In 2014, Advanced Micro Devices (AMD) was teetering on the edge of bankruptcy. Its stock had plummeted to just $3 per share, and the company was drowning in debt.
Today, under the leadership of CEO Lisa Su, AMD’s stock has surged to over $94 per share, and its market capitalization has soared past $275 billion, surpassing long-time rival Intel.
As of 2024, Lisa Su’s net worth is estimated at approximately $1.1 billion, according to Forbes and Bloomberg.
Su’s transformation of AMD from a struggling chipmaker into a semiconductor powerhouse has not only revived the company, but also made her one of the wealthiest CEOs in the world.
The majority of her wealth stems from her ownership of around 4 million AMD shares, which represents just 0.2% of the company.
The rest of her fortune is made up from the AMD shares she sold in 2016, earning her nearly $400 million.
Born in Tainan, Taiwan, and raised in New York City from the age of three, Su was encouraged by her parents to pursue math and science from a young age.
Her parents gave her three career choices: concert pianist, doctor, or engineer.
She chose engineering, mainly because she disliked the sight of blood and felt she lacked the talent for piano.
“I just had a great curiosity about how things worked,” Su said in an interview with SFG.
She went on to attend the Massachusetts Institute of Technology (MIT), where she earned three degrees in electrical engineering.
“Electrical engineering, particularly at MIT, was the hardest major, so I said, ‘You know, how about we try that and see how it goes,’” she told the publication.
It was at MIT that Su discovered her passion for semiconductors, often spending long hours in labs tinkering with hardware.
After graduation, she held engineering and leadership roles at IBM, Texas Instruments, and Freescale Semiconductor.
Su joined AMD in 2012 as Senior Vice President and General Manager at a time when Intel dominated the PC processor market.
At the time, 90% of AMD’s revenue came from PC-related products.
By the end of 2014, that figure had dropped to around 40%, thanks to Su’s efforts to diversify the company’s product offerings.
Just two years after joining, she was promoted to president and CEO in 2014.
Upon taking the helm, Su committed to making “the right technology investments” while accelerating innovation across AMD’s portfolio.
Su shifted AMD’s focus to high-performance computing, spearheading the development of the Ryzen and EPYC processor lines.
Ryzen CPUs disrupted Intel’s dominance in both consumer and server markets, offering competitive performance at more affordable prices.
Under Su’s leadership, AMD evolved from a near-bankrupt company valued at $2 billion in 2014 into a company now worth over $150 billion.
In 2022, AMD surpassed Intel in market value, and the company now has its sights set on another industry giant Nvidia.
With AMD’s core business thriving, Su is now focusing on the AI revolution, a market currently led by Nvidia.
Recognizing AI’s potential to shape the future of computing, she has directed AMD to invest aggressively in AI hardware and software.
The company’s MI300 series AI chips have been adopted by major tech players like Microsoft and Meta for use in their data centers.
Su also led a strategic pivot in AMD’s manufacturing approach, championing the use of “chiplets”—smaller modular components assembled into a complete chip.
This innovation has improved production flexibility and enabled AMD to leverage multiple foundries for different chip components.
While AMD still trails Nvidia in AI chip market share, Su remains confident in the company’s trajectory.
“This is the beginning, not the end of the AI race,” she told the Financial Times.
However, with Nvidia’s $3 trillion market valuation and larger headstart, the company has a long way to go.
“I think there’s another phase for AMD. We had to prove that we were a good company. I think we’ve done that. Proving, again, that you’re great, and that you have a lasting legacy of what you’re contributing to the world—those are interesting problems for me.”
“We’re partnering with many of the companies in the semiconductor industry because no one company has all of the good ideas.”
“As good as today’s large language model is, it can still get better if you continue to increase the training performance and the inference performance.”