Forget AI Training: AI Inference Is the Real Money Maker in 2026. Here Are 2 Stocks to Own.
The Motley Fool
by newsfeedback@fool.com (Justin Pope)February 24, 2026
AI-Generated Deep Dive Summary
The AI landscape is shifting, with AI inference poised to dominate over training in 2026. According to Deloitte Global's TMT Predictions report, inference will account for two-thirds of all AI computing by that year. This marks a significant evolution in how AI is utilized, moving beyond the initial model-building phase (training) to focus on real-world applications and operations (inference). While training involves building intelligent models, inference deals with applying these models to solve practical problems, such as OpenClaw AI agents operating autonomously on personal computers. This shift highlights a growing demand for efficiency in computing power rather than raw processing might.
The distinction between training and inference lies in their computational requirements. Training typically requires massive amounts of data and powerful hardware to build accurate models, but inference focuses on delivering results quickly and efficiently in real-world scenarios. Despite this shift toward efficiency, the need for advanced chips remains critical. Inference tasks require specialized hardware that balances speed and energy consumption, making semiconductor companies like NVIDIA and AMD key players in this transformation. The demand for these chips is expected to surge as AI adoption accelerates across industries.
From a financial perspective, the rise of inference presents lucrative opportunities for investors. Companies specializing in efficient computing solutions are likely to see significant growth. For instance, NVIDIA's GPUs and AMD's processors are essential for inference tasks, positioning them as key beneficiaries of this trend. Additionally, the shift toward efficiency could drive innovation in chip design,
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Originally published on The Motley Fool on 2/24/2026