Inside the AI Upgrades Reshaping Consumer Devices

Ahead of CES 2026 next week in Las Vegas, several consumer electronics manufacturers are previewing hardware products built on specific, identifiable artificial intelligence (AI) technologies. The devices span wearables, mixed-reality systems, home security, appliances and robotics, but each relies on concrete combinations of cameras, sensors, onboard processors and AI models designed to capture data from the physical world, analyze it locally and trigger defined responses.

Wearables and Headsets

The AI glasses previewed by Rokid are built around a first-person camera, microphones, a micro-display and an internal computing module integrated into a glasses-style form factor. According to the company’s CES preview, the product has entered commercial mass production, signaling a move beyond developer kits or concept wearables.

The camera captures continuous visual input from the wearer’s perspective, which is processed by AI models capable of tasks such as text recognition, object identification and scene interpretation. Voice input captured through microphones is handled by speech recognition models that allow users to issue commands or queries hands-free. Outputs are delivered as brief visual overlays through the display, rather than full screen interfaces.

The mixed-reality headset from Play For Dream is a standalone, Android-based device designed for spatial computing without external hardware. It uses dual 4K-per-eye micro-OLED displays driven by onboard processors to render digital imagery directly in the headset. Cameras and motion sensors track head position and orientation, while software continuously calculates how digital objects should be positioned relative to the user’s physical surroundings. This allows virtual content to remain fixed in space as users move, an essential requirement for mixed-reality applications such as simulations and interactive environments.

AI in Security Cameras

Home and small business security systems are another category where AI is being embedded directly into hardware. Reolink previewed security cameras that run AI models locally on the device rather than relying entirely on cloud processing. The cameras use image sensors paired with onboard processors to analyze video streams in real time. Object detection and classification models are trained to distinguish between people, vehicles and animals, enabling the system to decide which events require attention.

Running AI on the device allows alerts to be triggered immediately and reduces the need to transmit continuous video footage offsite. The approach also enables features such as object-based search and customizable detection rules to operate even when network connectivity is limited or unavailable.

AI in Household Appliances

In the kitchen, Samsung showcased a AI Vision systems built with Google Gemini that integrate cameras and AI models into appliances such as refrigerators. Internal cameras capture images of stored food items and containers. Computer vision models analyze those images to identify what is inside, while a language model interprets the results and generates responses through the appliance interface.

According to the company, the system can recognize a wider range of food items without requiring users to manually label or register them in advance, relying instead on visual identification.

This setup connects perception and language processing inside the appliance itself. The system is designed to operate continuously in the background as the contents of the appliance change.

LG’s Home Robot

LG is applying similar AI components to robotics with a home robot unveiled ahead of CES. The robot integrates cameras, proximity sensors, motors and an onboard AI processor into a mobile platform intended for indoor environments. Vision systems allow the robot to recognize people and objects around it, while navigation software uses sensor data to move through rooms and avoid obstacles.

The robot also includes articulated arms designed for basic physical interaction with its surroundings. Voice input and audio output support basic interaction, allowing the robot to respond to spoken requests while operating within predefined parameters.