Competing AI assistants have leaned heavily into large cloud-based language models, while Apple has historically balanced cloud capability with a strong emphasis on on-device processing and privacy.
This balance affects feature rollout speed — cloud-first competitors can update capabilities server-side overnight, while Apple’s approach often ties new AI features to specific hardware generations with enough on-device processing power.
The broader industry trend suggests a hybrid future, where routine tasks run locally for speed and privacy while more complex queries are handled by larger cloud models with user consent.