By PYMNTS
Publication Date: 2026-01-02 19:34:00
For much of the past decade, artificial intelligence has been concentrated in the cloud. Large models trained and run in centralized data centers have powered chatbots, enterprise tools and consumer applications, but that approach comes with trade-offs. Cloud dependence introduces latency, increases infrastructure costs and requires user data to move across networks. As AI becomes embedded into operating systems and everyday software, those constraints are becoming more visible.
