How does AT&T Wi-Fi Personalization work?

AT&T's Wi-Fi Personalization uses AI to learn your internet usage habits and automatically prioritize traffic for activities like gaming or streaming.

Is AT&T Wi-Fi Personalization free?

Yes, the Wi-Fi Personalization feature is being added at no extra cost for eligible AT&T subscribers.

Does AT&T collect my personal data with Wi-Fi Personalization?

No, AT&T states that all AI processing occurs locally on your gateway, and personal details do not leave your home.

Home / Technology / AT&T AI Boosts Your Home Wi-Fi Speed

AT&T AI Boosts Your Home Wi-Fi Speed

10 Dec

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Summary

New AI feature prioritizes home Wi-Fi traffic based on user activity.
Feature automatically activates for AT&T fiber and mobile subscribers.
AI processes data locally on gateways, ensuring user privacy.

AT&T is introducing Wi-Fi Personalization, an innovative AI feature aimed at optimizing home internet performance. This system intelligently identifies and prioritizes your online activities, such as streaming video or engaging in online gaming, based on typical usage patterns. For customers subscribed to both AT&T home fiber and mobile services, or those with All-Fi Pro plans, this enhancement is automatically enabled.

The AI analyzes application-level traffic, distinguishing it from device-based prioritization. For instance, multiple streaming devices will be recognized as video streaming and prioritized during typical viewing times. This software-based feature is being rolled out to AT&T's Wi-Fi 7 and Wi-Fi 6 gateways, with no additional cost to subscribers. Importantly, AT&T states that all AI processing is confined to the home gateway, ensuring personal details and specific content remain private.

While Wi-Fi Personalization is automatically active, users can manage its settings through the AT&T Smart Home Manager app. This allows for pausing the feature or manually setting priorities for specific activities, like ensuring optimal performance during live sports events. The AI operates by analyzing historical data patterns rather than reacting to immediate demand, aiming to continuously refine network performance over time.