Inflation may have cooled significantly in June, but one Wall Street strategist says it's still a problem for one of the market's hottest commodities: AI chips.
Julia Hermann, global market strategist at New York Life Investment Management, says that "chipflation"—or the surging prices for AI-related logic and memory chips—will be the next headwind to test the strength of the AI trade.
"Hyperscalers face a balancing act of rising input costs — higher chip prices, as well as rising energy and utility costs — with an outlook for return on investment that is still several years away," Hermann told Business Insider. "We believe this environment is primed to test conviction: investors may tolerate volatility and a slower monetization outlook if they continue to believe in the long term potential of the AI trade."
Chip stocks have been under pressure lately as investors start to scrutinize the economics of the AI boom. Sector leaders have tumbled in recent weeks, with investors dumping hot stocks like memory makers and other hardware plays, even as early earnings reports have largely beaten estimates.
In Hermann's view, Asian markets have been showing the type of growth that can be worrisome, reaffirming her thesis on chipflation.
"One of the best indicators of chipflation in memory capacity is South Korea's export price index of DRAM memory," she said. "In past cycles, memory chip price growth topped out at around 100% year-over-year growth, but today, South Korean memory chip prices are growing at 370% year-over-year growth."
Hermann's thesis about the impact of pricier chips centers on the idea that it's a double-edged sword, and a market-driving force that impacts the AI trade in a few ways.
While rapidly rising chip prices are an indication of strong demand, they also have the power to grind the AI boom to a halt, as more expensive chips mean higher costs for the companies already pouring billions into building out AI infrastructure.
"Although the volatility associated with semiconductor leadership has been primarily to the upside this year, that volatility can work in both directions and test investor conviction," she said. "We are most focused on quality across the AI supply chain, including semiconductor giants, and define quality as strong profitability, low-to-moderate earnings variability, and strong interest coverage."
