{
  "id": 19588853,
  "title": "Nvidia’s AI Dominance Faces 2027 Turning Point, KB Securities Report Says",
  "url": "https://urgent.news/2026/11/12/nvidias-ai-dominance-faces-2027-turning-point-kb-securities-report",
  "topic": "ai",
  "section": "AI",
  "published": "2026-11-12T02:52:51.000Z",
  "source": {
    "name": "BusinessKorea",
    "slug": "businesskorea",
    "url": "https://www.businesskorea.co.kr/news/articleView.html?idxno=281112"
  },
  "original_language": "en",
  "account": "A report by KB Securities suggests that Nvidia's dominance in the AI industry could face a turning point by 2027, driven by the increasing availability of alternative chips and emerging challenges in power procurement and financing for data centers. The report, released on Nov. 12, predicts a growing distribution of profits across the industry, extending beyond GPU suppliers to include companies developing inference accelerators, proprietary accelerators, and CPUs.\n\nNvidia's CEO, Jensen Huang, is reportedly facing speculation about his departure, with the company's board reportedly preparing for a possible leadership change. This uncertainty has added to market volatility, particularly regarding Nvidia's financing policies that have supported customers' chip purchases and data center projects. However, the company's financial pressure due to high GPU depreciation costs and borrowing expenses on data center operators cannot be ignored.\n\nAlternative accelerators, such as Google's tensor processing units (TPUs) and Cerebras' inference systems, are expected to gain traction as they offer greater cost and power efficiency. Google TPUs are projected to see a significant surge in sales, reaching over $135 billion by 2028, while Cerebras plans to offer its inference systems to cloud customers in the first half of 2027. Power availability and regulatory compliance are emerging as major challenges for the expanding AI data center industry, with 40 out of 41 ballot measures favoring tighter regulation.\n\nNvidia's revenue is expected to grow by 70% in fiscal 2028, but its share of the accelerator market is gradually declining. The AI market's shift towards inference, which enables AI models to be used in services and applications, could further strengthen the position of alternative chips. While Nvidia remains strong in the short term, the report recommends diversifying AI investments to include companies involved in inference and proprietary accelerators to capture the profits generated by the evolving AI industry.",
  "summary": "Forecasts suggest that the current structure of the AI industry, in which profits are concentrated in Nvidia, could reach a turning point around 2027. The outlook is driven by the growing availability of alternative chips, including Google’s proprietary tensor processing units (TPUs) and accelerator",
  "key_points": [],
  "editors_take": "The rise of cost-efficient inference accelerators and power constraints signals a transition from GPU-centric dominance toward a more distributed profit landscape across the broader artificial intelligence hardware industry.",
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}