On-body agents: Why Big Tech is buying into AI wearables

What Changed and Why It Matters

Wearables are moving from step counters to “on-body agents.” They listen, watch, coach, and take action.

Big Tech and startups are rushing in with rings, pins, glasses, and bands. The bet: a new interface layer that’s closer than your phone.

“Startups and tech giants alike are rushing to launch wearable technology—from bracelets to necklaces to glasses and more.”

Two signals stand out. First, demand and spend are climbing fast. Second, most devices still lean on the phone for brains.

“Spending on AI-powered wearables is expected to reach $304.8 billion by 2033.”

“Most AI wearables rely on smartphone connectivity for advanced processing and full functionality.”

Here’s the part most people miss: the battle isn’t just hardware. It’s who owns the on-body context—sensors, routines, and trust.

The Actual Move

What’s happening across the ecosystem:

New form factors, same pattern: rings, pins, glasses, necklaces—all promising ambient AI access and coaching.
Health is the wedge: early warnings for heart rhythm, glucose patterns, and stress signals are mainstreaming.
Coaching as a feature: wellness, productivity, and safety coaching are becoming default software layers.
Phones remain the anchor: most devices offload heavy AI to the smartphone for latency and battery reasons.
Industry pull: healthcare, sports, manufacturing, and retail are adopting wearables for efficiency and safety.
Privacy and “always-on” concerns are rising: continuous sensing creates new trust and design requirements.

“AI-enabled wearables can detect early signs of health issues, such as irregular heart rhythms or abnormal glucose levels.”

“From healthcare and sports to manufacturing and retail, AI-powered wearables are driving efficiency, safety, and personalization.”

“The convergence of AI and wearables is making technology more human-centered, predictive, and adaptive.”

“The ultimate AI wearable is a piece of tech you already own.”

“Personalized health monitoring, wellness coaching, and enhanced privacy in stylish new designs.”

“The fundamental question isn’t whether these AI wearables will be helpful—they undoubtedly will be in many ways.”

“Most AI wearables rely on smartphone connectivity for advanced processing and full functionality. This limits their appeal as genuine smartphone replacements.”

“Implementation of artificial intelligence in wearables has revolutionized different industries.”

The Why Behind the Move

Zoom out and the pattern becomes obvious: on-body context is the new moat. Big Tech is buying into wearables to deepen daily touchpoints, own sensor data, and anchor AI agents to real-world signals.

• Model

Lightweight, on-device models for intent, speech, and anomaly detection. Heavy LLM calls still route through phones or the cloud to save battery.

• Traction

Health, safety, and coaching show the fastest adoption. Clear ROI and daily utility drive retention.

• Valuation / Funding

Category growth attracts capital. Forecasts point to a massive market by 2033. Winners pair sensor IP with sticky software.

• Distribution

The phone is the distribution backbone. The best wearables ride existing app stores, accounts, and payments. Distribution often beats novel hardware.

• Partnerships & Ecosystem Fit

Healthcare systems, insurers, employers, and sports leagues are critical partners. Data standards and integrations create moat-like friction.

• Timing

On-device AI is finally good enough. Battery tech and low-power silicon unlock all-day agents. Consumers now expect personalized coaching.

• Competitive Dynamics

Platforms: Apple, Google, Meta leverage OS, identity, and app ecosystems.
Specialists: health-first players win on accuracy and trust.
Fashion and form factor matter: comfort drives compliance.

• Strategic Risks

Battery and heat constraints limit features.
“Always-on” privacy risks can erode trust fast.
Overpromising clinical claims invites regulation.
Too much cloud reliance kills latency and UX.

What Builders Should Notice

Anchor to the phone, then graduate. Piggyback on distribution you already have.
Sensors are a moat. Proprietary signals plus useful models beat me-too hardware.
Coach over chat. Outcome-oriented coaching drives retention better than Q&A.
Privacy is product. Clear data boundaries and on-device defaults win trust.
Energy is a feature. Optimize for battery before you ship features people won’t use.