자동 인슐린 투여 시스템 시장 : 제품 유형, 컴포넌트, 인슐린 유형, 기술, 당뇨병 유형, 케어 환경, 최종 사용자, 유통 채널별 예측(2026-2032년)

The Automated Insulin Delivery System Market is projected to grow by USD 1,942.07 million at a CAGR of 10.09% by 2032.

Automated insulin delivery systems, often described as hybrid closed-loop or artificial pancreas systems, combine an insulin pump, continuous glucose monitor (CGM), dosing algorithm, and connected software to adjust insulin delivery based on real-time glucose trends. The category has moved from early type 1 diabetes innovation to a core diabetes technology segment as clinical evidence, regulatory clearances, and payer recognition expand.

Demand is grounded in a large and rising diabetes burden. The International Diabetes Federation estimated that 537 million adults were living with diabetes in 2021 and projected 643 million by 2030 and 783 million by 2045. While automated insulin delivery is most established in type 1 diabetes, interest is widening as clinicians, payers, and device developers evaluate how connected insulin management can reduce hypoglycemia, improve time in range, and support safer self-management.

Transformative Shifts in the AID Landscape

The automated insulin delivery landscape is shifting from device-centric innovation to integrated diabetes management ecosystems. Competition is increasingly shaped not only by pump hardware, but also by CGM interoperability, algorithm performance, mobile app usability, remote monitoring, cloud analytics, customer support, cybersecurity, and data integration with clinical workflows.

Regulatory and reimbursement changes are accelerating adoption. The U.S. FDA's interoperable pathways for integrated CGMs, alternate controller enabled pumps, and automated glycemic controllers have encouraged modular system development, while broader CGM coverage in the United States has strengthened the installed base needed for AID uptake. In Europe, the transition to the Medical Device Regulation has raised evidence and post-market surveillance expectations, and the United Kingdom's NICE recommendation for hybrid closed-loop systems in type 1 diabetes has reinforced the value case for clinically appropriate patients.

Cumulative Impact of Artificial Intelligence

Artificial intelligence is reshaping automated insulin delivery through better personalization, predictive decision support, and population-level analytics. Current commercial AID systems rely on control algorithms that adjust basal insulin and, in some platforms, deliver correction boluses; the next wave is expected to use machine learning more extensively to identify patterns related to meals, exercise, stress, illness, sleep, and adherence.

The cumulative impact of AI will depend on evidence quality and safety governance. FDA guidance on predetermined change control plans for AI-enabled medical devices signals a pathway for controlled algorithm updates, but manufacturers must prove that adaptive features improve outcomes without increasing hypoglycemia risk. AI can also support customer service triage, device failure prediction, clinician dashboards, and behavioral coaching, creating value beyond the dosing algorithm itself.

Key Regional Insights

North America remains the most mature region for automated insulin delivery, led by the United States, where FDA-cleared AID systems, high CGM use, advanced endocrinology networks, and commercial as well as public payer coverage support adoption. Canada follows a more province-driven reimbursement model, creating uneven but improving access for insulin pump therapy, CGMs, and hybrid closed-loop systems.

Europe is a major clinical and regulatory market, with Germany, France, Italy, Spain, and the United Kingdom shaping adoption through national health systems, health technology assessment reviews, diabetes registries, and CE-marked device availability. The region's Medical Device Regulation has increased expectations for clinical evidence, post-market surveillance, software validation, and data protection, making compliance strength a central differentiator.

Asia-Pacific is the fastest-developing opportunity as China, Japan, India, South Korea, and Australia combine large diabetes populations with expanding digital health infrastructure. Japan, South Korea, and Australia benefit from advanced specialist care and stronger CGM familiarity, while China and India present broad unmet need but face affordability, reimbursement, and diabetes educator capacity constraints. Latin America, the Middle East, and Africa show rising demand in private care and urban diabetes centers; however, reimbursement gaps, supply continuity, clinician training, and uneven access to sensors and infusion consumables limit broader use.

Key Group Insights

Within ASEAN, automated insulin delivery adoption is concentrated in private hospitals and specialist diabetes clinics in markets such as Singapore, Malaysia, and Thailand, while broader access depends on reimbursement expansion, diabetes educator capacity, and continuity of CGM and infusion set supply. GCC countries are attractive due to high diabetes prevalence, strong private-sector purchasing, and government digital health programs, particularly in Saudi Arabia and the United Arab Emirates, where connected care initiatives support remote monitoring and specialist-led diabetes management.

The European Union offers scale through harmonized CE-mark access, but country-level reimbursement and health technology assessment decisions still determine uptake. BRICS markets present significant long-term adoption potential because of population size, rising diabetes diagnosis, and increasing CGM awareness, although local pricing, distribution, regulatory approvals, and domestic manufacturing strategies are decisive. G7 countries remain the highest-value commercialization group because of advanced clinical guidelines, mature device regulation, established payer capacity, and stronger real-world evidence infrastructure. NATO markets overlap significantly with Europe and North America and increasingly emphasize procurement resilience, cybersecurity, data privacy, and supply-chain reliability for connected medical devices.

Key Country Insights

The United States is the global adoption leader for automated insulin delivery, supported by FDA-cleared systems, strong CGM use, established endocrinology networks, and a large treated type 1 diabetes population. Canada shows steady uptake, but reimbursement varies by province and affects access to pumps, CGMs, and consumables. Mexico and Brazil represent important Latin American opportunities where private-pay channels, major urban endocrinology centers, and growing awareness of diabetes technology lead adoption before broader public reimbursement develops.

In Europe, the United Kingdom is positioned for faster public-sector scale following NICE guidance for hybrid closed-loop use in type 1 diabetes, while Germany, France, Italy, and Spain are shaped by national reimbursement processes, hospital-led diabetes technology programs, and clinician training capacity. Russia remains more limited by regulatory, import, supply-chain, and reimbursement conditions, which can restrict access to advanced connected diabetes devices.

China offers large long-term potential due to population scale, rising diabetes diagnosis, digital health adoption, and domestic medtech investment, while India combines substantial unmet need with affordability challenges and uneven specialist access. Japan, South Korea, and Australia have advanced clinical infrastructures and strong CGM familiarity, making them important countries for premium systems, pediatric use, remote monitoring, and real-world evidence generation.

Actionable Recommendations for Industry Leaders

Industry leaders should prioritize interoperability, payer evidence, and patient-centered design. Systems that reduce user burden, support multiple CGM options, integrate with smartphones, and provide secure remote monitoring are better positioned as diabetes care shifts toward connected, outcomes-based management.

Manufacturers should invest in real-world evidence that demonstrates time-in-range improvement, hypoglycemia reduction, quality-of-life gains, and health-economic value. Commercial strategies should segment countries by reimbursement maturity, develop clinician and diabetes educator training programs, localize onboarding support, and build resilient supply chains for sensors, infusion sets, reservoirs, batteries, software updates, and replacement devices.

Research Methodology

Research methodology is developed using a secondary and triangulated research approach focused on verified public sources, clinical evidence, regulatory databases, and health-system policy signals. Key reference categories include International Diabetes Federation diabetes prevalence estimates, U.S. CDC diabetes statistics, FDA device classification and clearance pathways, NICE guidance, ADA Standards of Care, peer-reviewed trials, regulatory notices, reimbursement policies, and public clinical practice guidance.

Market interpretation is built by comparing disease burden, CGM penetration, reimbursement maturity, regulatory readiness, clinical infrastructure, diabetes educator availability, digital health adoption, cybersecurity expectations, and supply-chain conditions across regions and countries. Insights are validated through consistency checks across clinical outcomes, payer policy, device availability, regulatory pathways, and adoption barriers rather than relying on a single indicator.

Conclusion

Automated insulin delivery is becoming a defining technology in modern insulin-dependent diabetes care. The sector is supported by rising diabetes prevalence, strong clinical evidence for improved glycemic control, expanding CGM use, and regulatory frameworks that increasingly recognize interoperable digital medical devices.

The next phase of adoption will be determined by affordability, reimbursement, AI-enabled personalization, cybersecurity, supply continuity, clinical training, and ease of use. Organizations that combine clinically proven algorithms with patient-friendly design, scalable support models, interoperable platforms, and robust real-world evidence will be best positioned to advance the global automated insulin delivery ecosystem.

Table of Contents

1. Preface

• 1.1. Objectives of the Study
• 1.2. Market Definition
• 1.3. Market Segmentation & Coverage
• 1.4. Years Considered for the Study
• 1.5. Currency Considered for the Study
• 1.6. Language Considered for the Study
• 1.7. Key Stakeholders

2. Research Methodology

• 2.1. Introduction
• 2.2. Research Design
  • 2.2.1. Primary Research
  • 2.2.2. Secondary Research
• 2.3. Research Framework
  • 2.3.1. Qualitative Analysis
  • 2.3.2. Quantitative Analysis
• 2.4. Market Size Estimation
  • 2.4.1. Top-Down Approach
  • 2.4.2. Bottom-Up Approach
• 2.5. Data Triangulation
• 2.6. Research Outcomes
• 2.7. Research Assumptions
• 2.8. Research Limitations

3. Executive Summary

• 3.1. Introduction
• 3.2. CXO Perspective
• 3.3. Market Size & Growth Trends
• 3.4. Market Share Analysis, 2025
• 3.5. FPNV Positioning Matrix, 2025
• 3.6. New Revenue Opportunities
• 3.7. Next-Generation Business Models
• 3.8. Industry Roadmap

4. Market Overview

• 4.1. Introduction
• 4.2. Industry Ecosystem & Value Chain Analysis
  • 4.2.1. Supply-Side Analysis
  • 4.2.2. Demand-Side Analysis
  • 4.2.3. Stakeholder Analysis
• 4.3. Market Dynamics
  • 4.3.1. Key Drivers
  • 4.3.2. Key Restraints
  • 4.3.3. Key Opportunities
  • 4.3.4. Key Challenges
• 4.4. Porter's Five Forces Analysis
• 4.5. PESTLE Analysis
• 4.6. Market Outlook
  • 4.6.1. Near-Term Market Outlook (0-2 Years)
  • 4.6.2. Medium-Term Market Outlook (3-5 Years)
  • 4.6.3. Long-Term Market Outlook (5-10 Years)
• 4.7. Go-to-Market Strategy

5. Market Insights

• 5.1. Consumer Insights & End-User Perspective
• 5.2. Consumer Experience Benchmarking
• 5.3. Opportunity Mapping
• 5.4. Distribution Channel Analysis
• 5.5. Pricing Trend Analysis
• 5.6. Regulatory Compliance & Standards Framework
• 5.7. ESG & Sustainability Analysis
• 5.8. Disruption & Risk Scenarios
• 5.9. Return on Investment & Cost-Benefit Analysis

6. Cumulative Impact of Artificial Intelligence 2026

7. Automated Insulin Delivery System Market, by Product Type

• 7.1. Fully Closed Loop
• 7.2. Hybrid Closed Loop
  • 7.2.1. Fuzzy Logic
  • 7.2.2. Model Predictive Control
  • 7.2.3. Proportional Integral Derivative
• 7.3. Sensor Augmented Pump
• 7.4. Threshold Suspend Pump

8. Automated Insulin Delivery System Market, by Component

• 8.1. Continuous Glucose Monitor
  • 8.1.1. Flash Monitoring
  • 8.1.2. Real Time
• 8.2. Control Algorithm Software
  • 8.2.1. Cloud Based
  • 8.2.2. Mobile Based
• 8.3. Pump
  • 8.3.1. Patch Pump
  • 8.3.2. Tubed Pump

9. Automated Insulin Delivery System Market, by Insulin Type

• 9.1. Rapid Acting
  • 9.1.1. Aspart
  • 9.1.2. Glulisine
  • 9.1.3. Lispro
• 9.2. Regular U100
• 9.3. Ultra Rapid
  • 9.3.1. Fiasp
  • 9.3.2. Lyumjev

10. Automated Insulin Delivery System Market, by Technology

• 10.1. Bluetooth Based
  • 10.1.1. BLE 5.0
  • 10.1.2. Legacy BLE
• 10.2. Cellular Based
• 10.3. WiFi Based
  • 10.3.1. 2.4 GHz
  • 10.3.2. 5 GHz

11. Automated Insulin Delivery System Market, by Diabetes Type

• 11.1. Gestational
• 11.2. Type 1
  • 11.2.1. Juvenile Onset
  • 11.2.2. Late Autoimmune
• 11.3. Type 2
  • 11.3.1. Insulin Dependent
  • 11.3.2. Non Insulin Dependent

12. Automated Insulin Delivery System Market, by Care Setting

• 12.1. Inpatient
  • 12.1.1. General Ward
  • 12.1.2. Intensive Care Unit
• 12.2. Outpatient
  • 12.2.1. Ambulatory Daycare
  • 12.2.2. Specialty Clinic

13. Automated Insulin Delivery System Market, by End User

• 13.1. Ambulatory
• 13.2. Clinics
• 13.3. Homecare
  • 13.3.1. Adult Users
  • 13.3.2. Pediatric Users
• 13.4. Hospital
  • 13.4.1. Ambulatory Surgical Centers
  • 13.4.2. Inpatient

14. Automated Insulin Delivery System Market, by Distribution Channel

• 14.1. Offline Pharmacy
• 14.2. Online Pharmacy

15. Automated Insulin Delivery System Market, by Region

• 15.1. Asia-Pacific
• 15.2. North America
• 15.3. Latin America
• 15.4. Europe
• 15.5. Middle East
• 15.6. Africa

16. Automated Insulin Delivery System Market, by Group

• 16.1. ASEAN
• 16.2. GCC
• 16.3. European Union
• 16.4. BRICS
• 16.5. G7
• 16.6. NATO

17. Automated Insulin Delivery System Market, by Country

• 17.1. United States
• 17.2. Canada
• 17.3. Mexico
• 17.4. Brazil
• 17.5. United Kingdom
• 17.6. Germany
• 17.7. France
• 17.8. Russia
• 17.9. Italy
• 17.10. Spain
• 17.11. China
• 17.12. India
• 17.13. Japan
• 17.14. Australia
• 17.15. South Korea

18. Competitive Landscape

• 18.1. Market Concentration Analysis, 2025
  • 18.1.1. Concentration Ratio (CR)
  • 18.1.2. Herfindahl Hirschman Index (HHI)
• 18.2. Recent Developments & Impact Analysis, 2025
• 18.3. Product Portfolio Analysis, 2025
• 18.4. Benchmarking Analysis, 2025

19. Company Profiles

• 19.1. Abbott Laboratories
• 19.2. Ascensia Diabetes Care Holdings AG
• 19.3. Becton, Dickinson and Company
• 19.4. Beta Bionics, Inc.
• 19.5. Bigfoot Biomedical, Inc.
• 19.6. CamDiab Limited
• 19.7. Cellnovo Group S.A.
• 19.8. Companion Medical, Inc.
• 19.9. Dexcom, Inc.
• 19.10. Diabeloop S.A.
• 19.11. DreaMed Diabetes Ltd.
• 19.12. Eli Lilly and Company
• 19.13. EOFlow Co., Ltd.
• 19.14. F. Hoffmann-La Roche Ltd
• 19.15. Glooko, Inc.
• 19.16. i-SENS, Inc.
• 19.17. Insulcloud S.L.
• 19.18. Insulet Corporation
• 19.19. Medtronic plc
• 19.20. Medtrum Technologies Inc.
• 19.21. MicroTech Medical (Hangzhou) Co., Ltd.
• 19.22. Novo Nordisk A/S
• 19.23. Pancreum, Inc.
• 19.24. Pendiq GmbH
• 19.25. Roche Diabetes Care GmbH
• 19.26. Sanofi S.A.
• 19.27. Senseonics Holdings, Inc.
• 19.28. Sequel Med Tech, LLC
• 19.29. Sinocare Inc.
• 19.30. SOOIL Development Co., Ltd.
• 19.31. Tandem Diabetes Care, Inc.
• 19.32. Tidepool Project
• 19.33. TypeZero Technologies, LLC
• 19.34. Valeritas Holdings, Inc.
• 19.35. Ypsomed Holding AG