Oracle is the recommended AI stock for 2026. Its sales grew 17% to $67.4 billion.
C3.ai's revenue dropped nearly 36% to $250.3 million.
Oracle also forecasts $90 billion in FY2027 sales.
What happened
Oracle is presented as the better AI stock investment for 2026 compared with C3.ai, despite C3.ai having a slightly lower sales multiple. Oracle's FY 2026 revenue reached $67.4 billion, up 17.4%, while C3.ai's revenue fell 35.7% to $250.3 million.
Why it matters
Oracle's growth is backed by record remaining performance obligations of $638 billion at the end of Q4, pointing to more sales ahead. C3.ai faces risks from revenue concentration, a sales organization restructuring, and its CEO Thomas Siebel's return in June after stepping down due to health issues.
What to watch
Oracle forecasted fiscal 2027 sales to hit $90 billion, while C3.ai still has to prove it can bounce back to growing sales. C3.ai reported a net loss of $470.4 million and a negative free cash flow of $190.7 million in its latest fiscal year.
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The article's recommendation hinges on momentum. Oracle's 17% revenue growth in FY 2026, combined with a record $638 billion in remaining performance obligations, signals sustained demand for its AI infrastructure. C3.ai, in contrast, is in a rebuilding phase following a 35.7% revenue decline and the temporary departure of its CEO, Thomas Siebel. Siebel's return in June is presented as a potential catalyst, but the company remains unprofitable with a negative net margin of 187.9%.
It's worth noting the divergent valuation metrics: C3.ai carries a slightly lower P/S ratio (5.9x) than Oracle (6.4x), making it appear cheaper on that basis. However, Oracle's forward P/E of 18.5x — the only one available since C3.ai isn't profitable — and its forecast of $90 billion in FY2027 sales frame it as the safer, more predictable choice. The article also highlights Oracle's resilience through a diversified global customer base and partnerships with third-party cloud providers like Alphabet, whereas C3.ai depends on a limited set of high-value customers, including the U.S. Department of Energy. While both operate in the AI field, the author's core argument is that not all AI exposure is equal: one offers proven, scaling profitability, while the other is betting on a turnaround.
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