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AI industry competition, energy demand, and labor shifts

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2026-08-29 01:07 UTC → 2026-09-05 10:42 UTC · added ~~removed~~

The AI industry is undergoing intense economic and structural shifts. A significant price war has emerged as major US laboratories, including OpenAI and Anthropic, compete against Chinese developers like DeepSeek and Moonshot. ~~While token prices for leading US models dropped by nearly 25% in mid-July, the~~ The industry is ~~now~~ transitioning toward usage-based, pay-as-you-go pricing ~~models. This~~ models, a shift is driven by the rise of ‘agentic AI’—autonomous systems capable of executing complex ~~workflows—which significantly increases computational demands. Goldman Sachs predicts global monthly token processing will reach 120 quintillion~~ workflows. This transition is fueled by ~~2030,~~ the pursuit of Artificial General Intelligence (AGI), a ~~24-fold increase from 2026 levels.~~ theoretical stage of human-like reasoning. OpenAI co-founder Greg Brockman has suggested that advancements such as the GPT-6 Astra model mark the “beginning of the era of AGI.” These technological shifts are creating profound labor market disruptions. In the United Kingdom, AI is displacing traditional entry-level positions, contributing to a youth unemployment rate of ~~16.4%, the highest in a decade.~~ 16.4%. Consequently, university degrees alone are becoming insufficient, prompting the British government to subsidize employer hiring through job guarantee programs for those aged 18 to 24. Despite individual efficiency gains, macro-level productivity remains elusive. In both Japan and the United States, data suggests that total working hours have not decreased and organizational productivity has not significantly increased. In Japan, a significant investment gap exists; ~~nearly half~~ approximately 47.1% of large companies invest less than 1 million yen in generative AI, while only 2.3% invest more than 500 million yen. This low investment, coupled with the risk of high costs from usage-based billing, may impact international competitiveness. Success remains tied to the human component, as organizations neglecting talent are 1.6 times more likely to fail in achieving expected AI returns.

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