Closing in on #1
Remarkably, Larry Ellison, founder and Executive Chairman of the company, is now closing in on Elon Musk for bragging rights to the title of world’s richest man. We estimate his net worth will climb to something around $350 billion at current trading levels for ORCL.
ORCL’s market cap is still far below its largest tech peers, although it is getting close to the trillion dollar club with today’s post-market surge. The reason Ellison’s net worth is so high is that he owns so much of the company—more than 40%.
A key factor behind Ellison’s large ownership stake is that ORCL for many years was aggressively repurchasing its own shares through internally generated cash flow when the stock was underperforming.
As total share count declined, Ellison and other shareholders who hung onto their shares gradually owned more of the company.
What ORCL is getting right
ORCL has made a remarkable transition from the world’s leading database provider to become a major player in AI infrastructure.
While leveraging its dominance in database management in many ways, ORCL has pursued a partnership-friendly approach. Unlike cloud peers like Amazon (AMZN), Microsoft (MSFT) and Alphabet (GOOGL), ORCL does not have its own AI model.
Instead, ORCL is a neutral player that provides AI computing capacity to these AI hyperscalers as well as enterprises. And it allows all of its customers to connect their data to AI supercomputers in a safe and efficient manner.
Thanks to its unique positioning within the emerging AI ecosystem, Oracle Cloud Infrastructure (OCI) is now growing at extremely fast rates.
On the earnings call, CEO Safra Katz presented guidance for massive growth expectations in the OCI business in the years ahead.
She expects revenue for the unit to grow by 77% to $18 billion in the current fiscal year, and “then increased to $32 billion, $73 billion, $114 billion and $144 billion over the following four years.”
Focus on inference
One interesting area of major emphasis on the earnings call was Ellison’s discussion of the long-term opportunity in AI inference.
While AI training represents the process of teaching AI supercomputers how to think, inference refers to the application of that learning in the real world.
If training is going to school, inference is getting a job.
Ellison thinks inference will ultimately be the far larger market. ORCL is positioning itself to win here by leveraging its core strength as custodian of enterprise data.
