Yet Scale’s value remains in its elite trainer network (historians, scientists, PhDs) handling specialized tasks costing reportedly “tens to hundreds of dollars” per unit. While Meta’s non-voting stake avoided automatic antitrust review, regulators may still investigate the blurred line between influence and control. For now, the full implications will take months to unfold, as regulatory reviews, vendor transitions, and internal audits continue to reshape the AI data supply chain.
The new realities of AI development
As companies such as Google rush to build in-house data labeling capabilities, the industry faces a choice to repeat the mistakes of the cloud consolidation era of 2010-2015 or take a more open route.
“We’re seeing history repeat itself,” observed Anushree Verma, senior director analyst at Gartner. “The AI race is causing vendor fragmentation now, but consolidation is inevitable.” The parallels are striking. Like cloud providers before them, AI giants are pushing vertical integration that risks locking enterprises into monolithic systems. She urged CIOs to prioritize “agile, interoperable solutions” as safeguards against monolithic systems.
This story originally appeared on Computerworld
