Navitas Semiconductor got a lot of attention last year as its stock price surged some 376% for the year to more than $17 per share in late October.
The chipmaker’s stock price has fallen back to roughly $9 per share as of March 19, but it is still up 23% year to date and 250% over the past 12 months.
Will AI create the world’s first trillionaire? Our team just released a report on the one little-known company, called an “Indispensable Monopoly” providing the critical technology Nvidia and Intel both need. Continue »
Navitas’ meteoric rise was fueled by several factors. One of the major catalysts was a new partnership with Nvidia to supply it with its gallium nitride (GaN) and silicon carbide (SiC) chips for AI data centers. These Navitas chips are considered faster and more efficient than traditional silicon wafers and will be used in Nvidia’s next-generation data center architecture, starting in 2027.
Also, Navitas is pivoting from providing chips for consumer markets — smart phones, PC, and electronics — to bigger power markets, like data centers, electric vehicles, and industrial.
Analysts expect to see revenue decline this year, due to the pivot, but bounce back in 2027 when the Nvidia contract kicks in.
Navitas stock has a median price target of $8 per share, which would suggest a 9% decline in the stock price. While Navitas stock could certainly be a stellar long-term option, it is still not consistently profitable and faces uncertainties with its pivot.
A more cautious investor may want to consider a less volatile AI stock, IBM (NYSE: IBM).
IBM has made the transition from a computer hardware company to an AI powerhouse, focusing on AI consulting through its watsonX platform and cloud computing.
In 2025, IBM grew revenue by 8% and adjusted earnings by 12%. It also lifted its gross profit margin by 1.7 percentage points to 59.5%. For this fiscal year, it anticipates revenue growth of 5% and free cash flow to increase by about $1 billion.
In March, IBM signed an agreement with Nvidia for its watsonX AI platform to increase performance and reduce costs for the extraction of large AI datasets.
IBM also recently acquired Confluent and its data streaming platform, used by 40% of Fortune 500 companies. The smart data platform gives AI models and agents the data needed to operate across hybrid cloud environments. Typically, AI data is siloed and takes longer to access, so IBM is seeking to use Confluent to deliver data faster and securely at scale.