Energy for AI

A stock market frenzy in Korea is driven by semiconductor firms tied to global AI investment, but new concerns about energy supply for AI training and inference could delay adoption. McKinsey projects worldwide data center capacity will reach 220 gigawatts by 2030, six times 2020 levels, while Gartner forecasts a 26% rise in data center power consumption this year.

Korea is in the midst of a stock market frenzy. Stock prices are influenced by a company's future value, and Korea's market is heavily weighted toward semiconductor firms whose share prices are shaped by global artificial intelligence AI investment. This is why investors in the Korean market are fixated on the future of AI. Their focus is on how much AI will reshape past industries and cultures, and whether it can generate returns commensurate with expectations. Recently, a new element has entered this mix: energy. Concerns have emerged that the energy essential for AI training and inference may not be supplied as smoothly as anticipated, potentially delaying AI adoption in certain regions. According to data released last August by global consulting firm McKinsey, worldwide data center capacity is projected to reach a cumulative 220 gigawatts by 2030, six times the 2020 level. This growth is driven primarily by the expansion of AI data centers. Relatedly, earlier this month, research firm Gartner projected this year's data center power consumption to rise 26 percent from last year to