Why Oracle’s New Data Platform Matters

Good morning. The headline numbers in Oracle’s first-quarter earnings report were impressive enough, sparking a turnaround in its stock. Shares of the tech giant were up this morning in premarket trading.The company’s results and its forecast for the current quarter and the year were reassuring. It confirmed capital spending plans that have unnerved some investors and contributed to a lowering of its credit rating. The company also announced a new data platform that has received little attention, but it’s worth understanding, because it says a lot about how technological advances are extending the pathway for the continued adoption of AI by large companies.

The word of the day is ‘ontology.’ Ontology refers to “a model defining the core concepts, relationships and rules of the business,” Oracle said yesterday in its announcement. It unveiled a new data platform that automates that descriptive process.

“Virtually all of Oracle’s enterprise customers want to use AI to reason on their private data and to use AI agents to automate their business processes. To do this efficiently, customers must first precisely describe the semantic details of their private data and business processes in an Enterprise Ontology,” the company said. It gave a nod to Palantir for pioneering the use of AI on private data by crafting ontologies for each of its customers.

Oracle said its new platform fully automates the creation of such ontologies, making it “inexpensive, easy and fast” for enterprises to use the most advanced AI to reason on their data and automate their business processes.

That user experience is the glide path to continued AI adoption for Oracle and the market more broadly. Those innovations in so-called deep technology go way beyond the development of faster models. They’re the ultimate engine behind the AI boom, and that engine is still running.

How is your company getting its data infrastructure ready for AI? Send your feedback to me at steven.rosenbush@wsj.com (if you’re reading this in your inbox, you can just hit reply).

“What will our economic future look like?” That’s the question posed by a report Anthropic’s economics team examining artificial intelligence’s potential impact on productivity and jobs between 2026 and 2030.

The team lays out several scenarios, varying by the speed of adoption, the degree to which AI drives productivity, and whether it supports or replaces workers.

What Anthropic calls a “modest” scenario would play out something like the emergence of the internet—driving real gains, but gradually, and within what they call “the historical norm for new technologies.”

In an “extreme” scenario, AI surpasses human productivity across most knowledge-work tasks, performing nearly all of them autonomously. By 2030 GDP growth climbs to 15% per year.

By 2030, cognitive employment is 21.5 percent below its mid-2026 level, and the unemployment rate for workers who began in cognitive occupations is a stunning 17.9 percent, far above any postwar rate in the United States. The economy-wide unemployment rate rises to 11.9 percent.

Coming amid a week of prophesying—by researchers connected to the same AI lab—that humanity could face extinction within the next 10 years, the report can be read as a note of optimism. Good or bad, an economic future implies there is a future.

Meanwhile, in the present

Closer to home, research and advisory firm Gartner predicts another sort of reckoning: By 2029, 30% of employees laid off due to AI will need to be rehired, the assumption being that business and IT executives who used AI primarily as a cost-cutting tool moved a bit too hastily.

“Instead, they should develop a ‘talent remix’ strategy that uses AI to reshape roles and redirect workers from less productive work to new opportunities,” said Tori Paulman, VP analyst at Gartner.

The personal version of the question

And even closer to home, the WSJ talked with a variety of future-of-work experts about the best college majors to not only survive but thrive in the AI era.

Forget computer science—although grads from top schools are doing all right—and forget AI itself: “It’s sort of like saying you majored in Excel,” says one expert.

Instead, think math, anthropology, even philosophy.

Some of them might be baristas, but the data suggests people who study philosophy are good at figuring out alternative uses for their talents. That’s sure to be valuable in a future job market that AI will change in ways we can’t anticipate.

An economy run by philosophy majors? How would Anthropic classify that scenario?

The WSJ Tech Council brings together CIOs, CTOs and CISOs advancing innovation and shaping the future. Join this trusted community where tech executives connect with peers to explore emerging trends and gain the perspective they need to stay ahead of disruption.

Request Information

Follow Isabelle Bousquette on LinkedIn, Instagram, X, and TikTok for more behind the scenes on her tech and AI coverage, and lately, her contributions to the WSJ Leadership Institute’s new Executive Resilience series, where she’s profiling America’s top execs about their fitness and wellness habits.

Follow Belle Lin on LinkedIn and X for her latest reporting on enterprise technology and AI.

Steven Rosenbush is chief of the enterprise technology bureau at the WSJ Leadership Institute. He also has a column. You can follow him on LinkedIn.

Tom Loftus is the editor of The Morning Download. He suggests following Isabelle, Belle and Steve on their various social channels. But if you insist, here’s his LinkedIn.