GE Vernova and Vertiv: Why AI Power Stocks Are Becoming the New Data-Center Bottleneck Trade
Gartner 565 TWh forecast and a FERC grid order put GE Vernova and Vertiv at the center of AI data‑center constraints. Compare roles, catalysts, and risks.
ComputerWorld AI·
Tech industry experts are urging IT decision-makers to be wary of AI vendor gimmicks such as free tokens, and to adopt a multi-vendor and multi-model strategy to avoid vendor lock-in. “Don’t be afraid to adopt a multi-vendor approach to get value from different AI tools rather than risk lock-in with a single one,” said Max Goss, senior director analyst at Gartner. It is unlikely one AI vendor or model will meet an organization’s requirements, Goss said. The advice comes as more AI vendors are offering cheap tokens subsidized by venture capital in a land grab for customers. The companies are also hiring forward-deployed engineers (FDEs) to push their models to enterprises. Once companies start developing business processes around specific AI models, they get locked into their ecosystem. “People are adopting hybrid strategies…to cut token costs, and adopting more token-efficient models,” said Jack Gold, principal analyst at J. Gold Associates. Free and low-cost tokens from AI vendors cou
Read full articleGartner 565 TWh forecast and a FERC grid order put GE Vernova and Vertiv at the center of AI data‑center constraints. Compare roles, catalysts, and risks.
When it comes to AI deployments, IT leaders are often caught in an awkward middle space, trying to reconcile conflicting directives from senior management with constantly changing AI models, capabilities, and costs; data governance and security needs; and the limitations of their own team. “Very few real benefits can be attained by simply purchasing an AI product and giving it to employees. Vendors have been overselling that fallacy for the past three years,” said Nader Henein, a Gartner VP analyst. “The reality is that strong AI value and consistent ROI are almost always a result of deep and intentional integration of AI capabilities into existing workflows. For that you need specialized teams, which do not come cheap, and organizations have been recruiting those teams in a variety of ways,” Heinen said. Among the options available to IT leaders looking for help with AI deployments are traditional IT consultancies, AI-specific consultancies, and independent contractors. Large enterpri
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