Xiaomi President: AI Boom Will Force Smartphone Price Hikes in 2026
Xiaomi has issued a direct warning to the consumer electronics market: smartphone prices are set to rise significantly in the coming year due to supply chain constraints created by the global surge in artificial intelligence development.
During the company’s third-quarter earnings call on Tuesday, Xiaomi President Lu Weibing stated that the rising cost of memory chips, driven by a reallocation of manufacturing capacity toward AI servers, will result in a “sizeable rise” in retail prices for consumers in 2026.
The “AI Tax” on Consumer Electronics
The projected price increases stem from a fundamental shift in semiconductor manufacturing. As demand for AI training and inference explodes, major chipmakers such as Samsung and SK Hynix have shifted production lines to prioritise High Bandwidth Memory (HBM) chips, which are essential for AI accelerators.
This pivot has constrained the supply of standard DRAM and NAND flash memory used in smartphones and personal computers.
“I expect pressure to be much heavier next year than this year,” Lu told reporters regarding component costs. He indicated that while manufacturers will attempt to absorb some variance, the scale of the cost increase is too large to ignore. “Some of the pressure may have to be addressed through price hikes; price increases alone won’t be enough to digest it.”
Industry analysts suggest this trend will likely affect all major smartphone manufacturers, not just Xiaomi, as the competition for limited memory fabrication capacity intensifies.
Industry Outlook
The dual pressures of rising component costs and the need for advanced on-device AI capabilities are reshaping the smartphone market economics. While diversified manufacturers may have some buffer through other product lines, the core message remains that the cost of mobile hardware is on an upward trajectory. Consumers upgrading their devices in 2026 should anticipate higher price points across the board as the industry passes on the costs of the AI infrastructure boom.
