India wants to become a global chip major, but the odds are steep: competition is fierce, and India is a late entrant in the race to make the most advanced chips.

In 2022, when the U.S. restricted exports of its advanced AI chips to China to curb Beijing’s access to cutting-edge technology, a global race for semiconductor self-reliance began.

For India, it offered an opportunity: the country wants to reduce dependence on imports, secure chips for strategic sectors, and capture a bigger share of the global electronics market shifting away from China.

India is one of the world’s largest consumers of electronics, but it has no local chip industry and plays a minimal role in the global supply chain. New Delhi’s “Semiconductor Mission” aims to change that.

The ambition is bold. It wants to create a full supply chain — from design to fabrication, testing and packaging — on Indian soil.

As of this month, the country has approved 10 semiconductor projects with total investment of 1.6 trillion rupees ($18.2 billion). These include two semiconductor fabrication plants, and multiple testing and packing factories.

India also has a pool of engineering talent that is already employed by global chip design companies.

Yet progress so far has been uneven, and neither the investments nor talent pool is enough to make India’s chip ambitions a reality, say experts.

“India needs more than a few fabs or ATP facilities (i.e., more than a few “shiny objects.”) It needs a dynamic and deep and long-term ecosystem,” said Stephen Ezell, vice president for global innovation policy at the Information Technology and Innovation Foundation, a science and technology policy think tank.

Ezell says that leading semiconductor manufacturers consider “as many as 500 discrete factors” before they set up multi-billion-dollar fab investments. These include talent, tax, trade, technology policies, labor rates and laws and customs policies — all areas where India has work to do.

The unit will make chips for power management integrated circuits, display drivers, microcontrollers and high-performance computing logic, Tata Electronics said, which can be used in AI, automotive, computing and data storage industries.

The U.K.’s Clas-SiC Wafer Fab has also tied up with India’s SiCSem to set up the country’s first commercial compound fab in the eastern state of Odisha.

These compound semiconductors can be used in missiles, defence equipment, electric vehicles, consumer appliances and solar power inverters, according to a government press release.

“The coming 3-4 years is pivotal for advancing India’s semiconductor goals,” said Sujay Shetty, managing director of semiconductor at PwC India.

Establishing operational silicon fabrication facilities and overcoming technical and infrastructural hurdles that extend beyond incentives will be a key milestone, according to Shetty.

These 2nm chips offer better performance and power efficiency due to their smaller transistor size. Taiwan Semiconductor Manufacturing Corporation will start mass-producing cutting-edge 2nm chips later this year, according to an FT report.

Last week, Indian minister Ashwini Vaishnaw, who was in Bengaluru to inaugurate a new office of semiconductor design firm ARM, said the British company will design the “most advanced chips used in AI servers, drones, mobile phone chips of 2 nm” from the south Indian city.

But experts say the role of local talent is likely to be limited to non-core design testing and validation, as the core intellectual property for chip designs is often held in locations like the U.S. or Singapore, where established IP regimes support such activities.

“India has sufficient talent in design space, because unlike semiconductor manufacturing and testing that has come up in the last 2 years, design has been there since 1990s,” said Jayanth BR, a recruiter with over 15 years of experience in hiring for global semiconductor companies in India.

He said global companies usually outsource “block-level” design validation work to India.

Going beyond this is something India’s government will need to solve if it wants to fulfil its semiconductor ambitions.

“India may consider updating its IP laws to address new forms of IP, like digital content and software. Of course, improving enforcement mechanisms will go a long way in protecting IP rights,” says Sajai Singh, a partner at Mumbai-based JSA Advocates & Solicitors.

“Our competition is with countries like the U.S., Europe, and Taiwan, which not only have strong IP laws, but also a more established ecosystem for chip design.”

Nvidia CEO Jensen Huang and OpenAI CEO Sam Altman on Monday commented on President Donald Trump’s decision to increase the cost of hiring overseas workers on visas.

Trump on Friday announced that he would raise the fee for an H-1B visa to $100,000, leaving companies scrambling. Employers now must have documentation of the payment prior to filing an H-1B petition on behalf of a worker. Applicants will have their petitions restricted for 12 months until the payment is made, according to the White House.

Huang and Altman responded to the changes in an interview with CNBC’s Jon Fortt, where the two executives announced that Nvidia will invest $100 billion in OpenAI as the artificial intelligence lab sets out to build hundreds of billions of dollars-worth of data centers based around the chipmaker’s AI processors.

“We want all the brightest minds to come to the U.S. and remember immigration is the foundation of the American Dream,” Huang said Monday. “We represent the American Dream. And so I think immigration is really important to our company and is really important to our nation’s future, and I’m glad to see President Trump making the moves he’s making.”

OpenAI CEO Sam Altman also expressed a positive outlook on Trump’s changes.

“We need to get the smartest people in the country, and streamlining that process and also sort of outlining financial incentives seems good to me,” Altman said.

The new $100,000 fee would be a seismic shift for U.S. technology and finance sectors, which rely on the H-1B program for highly skilled immigrants, particularly from India and China. Those two countries accounted for 71% and 11.7% of visa holders last year, respectively.

Those who already have H-1B visas and are located outside the U.S. will not be required to pay the fee in order to re-enter. Many employers use H-1B workers to fill the gaps in these highly technical roles that are not found within the American labor supply. 

— CNBC tech reporter Annie Palmer contributed to this report.

WATCH: Watch CNBC’s full interview with Nvidia CEO Jensen Huang and OpenAI leaders Sam Altman and Greg Brockman

Nvidia will invest $100 billion in OpenAI as the artificial intelligence lab sets out to build hundreds of billions of dollars in data centers based around the chipmaker’s AI processors, the companies said on Monday.

OpenAI plans to build and deploy Nvidia systems that require 10 gigawatts of power, the companies said on Monday. A gigawatt is a measure of power that is increasingly being used to describe the biggest clusters of AI chips.

Nvidia CEO Jensen Huang told CNBC’s Jon Fortt in an interview in San Jose, California, that the 10 gigawatts is equal to between 4 million and 5 million graphics processing units (GPUs), which is what the company will ship in total this year and “twice as much as last year.”

“This is a giant project,” Huang said in the interview, alongside OpenAI CEO Sam Altman and Greg Brockman, the company’s president.

Nvidia’s first investment of $10 billion will be deployed when the first gigawatt is completed, according to a person familiar with the matter. Investments will be made at then-current valuations, said the person, who declined to be named because the details are private.

Nvidia stock rose almost 4% during on Monday, instantly adding roughly $170 billion in value to the company’s market cap, which now sits close to $4.5 trillion.

The partnership, which Huang described as “monumental in size,” highlights the intimate link between OpenAI and Nvidia, two of the biggest drivers of the recent AI boom. Demand for Nvidia’s GPUs started picking up when OpenAI first released ChatGPT in 2022, and OpenAI still relies GPUs to develop its software and deploy it to users.

“Nvidia invests $100 billion in OpenAI, which then OpenAI turns back and gives it back to Nvidia,” Bryn Talkington, managing partner at Requisite Capital Management, told CNBC after the announcement. “I feel like this is going to be very virtuous for Jensen.”

It further signals the magnitude of Nvidia technology that OpenAI will need to develop next-generation AI that can do more than its current models. OpenAI was already in need of an increasing number of chips to serve its users. The company said it had 700 million active weekly users.

“You should expect a lot from us in the coming months,” Altman said in the interview. “There are three things that OpenAI has to do well: we have to do great AI research, we have to make these products people want to use, and we have to figure out how to do this unprecedented infrastructure challenge.”

The companies said the investment will be deployed “progressively” as the infrastructure is built and that Nvidia would be a “preferred” supplier for OpenAI for chips and networking gear. Nvidia dominates the market for AI chips, but faces increased competition from Advanced Micro Devices and cloud providers which are developing their own chips and systems to tie them together.

In August, Huang told investors on an earnings call that building one gigawatt of data center capacity costs between $50 billion and $60 billion, of which about $35 billion of that is for Nvidia chips and systems.

Nvidia and OpenAI said that the first phase of the latest investment will come online in the second half of 2026, using Nvidia’s next-generation Vera Rubin systems.

Nvidia’s investment comes after a roster of investors valued OpenAI at $500 billion in a recent secondary round. Microsoft was one of OpenAI’s early investors, and has a strategic partnership to integrate OpenAI models into its cloud service, Azure, and Microsoft Office. Other OpenAI investors include SoftBank and Thrive Capital.

The companies said on Monday that the partnership will compliment the infrastructure work it is doing with Microsoft, Oracle, SoftBank and the Stargate project.

Altman referred to Nvidia and Microsoft as “passive” investors and two of the company’s “most critical partners” in the CNBC interview.

Huang said Nvidia’s investment is “additive to everything that’s been announced and contracted.” He indicated to CNBC that it’s in addition to anything the company has told Wall Street about its financial expectations.

While this investment dwarfs Nvidia’s prior commitments, the chipmaker has been opening its wallet of late to put funds in many companies in and around the industry.

Last week, Nvidia said it’s taken a $5 billion stake in Intel and announced that the two companies will collaborate on AI processors. Nvidia also said it invested close to $700 million in U.K. data center startup Nscale. And CNBC reported on Thursday that the company spent over $900 million to hire Enfabrica CEO Rochan Sankar and other employees at the AI startup, and to license the company’s technology.

WATCH: Nvidia-OpenAI partnership theme seems to be shortage of compute