By Harsh Chauhan
Publication Date: 2026-05-23 15:59:00
Consulting giant Deloitte noted in November last year that inference workloads will be the next big thing in artificial intelligence (AI) in 2026. According to Deloitte, inference will account for two-thirds of AI computing power this year, up from 50% in 2025.
Deloitte estimates the market for inference-focused AI chips could reach $50 billion this year. McKinsey, on the other hand, estimates that AI inference workloads in data centers could jump from almost 21 gigawatts (GW) last year to 93 GW in 2030, clocking a compound annual growth rate (CAGR) of 35%.
Not surprisingly, there is a race among AI chipmakers to make inference-focused processors to capitalize on this lucrative growth opportunity. From Nvidia (NVDA 1.86%) to Advanced Micro Devices to Broadcom to Intel, everyone is trying to make the most efficient chips that can run AI inference applications cost-effectively in data centers and at the edge.
However, I believe that these semiconductor companies will be beaten by Arm…
