웨어러블 헬스 분야 AI 시장 : 시장 점유율 분석, 업계 동향 및 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the AI in wearable health market size is expected to grow from USD 13.04 billion in 2025 to USD 15.28 billion in 2026 and is forecasted to reach USD 39.18 billion by 2031 at 20.72% CAGR over 2026-2031.

This report is Segmented by Device Type (Smartwatches, Fitness Bands, and Others), Component (Software, Hardware), Application (Remote Patient Monitoring, and Others, AI Algorithm (Machine Learning and Predictive Analytics, and Others)), End-User (Individual Users, and Others), and Geography (North America, Europe, and Others). The Market Forecasts are Provided in Terms of Value (USD).

Global AI In Wearable Health Market Trends and Insights

Continuous Miniaturization of Low-Power AI Chipsets

The AI in wearable health market is gaining from smaller and more power-efficient silicon that improves performance without raising device size or charging burden. Ambiq and Bravechip introduced the BCL603S3H chiplet platform in January 2026, and the launch claimed smart ring bill-of-materials cuts of up to 85% and production yield improvement of 20% while supporting on-device analysis of SpO2, heart rate variability, and sleep metrics with battery life of up to 7 days. That scale of cost compression matters because it widens the addressable base from wellness buyers to patients who need frequent monitoring but remain price sensitive. Qualcomm also announced Snapdragon Wear Elite in 2026, showing that wearable chip design is moving toward stronger local inference capability and more direct hardware differentiation. The AI in wearable health market should keep benefiting as low-power NPUs become standard in watches, rings, and medical sensors, because the hardware base then supports richer models without depending on the cloud.

Shift to Value-Based Care and Remote Patient Monitoring Reimbursement

The AI in wearable health market is also being pulled forward by reimbursement reform that makes short-duration monitoring economically workable for providers. CMS finalized new RPM and parallel RTM supply coding under the CY 2026 Medicare Physician Fee Schedule, allowing billing for as few as 2 to 15 monitoring days in a 30-day period at the same reimbursement level as the earlier 16-day minimum threshold. That change increases eligibility for post-discharge care, acute episodes, and lower-adherence patients who often failed to qualify under the prior standard. It also improves the case for episodic wearable deployment, which had weak economics when reimbursement depended on longer data collection windows. The same CMS rule recognizes device supply cost using a methodology that captures software, storage, and cybersecurity inputs, which is important for the AI in wearable health market because much of the value sits in software rather than the physical sensor.

Uncertain Regulatory Pathways for AI-Driven Clinical Claims

The AI in wearable health market still faces slower commercialization when companies want to attach formal clinical claims to AI-driven outputs. The FDA published draft guidance in January 2025 on lifecycle management and marketing submissions for AI-enabled device software functions, but most wearable products still move through existing 510(k) or De Novo routes instead of a dedicated AI-device pathway. That creates friction because many newer algorithms evolve faster than the available predicate base. Incumbents with cleared predicates and prior submission experience can usually manage that uncertainty better than startups building novel algorithms from scratch. The AI in wearable health market therefore risks seeing its most clinically ambitious entrants slowed by regulatory process even while demand for higher-acuity applications keeps rising.

Other drivers and restraints analyzed in the detailed report include:

1. Consumer Demand for Preventive Health and Wellness Insights
2. On-Device Foundation Models Enabling Multimodal Vitals Interpretation
3. Battery-Life Limitations Constrain Always-On Inference

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Smartwatches held 43.44% of AI in wearable health market share in 2025, which kept them as the largest device category because they combine wide consumer familiarity with broad health feature sets. They remain the main access point for ECG, blood oxygen, and hypertension-related monitoring in the AI in wearable health market. A 2024 meta-analysis published in the American Journal of Cardiology series reported 94.8% sensitivity and 95% specificity for the Apple Watch ECG app in atrial fibrillation detection across 4,241 participants. Fitness bands still matter in cost-sensitive settings because they offer a lower entry price for basic health monitoring and support broader penetration in emerging consumer segments. Hearables are also widening the device mix as audio products add medically relevant testing and interpretation.

Medical-grade wearables are projected to expand at 21.69% CAGR through 2031, making them the fastest-growing device segment in the AI in wearable health market. University of Chicago researchers also demonstrated a stretchable AI patch in 2026 that executes inference directly on the body, which points to a longer-term shift toward textile and patch form factors with embedded local intelligence. Those developments show that future growth in the AI in wearable health industry will come from devices designed for continuous care pathways rather than only daily wellness tracking.

Software accounted for 59.53% of the AI in wearable health market size in 2025, which reflects the pricing power of algorithms, clinical applications, and analytics layers relative to device manufacturing. That revenue structure shows where margins and customer lock-in are strongest in the AI in wearable health market. Research published in Healthcare in 2025 found that combining AI, EHR, and wearable data through HL7 FHIR and SMART on FHIR supports predictive and patient-centered decision support in clinical settings. As interoperability improves, software becomes the layer that turns biosignals into triage flags, workflow prompts, and documentation-ready outputs.

Hardware is anticipated to be the fastest-growing component, with 21.78% CAGR projected through 2031, because the AI in the wearable health market now depends on more capable local processing and better power management. The AI in wearable health market therefore treats hardware as more than a low-margin shell, because sensor layout, NPU performance, and power design are becoming core competitive inputs. Even when revenue concentration sits in software, platform-level control is still shaped by hardware choices that determine what kind of model can run continuously and how long the device can stay on the body.

Complete Report Scope:

• By Device Type
  • Smartwatches
  • Fitness Bands
  • Hearables
  • Smart Clothing and Patches
  • Medical-Grade Wearables
  • Other Device Types
• By Component
  • Software
  • Hardware
• By Application
  • Remote Patient Monitoring
  • Chronic Disease Management
  • Sports and Fitness Monitoring
  • Clinical and Diagnostic Monitoring
  • Other Applications
• By AI Algorithm
  • Machine Learning and Predictive Analytics
  • Deep Learning
  • Edge AI and Embedded Intelligence
  • Multimodal AI (sensor fusion)
• By End-User
  • Individual Users
  • Healthcare Providers
  • Long-Term Care and Home Healthcare Providers
  • Employers and Corporate Wellness Programs
  • Payers and Insurance Companies
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • Germany
    • United Kingdom
    • France
    • Italy
    • Spain
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • India
    • Australia
    • South Korea
    • Rest of Asia-Pacific
  • Middle East and Africa
    • GCC
    • South Africa
    • Rest of Middle East and Africa
  • South America
    • Brazil
    • Argentina
    • Rest of South America

Geography Analysis

North America held 54.19% of AI in wearable health market share in 2025, which kept it as the clear revenue leader. The region benefits from concentrated device leadership, deeper insurance infrastructure, and a more established path for digital health reimbursement. The FDA continued shaping market behavior through lifecycle guidance and change-control expectations for AI-enabled software functions, which gave manufacturers more direction on post-market model management. Canada and Mexico are growing contributors, but the United States still anchors regional demand because most reimbursement, platform development, and clinical integration activity remains centered there.

Asia-Pacific is projected to grow at 23.24% CAGR through 2031, making it the fastest-growing region in the AI in wearable health market. China's policy-backed focus on digital health and remote care is helping move wearables closer to formal healthcare delivery, especially where connectivity and hospital information systems are improving. Japan is also becoming more important because remote care need is rising against physician shortages and because consumer devices with diagnostic features are gaining more attention.

Europe held a meaningful but secondary position in the AI in wearable health market during 2025. Germany remained one of the more mature markets, supported by wider digital health adoption and stronger healthcare IT readiness. The EU AI Act is shaping deployment choices by prohibiting workplace emotion recognition, which limits some enterprise wearable use cases and pushes vendors to focus more clearly on clinical and wellness boundaries. The European Health Data Space and related FHIR-based interoperability efforts may be a short-term compliance burden, but they also support longer-term scaling by making wearable data easier to integrate into formal care systems. South America and the Middle East and Africa remain early-stage contributors, with Brazil and the GCC serving as the main entry points for digital health expansion.

1. Abbott Laboratories
2. AliveCor
3. Alphabet Inc.
4. Amazon.com
5. Apple
6. BioIntelliSense Inc.
7. Dexcom
8. Garmin
9. Huawei Technologies Co. Ltd.
10. Masimo
11. Medtronic
12. NeuroSky Inc.
13. OMRON
14. Oura Health Oy
15. Koninklijke Philips
16. Samsung Group
17. Senseonics
18. Valencell Inc.
19. Withings SA
20. Xiaomi Corporation

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 Introduction

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 Research Methodology

3 Executive Summary

4 Market Landscape

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Continuous Miniaturization of Low-Power AI Chipsets
  • 4.2.2 Integration of Wearable Data Into EHR/EMR Ecosystems
  • 4.2.3 Shift to Value-Based Care and Remote Patient Monitoring Reimbursement
  • 4.2.4 Consumer Demand for Preventive Health and Wellness Insights
  • 4.2.5 Federated Learning Rollouts to Solve Privacy-Regulated Data Scarcity
  • 4.2.6 On-Device Foundation Models Enabling Multimodal Vitals Interpretation
• 4.3 Market Restraints
  • 4.3.1 Uncertain Regulatory Pathways for AI-Driven Clinical Claims
  • 4.3.2 Battery-Life Limitations Constrain Always-On Inference
  • 4.3.3 Edge-AI Model Drift Caused by Sensor Degradation Over Time
  • 4.3.4 Ethical Concerns Around Emotion-Recognition Wearables in Workplaces
• 4.4 Supply/Value Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Porter's Five Forces Analysis
  • 4.7.1 Threat of New Entrants
  • 4.7.2 Bargaining Power of Suppliers
  • 4.7.3 Bargaining Power of Buyers
  • 4.7.4 Threat of Substitutes
  • 4.7.5 Competitive Rivalry

5 Market Size & Growth Forecasts (Value, USD)

• 5.1 By Device Type
  • 5.1.1 Smartwatches
  • 5.1.2 Fitness Bands
  • 5.1.3 Hearables
  • 5.1.4 Smart Clothing and Patches
  • 5.1.5 Medical-Grade Wearables
  • 5.1.6 Other Device Types
• 5.2 By Component
  • 5.2.1 Software
  • 5.2.2 Hardware
• 5.3 By Application
  • 5.3.1 Remote Patient Monitoring
  • 5.3.2 Chronic Disease Management
  • 5.3.3 Sports and Fitness Monitoring
  • 5.3.4 Clinical and Diagnostic Monitoring
  • 5.3.5 Other Applications
• 5.4 By AI Algorithm
  • 5.4.1 Machine Learning and Predictive Analytics
  • 5.4.2 Deep Learning
  • 5.4.3 Edge AI and Embedded Intelligence
  • 5.4.4 Multimodal AI (sensor fusion)
• 5.5 By End-User
  • 5.5.1 Individual Users
  • 5.5.2 Healthcare Providers
  • 5.5.3 Long-Term Care and Home Healthcare Providers
  • 5.5.4 Employers and Corporate Wellness Programs
  • 5.5.5 Payers and Insurance Companies
• 5.6 By Geography
  • 5.6.1 North America
    • 5.6.1.1 United States
    • 5.6.1.2 Canada
    • 5.6.1.3 Mexico
  • 5.6.2 Europe
    • 5.6.2.1 Germany
    • 5.6.2.2 United Kingdom
    • 5.6.2.3 France
    • 5.6.2.4 Italy
    • 5.6.2.5 Spain
    • 5.6.2.6 Rest of Europe
  • 5.6.3 Asia-Pacific
    • 5.6.3.1 China
    • 5.6.3.2 Japan
    • 5.6.3.3 India
    • 5.6.3.4 Australia
    • 5.6.3.5 South Korea
    • 5.6.3.6 Rest of Asia-Pacific
  • 5.6.4 Middle East and Africa
    • 5.6.4.1 GCC
    • 5.6.4.2 South Africa
    • 5.6.4.3 Rest of Middle East and Africa
  • 5.6.5 South America
    • 5.6.5.1 Brazil
    • 5.6.5.2 Argentina
    • 5.6.5.3 Rest of South America

6 Competitive Landscape

• 6.1 Market Concentration
• 6.2 Market Share Analysis
• 6.3 Company Profiles (includes Global level Overview, Market level overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share for key companies, Products & Services, Recent Developments)
  • 6.3.1 Abbott Laboratories
  • 6.3.2 AliveCor Inc.
  • 6.3.3 Alphabet Inc.
  • 6.3.4 Amazon.com Inc.
  • 6.3.5 Apple Inc.
  • 6.3.6 BioIntelliSense Inc.
  • 6.3.7 Dexcom Inc.
  • 6.3.8 Garmin Ltd.
  • 6.3.9 Huawei Technologies Co. Ltd.
  • 6.3.10 Masimo Corporation
  • 6.3.11 Medtronic plc
  • 6.3.12 NeuroSky Inc.
  • 6.3.13 Omron Healthcare Inc.
  • 6.3.14 Oura Health Oy
  • 6.3.15 Philips Healthcare
  • 6.3.16 Samsung Electronics Co. Ltd.
  • 6.3.17 Senseonics Holdings Inc.
  • 6.3.18 Valencell Inc.
  • 6.3.19 Withings SA
  • 6.3.20 Xiaomi Corporation

7 Market Opportunities & Future Outlook

• 7.1 White-space & Unmet-need Assessment