000 users were reporting issues with the platform.
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X did not immediately respond to CNBC’s request for comment. Additional information on the outage was not available.
Musk, the billionaire owner of SpaceX and Tesla, acquired X, formerly known as Twitter in 2022.
The site has had a number of widespread outages since the acquisition.
Artificial intelligence robot looking at futuristic digital data display.
Yuichiro Chino | Moment | Getty Images
Businesses are turning to artificial intelligence tools to help them navigate real-world turbulence in global trade.
Several tech firms told CNBC say they’re deploying the nascent technology to visualize businesses’ global supply chains — from the materials that are used to form products, to where those goods are being shipped from — and understand how they’re affected by U.S. President Donald Trump’s reciprocal tariffs.
Last week, Salesforce said it had developed a new import specialist AI agent that can “instantly process changes for all 20,000 product categories in the U.S. customs system and then take action on them” as needed, to help navigate changes to tariff systems.
Engineers at the U.S. software giant used the Harmonized Tariff Schedule, a 4,400-page document of tariffs on goods imported to the U.S., to inform answers generated by the agent.
“The sheer pace and complexity of global tariff changes make it nearly impossible for most businesses to keep up manually,” Eric Loeb, executive vice president of government affairs at Salesforce, told CNBC. “In the past, companies might have relied on small teams of in-house experts to keep pace.”
Firms say that AI systems are enabling them to take decisions on adjustments to their global supply chains much faster.
Andrew Bell, chief product officer of supply chain management software firm Kinaxis, said that manufacturers and distributors looking to inform their response to tariffs are using his firm’s machine learning technology to assess their products and the materials that go into them, as well as external signals like news articles and macroeconomic data.
“With that information, we can start doing some of those simulations of, here is a particular part that is in your build material that has a significant tariff. If you switched to using this other part instead, what would the impact be overall?” Bell told CNBC.
‘AI’s moment to shine’
Trump’s tariffs list — which covers dozens of countries — has forced companies to rethink their supply chains and pricing, with the likes of Walmart and Nikealready raising prices on some products. The U.S. imported about $3.3 trillion of goods in 2024, according to census data.
Uncertainty from the U.S. tariff measures “actually probably presents AI’s moment to shine,” Zack Kass, a futurist and former head of OpenAI’s go-to-market strategy, told CNBC’s Silvia Amaro at the Ambrosetti Forum in Italy last month.
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“If you wonder how hard things could get without AI vis-a-vis automation, and what would happen in a world where you can’t just employ a bunch of people overnight, AI presents this alternative proposal,” he added.
Nagendra Bandaru, managing partner and global head of technology services at Indian IT giant Wipro, said clients are using the company’s agentic AI solutions “to pivot supplier strategies, adjust trade lanes, and manage duty exposure dynamically as policy landscapes evolve.”
Wipro says it uses a range of AI systems — both proprietary and supplied by third parties — from large language models to traditional machine learning and computer vision techniques to inspect physical assets in cross-border transit.
‘Not a silver bullet’
While it preferred to keep company names confidential, Wipro said that firms using its AI products to navigate Trump’s tariffs range from a Fortune 500 electronics manufacturer with factories in Asia to an automotive parts supplier exporting to Europe and North America.
“AI is a powerful enabler — but not a silver bullet,” Bandaru told CNBC. “It doesn’t replace trade policy strategy, it enhances it by transforming global trade from a reactive challenge into a proactive, data-driven advantage.”
AI was already a key investment priority for global firms prior to Trump’s sweeping tariff announcements on April. Nearly three-quarters of business leaders ranked AI and generative AI in their top three technologies for investment in 2025, according to a report by Capgemini published in January.
“There are a number of ways AI can assist companies dealing with the tariffs and resulting uncertainty. But any AI solution’s success will be predicated on the quality of the data it has access to,” Ajay Agarwal, partner at Bain Capital Ventures, told CNBC.
The venture capitalist said that one of his portfolio companies, FourKites, uses supply chain network data with AI to help firms understand the logistics impacts of adjusting suppliers due to tariffs.
“They are working with a number of Fortune 500 companies to leverage their agents for freight and ocean to provide this level of visibility and intelligence,” Agarwal said.
“Switching suppliers may reduce tariffs costs, but might increase lead times and transportation costs,” he added. “In addition, the volatility of the tariffs [has] severely impacted the rates and capacity available in both the ocean and the domestic freight networks.”
A Zoox autonomous robotaxi in San Francisco, California, US, on Wednesday, Dec. 4, 2024.
David Paul Morris | Bloomberg | Getty Images
Amazon‘s Zoox robotaxi unit issued a voluntary recall of its software for the second time in a month following a recent crash in San Francisco.
On May 8, an unoccupied Zoox robotaxi was turning at low speed when it was struck by an electric scooter rider after braking to yield at an intersection. The person on the scooter declined medical attention after sustaining minor injuries as a result of the collision, Zoox said.
“The Zoox vehicle was stopped at the time of contact,” the company said in a blog post. “The e-scooterist fell to the ground directly next to the vehicle. The robotaxi then began to move and stopped after completing the turn, but did not make further contact with the e-scooterist.”
Zoox said it submitted a voluntary software recall report to the National Highway Traffic Safety Administration on Thursday.
A Zoox spokesperson said the notice should be published on the NHTSA website early next week. The recall affected 270 vehicles, the spokesperson said.
The NHTSA said in a statement it had received the recall notice and that the agency “advises road users to be cautious in the vicinity of vehicles because drivers may incorrectly predict the travel path of a cyclist or scooter rider or come to an unexpected stop.”
If an autonomous vehicle continues to move after contact with any nearby vulnerable road user, it risks causing harm or further harm. In the AV industry, General Motors-backed Cruise exited the robotaxi business after a collision in which one of its vehicles injured a pedestrian who had been struck by a human-driven car and was then rolled over by the Cruise AV.
Zoox’s May incident comes roughly two weeks after the company announced a separate voluntary software recall following a recent Las Vegas crash. In that incident, an unoccupied Zoox robotaxi collided with a passenger vehicle, resulting in minor damage to both vehicles.
The company issued a software recall for 270 of its robotaxis in order to address a defect with its automated driving system that could cause it to inaccurately predict the movement of another car, increasing the “risk of a crash.”
Amazon acquired Zoox in 2020 for more than $1 billion, announcing at the time that the deal would help bring the self-driving technology company’s “vision for autonomous ride-hailing to reality.”
While Zoox is in a testing and development stage with its AVs on public roads in the U.S., Alphabet’s Waymo is already operating commercial, driverless ride-hailing services in Phoenix, San Francisco, Los Angeles and Austin, Texas, and is ramping up in Atlanta.
Teslais promising it will launch its long-delayed robotaxis in Austin next month, and, if all goes well, plans to expand after that to San Francisco, Los Angeles and San Antonio, Texas.