Enabling Ambient AI with Wearables and AIoT

Artificial Intelligence (AI) has quickly moved from research labs to our daily lives. Advances in large language models (LLMs) have accelerated AI adoption, with chatbots like ChatGPT and Meta AI now serving roughly 700 million and 1 billion active users, respectively. Consumers now rely on them to answer questions, summarize information, and even make simple decisions, gradually replacing traditional tools like Google Search and Wikipedia. Instead of browsing multiple sources, users can now ask an AI-powered app and receive a concise response. These models not only retrieve and consolidate information from various sources but also apply reasoning to provide simplified, actionable answers.

Despite its progress, today’s AI largely relies on the internet as its source of knowledge and struggles to become an intimate extension of our daily lives. While some smartphone apps have started experimenting with always-on microphones and camera-based environment understanding, these methods are neither convenient nor privacy-first. These features may help users find value in some AI offerings, but the current user experience’s requirement to point our phones at the environment remains impractical.

A significant shift is underway; AI models are being trained to be multimodal, learning to understand not just text but also images, audio, video, and even sensor data streams. This evolution will allow AI to comprehend real-world context, moving beyond the confines of our screens to become an environment-aware extension of our lives.

The Current Landscape: Assistive AI

Even with the surge in popularity, most consumer AI applications today are assistive rather than agentic. Consumers primarily use AI to rewrite text, summarize content, proofread emails, generate meeting notes, or occasionally get help with technical tasks. These are productivity boosters, but they do not act on behalf of the user. As a result, current AI adoption is driven by software, not hardware. Consumers can access these capabilities on smartphones and the web without investing in specialized devices because most AI services run in the cloud. For now, AI is convenient but largely passive and reactive as it waits for users to initiate interaction and constantly provide input.

AI and its capabilities are developing at an unprecedented pace, and the next major challenge lies in enabling seamless accessibility of AI through dedicated devices. Wearable AI proposes the next frontier in personal computing—devices that can take AI beyond screens, make it seamlessly interactive, and gather context in real time using multiple sensing modalities such as on-board microphones, sensors, and cameras.

Industry Shift Toward Agentic AI

The real transformation will come with agentic AI, which can act in the real world on behalf of the user with minimal prompting and supervision. Instead of merely answering questions or generating text, agentic AI can manage calendars, draft and send emails, order groceries, book rides, make reservations, and control smart home devices. This evolution turns AI from a passive productivity booster into an active participant in daily life, but enabling such capabilities requires deep integration with personal data and direct interaction with the user’s environment. Hence, these capabilities raise concerns about user privacy, trust, explainability, and reliability.

To enable agentic AI, the industry is exploring two paths:

• On-device AI, which processes data locally to improve privacy, reduce latency, and work even without connectivity. This approach, seen in Apple Intelligence, trades convenience for technical challenges; local AI models can drain battery life and increase device costs. Additionally, evolving models would require new hardware, resulting in poor backward compatibility. With limited compute power, device models may also underperform compared to cloud-based counterparts.
• Cloud and ecosystem AI, which leverages existing devices and the cloud to deliver advanced capabilities without requiring hardware upgrades. This approach powers platforms like ChatGPT, Meta AI, and Alexa+, where cloud-based AI spans many smart speakers, vehicles, smart TVs, smartphone apps, and wearables like smart glasses and earbuds. It offers a richer experience but relies on stable connectivity and often requires linking user accounts and sharing data with the cloud. While this is the fastest path to deployment and drives AI adoption, it may not be the most sustainable one.

Wearables Bring User Context

Smartphones and laptops are limited by their form factor. They require explicit user attention and interaction to operate. Wearables change that dynamic by enabling hands-free, always-available interaction, making agentic AI feel effortless. Today’s wearables offer early glimpses of this shift. Devices like Echo Frames and Echo Buds extend Alexa’s capabilities outside the home with location-aware assistance. At the same time, Apple Watch and AirPods enable voice interactions and health tracking without pulling out a phone.

As generative AI becomes multimodal, the next wave of wearables will move beyond notifications and simple commands. They will offer always-on voice interaction, real-time AI processing using cameras, and seamless interaction with the surrounding IoT environment. These devices can also act as personalized context collectors, sensing movement, gestures, orientation, and even biometrics. Combined with AI, this contextual awareness allows assistants to anticipate intent and respond intelligently, often without explicit commands. In essence, wearable AI will let devices hear what we hear, see what we see, and sense the world around us, transforming raw context into meaningful assistance.

Ambient Computing: Intelligent IoT and Wearables 

While wearables provide identification and rich personal context, AI cannot act effectively if the surrounding environment is not equally intelligent. This is where the Internet of Things (IoT) plays a crucial role, making the world around us both perceivable and actionable through sensing and actuation.

The next evolution of IoT comes from ambient sensing, where the environment itself becomes intelligent. In academia, this is referred to as ubiquitous computing. In this paradigm, the computer is not limited to a single device and it fades into the environment while understanding our presence and behavior without requiring constant input. Wireless sensing is a key enabler, allowing systems to detect human presence, movement, and even micro-motion like gestures and breathing rate. This capability unlocks a new generation of Artificial IoT (AIoT) experiences where intelligent environments like smart homes can collaborate with personal context from the wearables to create an ecosystem of AI-driven experiences.

Imagine a home could automatically adjust lighting, temperature, and media based on your preferences, where you are, and what you’re doing, without a single voice command. Health monitoring could become passive, detecting falls, abnormal movement, or even sleep quality without a smartwatch. Hospitality spaces like hotels and rental properties could recognize occupants and adjust environments automatically to their preferences. Secure access systems could unlock doors as you approach, and gesture recognition could replace voice commands in noisy settings like kitchens or workshops. Your identity and preferences can travel with you on your wearables and seamlessly interact with the environment. By processing this data locally, these systems can remain privacy-conscious while delivering a truly proactive experience.

The onset of augmented and mixed reality (AR/XR) devices will amplify these capabilities, allowing users to interact with the connected devices in their environment and surroundings with visual interfaces. Imagine glancing at a lamp through your smart glasses and seeing its controls instantly, adjusting lighting with a subtle gesture. By combining personal context provided by wearables with ambient intelligence of IoT environments, AI can move from reactive to proactive use cases, understanding both the user and the space in real time.

The Path to Ambient AI

Different motivations for companies and consumers drive the race toward AI-powered devices. For technology companies, the primary goal is speed to market and rapid AI adoption. Agentic AI capabilities and wearable devices serve as pathways to ecosystem lock-in and recurring revenue streams. Running AI models in the cloud while consuming user context and personalization is costly, so selling interconnected devices that encourage subscriptions or services helps justify the investment. Many companies envision multi-device ecosystems where consumers own AI-enabled hardware across categories: smartphones, smart glasses, earbuds, watches, vehicles, smart speakers, and sensing IoT devices.

Consumers, on the other hand, focus on privacy, trust, and tangible value. On-device AI offers stronger data security but can affect battery life and affordability, while cloud-based AI provides richer capabilities but requires data sharing and stable connectivity. Feature fatigue is also a risk; the market is crowded with low-value gimmicks that have little impact on our lives. For example, Samsung’s AI-enhanced moon photograph drew controversy, while practical features like Google’s Magic Eraser and Apple’s Clean Up gained traction by solving real problems. For consumers, the actual return on investment will come from AI that simplifies life, operates reliably, and earns trust without demanding constant attention.

At the intersection of wearables, ambient computing, and agentic AI lies the potential for IoT to reach its full maturity. Ambient AI refers to intelligent systems that seamlessly integrate into the background of everyday environments, continuously sensing context, anticipating needs, and taking proactive action without explicit commands. Wearables provide personal context and mobility. Ambient sensing enables environments to detect presence, activity, and intent without intrusive cameras. Agentic AI unites these elements, allowing the assistants to act purposefully on behalf of the user.

The future of IoT will not be defined by flashy features but by quiet intelligence, devices, and assistants that operate reliably in the background, delivering convenience and value while protecting privacy. As homes, workplaces, and vehicles become AI-aware, success will belong to systems that earn trust, preserve agency, and integrate naturally into daily routines. When that happens, wearable AI and ambient intelligence will no longer be optional enhancements; they will be woven into the fabric of everyday living.