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糖尿病管理市場中的人工智慧（按設備類型、技術、最終用戶、部署模式、類型和組件）—2025-2032 年全球預測

Artificial Intelligence in Diabetes Management Market by Device Type, Technology, End User, Deployment Mode, Type, Component - Global Forecast 2025-2032
出版日期: | 出版商: 360iResearch | 英文 183 Pages | 商品交期: 最快1-2個工作天內

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預計到 2032 年，糖尿病管理人工智慧市場規模將成長至 90.4 億美元，複合年成長率為 31.57%。

主要市場統計數據
基準年2024年 10億美元
預計2025年 13.2億美元
預測年份：2032年 90.4億美元
複合年成長率（%） 31.57%

一篇引人入勝的介紹，將人工智慧作為重塑糖尿病照護提供途徑中的臨床實踐和病人參與的戰略力量

人工智慧、數位健康整合和新型設備架構正在迅速改變糖尿病管理的臨床和商業性格局。本介紹將幫助您了解人工智慧工具如何從試點階段發展到主流臨床工作流程，進而影響護理路徑、病人參與和系統級效能。此外，本介紹也展示了技術成熟度、法規演變和相關人員期望變化的相互作用如何塑造短期應用動態。

相關人員閱讀本報告時會發現，報告的結構旨在強調實際意義，而非純粹的理論進展。臨床醫生和醫療服務提供者必須評估預測分析和決策支援系統將如何改變照護現場決策，而支付方和管理者則必須考慮遠端監控和閉合迴路解決方案對營運和資金籌措的影響。同時，患者越來越期待無縫的、智慧型手機主導的體驗，以減輕日常管理負擔並提供切實可行的洞察。因此，本導言將人工智慧定位為一個跨裝置、軟體和護理模式的乘數效應，而非一項獨立的創新，這為後續章節設定了明確的預期，這些章節將分析變革性轉變、細分市場、區域動態和實用建議。

對人工智慧和互聯護理系統轉變的權威分析，這些轉變正在重新定義糖尿病管理中的臨床實踐模式、報銷設計和患者期望

近年來，隨著人工智慧和連網型設備的融合，糖尿病管理格局發生了顯著變化，創造了新的護理標準。臨床團隊擴大採用持續監測和演算法主導的胰島素劑量，以減少差異性並實現個人化治療。同時，匯總生理和行為數據的軟體平台正在實現更具預防性和主動性的干涉措施。這些轉變反映了一個新興的生態系統，在這個生態系統中，硬體進步、即時分析和雲端工作流程相互作用，從而對血糖控制和風險軌跡產生更高解析度的洞察。

此外，法律規範和報銷政策正在根據臨床效益和營運價值的證據進行調整。因此，供應商的策略正在從銷售獨立設備轉向整合感測器、演算法和護理協調服務的整合解決方案。患者的期望也在不斷演變：便利性、與消費性設備的互通性以及透明的數據共用方法如今影響著產品的採用。總而言之，這些動態正在加速糖尿病管理從以門診為中心的偶發性護理轉向強調預防、個人化和系統級效率的持續性數據主導護理的轉變。

嚴格檢驗自 2025 年起生效的美國累積關稅如何改變整個糖尿病生態系統的供應鏈籌資策略和產品開發重點

美國將於2025年加徵累積關稅，這給整個糖尿病護理設備和軟體供應鏈帶來了明顯的壓力，也促使製造商制定了相應的戰略應對措施。目前，關稅增加了進口零件和成品的投入成本，促使製造商重新評估籌資策略，並盡可能加快供應鏈本地化進程。這促使他們仔細審查供應商關係和合約條款，採購團隊強調雙重採購、更長的交貨期規劃和前置作業時間彈性，以減輕持續貿易政策波動的風險。

同時，由於成本上限和利潤預期的變化，產品開發和商業化時間表也面臨壓力。一些供應商為了保持競爭力而消化了成本上漲，而另一些供應商則重新評估了價格或推遲了非關鍵投資。對於以軟體為中心的產品，雲端託管和跨境資料傳輸安排需要重新進行法律和合規審查，以確保與不斷變化的貿易和資料政策保持一致。從中期來看，關稅成為國內製造產能和戰略夥伴關係關係投資的催化劑，這些投資優先考慮近岸外包，加強區域供應鏈，並為本地供應商和委託製造創造有條件的機會，使其能夠根據需求擴大業務規模。

深度細分洞察，整合設備外形規格、技術堆疊、最終用戶配置、部署方式、疾病亞型和組件優先級，以揭示可行的採用潛力

細分洞察需要詳細了解設備外形規格、支援技術、使用者偏好、部署模型、疾病類型和組件優先順序如何相互作用，從而影響其採用和臨床效果。從設備角度來看，血糖儀仍然適用於自我監測和非侵入式用例，而更先進的連續血糖監測系統和胰島素輸送機制則支援閉合迴路自動化，以減輕日常負擔。間歇掃描監測器和即時連續監測器、貼片幫浦和管式幫浦之間的差異，導致了不同的使用者體驗和整合要求，而全閉合迴路系統比混合配置需要更高的互通性和監管保證。

技術選擇至關重要，因為雲端運算選項、決策支援模組、機器學習方法、行動應用平台和預測分析功能決定了擴充性和臨床效用。公共雲端和私有雲端架構決定資料管治和延遲特徵，決策支援功能涵蓋從警報產生到藥物推薦等各個面向。使用監督、非監督或強化方法的機器學習實施會導致不同的檢驗需求和臨床醫生採用路徑。診所和糖尿病中心優先考慮工作流程整合和專家支持，醫院強調住院和門診的連續性，居家醫療優先考慮遠端和自我監控的便利性，研究機構尋求靈活的資料存取以進行假設檢驗。雲端基礎的部署與本地部署在擴充性和控制之間產生權衡，混合部署越來越普遍。疾病類型細分，例如具有特殊需求的產前護理、成人與早發性 1 型或胰島素依賴型與非胰島素依賴型 2 型隊列，可為臨床方案和設備選擇提供資訊。最後，泵浦和感測器等硬體元素與演算法和使用者介面等軟體功能之間的組件級分類凸顯了投資和監管監督的重點。

全面的區域見解，詳細說明美洲、歐洲、中東和非洲以及亞太地區的動態將如何影響糖尿病解決方案所採用的監管和商業策略

區域動態正在從根本上塑造糖尿病管理的採用途徑、報銷方式和供應鏈架構。在美洲，醫療系統對基於價值的模型和遠端監控功能表現出強烈的需求，推動了支付方對以結果為導向的夥伴關係關係和能夠帶來可衡量的患者層面改善的產品的興趣。在北美，醫療設備軟體監管的明確性正在鼓勵在綜合醫療服務網路中進行試點部署，而商業性支付方的動態正在影響解決方案的打包和報銷方式。

在歐洲、中東和非洲，異質的法規環境和多樣化的醫療服務交付環境需要製定適應性打入市場策略，以應對各國報銷模式、隱私標準和基礎設施的差異。尋求在該地區滲透的製造商必須最佳化互通性和本地化，在集中式雲端架構與本地部署或邊緣運算之間取得平衡，因為頻寬和資料主權是這些領域的主要關注點。在亞太地區，技術的快速採用、智慧型手機的高普及率以及公共對數位醫療的不斷投資，為可擴展的人工智慧解決方案創造了肥沃的土壤。這些地區差異加在一起，需要差異化的商業性模式、策略夥伴關係和監管合作計畫。

公司層面的策略洞察揭示了競爭定位、夥伴關係模式、投資重點和能力，這些決定了人工智慧糖尿病護理領域的長期領導地位。

競爭格局由多種因素構成：成熟的醫療設備製造商正在向軟體賦能醫療領域擴張；科技公司提供分析和平台服務；以及新興參與企業專注於細分市場的病患體驗和演算法創新。市場領導企業強調融合感測硬體、雲端基礎分析和臨床醫生決策支援的整合產品組合，而中介軟體供應商則專注於連接不同設備和電子健康記錄的互通性層。同時，軟體優先型公司則透過演算法的複雜性和使用者介面設計實現差異化，旨在提升消費者參與度並增強臨床醫生的工作流程。

投資者和策略合作夥伴也透過優先考慮那些擁有可靠臨床證據、可擴展部署模式和清晰報銷路徑的公司來影響創新軌跡。設備原始設備製造商 (OEM) 與雲端或分析供應商之間的合作仍然是加快上市時間和拓展服務範圍的領先策略。評估其競爭定位的公司應專注於產品模組化、資料管治實踐、監管準備以及展示有意義的真實世界臨床結果的能力。

為行業領導者提供行動建議，以建立有彈性的商業模式，加速採用、建立信任並推動可衡量的臨床結果

產業領導者應採取一系列切實可行的行動，將技術前景轉化為可衡量的臨床和商業性成果。首先，優先考慮互通性和開放標準，以便設備和分析技術能夠整合到多樣化的臨床工作流程和電子健康記錄中。這種方法將促進多供應商生態系統的發展，減少供應商採用過程中的摩擦，並擴大患者的選擇範圍。其次，投資嚴格的臨床檢驗，將演算法輸出與臨床醫生判定和患者報告的結果相結合，以建立信任並支持報銷討論。這些證據對於將試點計畫納入標準護理路徑至關重要。

第三，採取策略提升供應鏈韌性，例如雙重採購、在適當情況下進行近岸外包，以及靈活調整合約以適應貿易政策的變化。第四，設計定價和報銷模式，使醫療服務提供者、付款人和患者的獎勵機制保持一致，優先考慮與控制改善和急性事件減少相關的基於價值的安排。第五，發展以使用者為中心的介面和行動體驗，以減輕患者和臨床醫生的認知負擔，並確保依從性和持續參與。最後，在硬體、軟體和臨床領域建立策略夥伴關係關係，以加速創新，同時降低執行風險。

一種透明的混合方法研究途徑，將專家訪談與文獻綜合和嚴格檢驗相結合，以產生可操作、可複製的見解

支撐本分析的調查方法結合了定性和定量分析，以確保研究的穩健性、三角測量和實用性。主要研究包括對臨床醫生、產品負責人、採購負責人和監管專家的深入訪談，以及專家圓桌討論，探討臨床應用和商業性途徑的障礙。次要研究則考察了同行評審文獻、監管指南、臨床試驗註冊中心和公司資訊披露，以整合主要研究的發現，並確定常見的技術趨勢和檢驗方法。

資料合成採用主題分析法進行定性輸入，並採用結構化架構評估技術就緒性、互通性和經營模式可行性。在適用的情況下，訪談結果與已備案的監管文件和公開的臨床證據進行交叉引用。倫理考量是調查方法的核心，並已獲得訪談參與者的知情同意，並在需要時進行仔細的去身分識別處理。研究結果強調可重複的推理、透明的假設和基於證據的結論，從而為戰略決策提供資訊，而無需依賴私人專有資料集。

簡潔的結論強調了在臨床檢驗互通性和商業設計方面採取協作行動的迫切需要，以實現人工智慧糖尿病護理的益處。

總而言之，人工智慧和連網型設備的創新正在融合，創造出一種截然不同的糖尿病護理模式，該模式強調持續監測、個人化胰島素給藥和數據主導的決策支援。積極主動地將產品設計、臨床檢驗和商業模式與不斷變化的監管和報銷格局相結合的相關人員，很可能獲得先發優勢。相反，將人工智慧視為護理路徑中一項功能而非不可或缺的組成部分的機構，則可能面臨應用受限和影響零散的風險。

未來發展需要設備製造商、軟體供應商、臨床醫生、支付者和政策制定者之間的通力合作，確保技術進步轉化為真正的臨床效益。透過利用互通性、優先生成可靠的證據以及設計永續的經營模式，糖尿病行業可以加速從被動管理向主動個性化糖尿病護理的轉變，從而改善治療效果並減輕系統負擔。

目錄

第1章：前言

第2章調查方法

第3章執行摘要

第4章 市場概況

第5章 市場洞察

  • 將持續血糖監測數據與人工智慧預測演算法結合，根據即時生活方式模式個人化胰島素劑量
  • 將機器學習模型應用於穿戴式設備，以便早期發現高風險糖尿病患者的低血糖事件
  • 在虛擬健康助理中使用自然語言處理為糖尿病患者提供量身定做的飲食和藥物建議
  • 發展聯邦學習框架，用於跨多個機構訓練 AI 糖尿病管理模型，同時保護病患資料隱私
  • 推出一款人工智慧智慧型手機應用程式，利用電腦視覺技術自動識別膳食並推薦胰島素Bolus
  • 製藥和科技公司合作在大規模臨床試驗中檢驗人工智慧閉合迴路胰島素輸送系統

第6章：2025年美國關稅的累積影響

第7章：人工智慧的累積影響，2025年

8. 糖尿病管理市場中的人工智慧（按設備類型）

  • 血糖儀
    • 無創血糖儀
    • SMBG
  • 封閉回路型系統
    • 全閉迴路
    • 混合閉合迴路
  • 連續血糖監測儀
    • 間歇掃描CGM
    • 即時CGM
  • 胰島素幫浦
    • 貼片幫浦
    • 管泵

9. 糖尿病管理市場中的人工智慧（按技術）

  • 雲端運算
    • 私有雲端
    • 公共雲端
  • 決策支援系統
    • 警報生成
    • 建議劑量
  • 機器學習
    • 強化學習
    • 監督學習
    • 無監督學習
  • 行動應用程式
    • Android
    • iOS
  • 預測分析
    • 血糖值趨勢預測
    • 風險預測

第 10 章糖尿病管理市場中的人工智慧（按最終用戶分類）

  • 診所
    • 糖尿病中心
    • 一般醫學
  • 居家護理
    • 遠端監控
    • 自我監控
  • 醫院
    • 住院病人
    • 門診
  • 研究所
    • 學術的
    • 私人的

第 11 章糖尿病管理市場中的人工智慧（按部署模式）

  • 雲端基礎
    • 混合雲端
    • 公共雲端
  • 本地部署
    • 邊緣運算
    • 基於伺服器

第 12 章糖尿病管理市場中的人工智慧（按類型）

  • 懷孕
    • 妊娠早期
    • 第二個三個月
    • 妊娠晚期
  • 類型 1
    • 成人發病
    • 早發
  • 類型 2
    • 胰島素依賴型
    • 胰島素依賴型

13. 糖尿病管理市場中的人工智慧（按組成部分）

  • 硬體
    • 泵浦
    • 感應器
    • 穿戴式裝置
  • 軟體
    • 演算法
    • 資料管理
    • 使用者介面

14. 糖尿病管理人工智慧市場（按地區）

  • 美洲
    • 北美洲
    • 拉丁美洲
  • 歐洲、中東和非洲
    • 歐洲
    • 中東
    • 非洲
  • 亞太地區

第 15 章糖尿病管理市場中的人工智慧（按群體）

  • ASEAN
  • GCC
  • EU
  • BRICS
  • G7
  • NATO

16. 糖尿病管理人工智慧市場（按國家）

  • 美國
  • 加拿大
  • 墨西哥
  • 巴西
  • 英國
  • 德國
  • 法國
  • 俄羅斯
  • 義大利
  • 西班牙
  • 中國
  • 印度
  • 日本
  • 澳洲
  • 韓國

第17章競爭格局

  • 2024年市佔率分析
  • 2024年FPNV定位矩陣
  • 競爭分析
    • Medtronic plc
    • Abbott Laboratories
    • Dexcom, Inc.
    • F. Hoffmann-La Roche Ltd
    • Insulet Corporation
    • Tandem Diabetes Care, Inc.
    • Teladoc Health, Inc.
    • Omada Health, Inc.
    • Bigfoot Biomedical, Inc.
    • Glooko Inc.
Product Code: MRR-4369010656EF

The Artificial Intelligence in Diabetes Management Market is projected to grow by USD 9.04 billion at a CAGR of 31.57% by 2032.

KEY MARKET STATISTICS
Base Year [2024] USD 1.00 billion
Estimated Year [2025] USD 1.32 billion
Forecast Year [2032] USD 9.04 billion
CAGR (%) 31.57%

A compelling introduction that contextualizes artificial intelligence as a strategic force reshaping diabetes care delivery pathways clinical practice and patient engagement

The clinical and commercial landscape for diabetes management is undergoing a rapid transformation driven by artificial intelligence, digital health integration, and novel device architectures. This introduction sets the stage for understanding how AI-enabled tools are moving from experimental pilots to mainstream clinical workflows, influencing care pathways, patient engagement, and system-level performance. It also frames the interplay between technology maturation, regulatory evolution, and shifting stakeholder expectations that together are shaping near-term adoption dynamics.

As stakeholders read on, they will find the report structured to highlight practical implications rather than purely theoretical advances. Clinicians and provider organizations must now evaluate how predictive analytics and decision support systems change point-of-care decision-making, while payers and administrators weigh the operational and financing implications of remote monitoring and closed loop solutions. Meanwhile, patients increasingly expect seamless, smartphone-driven experiences that reduce daily management burden and provide actionable insights. This introduction therefore positions AI not as a standalone innovation but as a force multiplier acting across devices, software, and care models, setting clear expectations for the subsequent sections that analyze transformative shifts, segmentation, regional dynamics, and actionable recommendations.

An authoritative analysis of the systemic shifts driven by AI and connected care that are redefining clinical practice models reimbursement design and patient expectations in diabetes management

The last few years have revealed transformative shifts in the diabetes management landscape as AI and connected devices converge to create new standards of care. Clinical teams are increasingly adopting continuous monitoring and algorithm-driven insulin delivery to reduce variability and personalize therapy; concomitantly, software platforms that aggregate physiological and behavioral data enable more proactive, preventive interventions. These shifts reflect an emergent ecosystem in which hardware advances, real-time analytics, and cloud-enabled workflows interact to produce higher-resolution insight into glycemic control and risk trajectories.

Moreover, regulatory frameworks and reimbursement policies are beginning to adapt to evidence of clinical benefit and operational value. As a result, vendor strategies have pivoted from selling standalone devices toward integrated solutions that combine sensors, algorithms, and care coordination services. Patient expectations are also evolving: convenience, interoperability with consumer devices, and transparent data-sharing modalities now influence product adoption. Collectively, these dynamics are accelerating the migration of diabetes management from episodic, clinic-centric care to continuous, data-driven modalities that emphasize prevention, personalization, and system-level efficiency.

A rigorous examination of how cumulative United States tariffs enacted in 2025 reshaped supply chains procurement strategies and product development priorities across the diabetes ecosystem

The imposition of cumulative United States tariffs in 2025 created a distinct set of stresses and strategic responses across the diabetes device and software supply chain. In the immediate term, tariffs increased input costs for imported components and finished devices, prompting manufacturers to re-evaluate sourcing strategies and to accelerate supply chain localization where feasible. The result has been a deliberate reassessment of supplier relationships and contractual terms, with procurement teams emphasizing dual sourcing, longer lead-time planning, and inventory resilience to mitigate exposure to ongoing trade policy volatility.

In parallel, product development and commercialization timelines experienced pressure as cost ceilings and margin expectations shifted. Some vendors absorbed incremental costs to preserve competitiveness, while others recalibrated pricing or deferred noncritical investments. For software-centric offerings, cloud hosting and cross-border data transfer arrangements required renewed legal and compliance scrutiny to ensure alignment with evolving trade and data policies. Over the medium term, tariffs acted as a catalyst for investment in domestic manufacturing capacity and for strategic partnerships that prioritize nearshoring, thereby strengthening regional supply networks and creating conditional opportunities for local suppliers and contract manufacturers to scale operations in response to demand.

Deep segmentation insights that integrate device form factors technology stacks end-user profiles deployment modalities disease subtypes and component priorities to reveal practical adoption levers

Segmentation insight requires a granular understanding of how device form factors, enabling technologies, user settings, deployment models, disease types, and component emphasis interact to influence adoption and clinical impact. From a device perspective, blood glucose meters remain relevant for self-monitoring and noninvasive use cases while more advanced continuous glucose monitoring systems and insulin delivery mechanisms support closed loop automation that reduces daily burden. Distinctions between intermittently scanned and real-time continuous monitors, and between patch and tubed pumps, drive different user experiences and integration requirements, while fully closed loop systems demand higher interoperability and regulatory assurance than hybrid configurations.

Technology choices matter because cloud computing options, decision support modules, machine learning approaches, mobile application platforms, and predictive analytics capabilities determine scalability and clinical utility. Public and private cloud architectures shape data governance and latency characteristics, while decision support functions range from alert generation to dosage recommendations. Machine learning implementations that use supervised, unsupervised, or reinforcement approaches will yield different validation needs and clinician acceptance pathways. End-user segmentation further clarifies where value accrues: clinics and diabetes centers prioritize workflow integration and specialist support, hospitals focus on inpatient and outpatient continuity, home care emphasizes remote and self-monitoring convenience, and research institutes demand flexible data access for hypothesis testing. Deployment modes-cloud-based versus on-premise-create trade-offs between scalability and control, with hybrid implementations increasingly common. Disease-type segmentation, including gestational care with trimester-specific needs, Type 1 adult and juvenile onset distinctions, and Type 2 insulin-dependent versus non-insulin-dependent cohorts, informs clinical protocols and device selection. Finally, the component-level split between hardware elements such as pumps and sensors and software capabilities like algorithms and user interfaces underscores where investment and regulatory oversight concentrate.

Comprehensive regional insights detailing how Americas Europe Middle East & Africa and Asia-Pacific dynamics influence adoption regulatory engagement and commercial strategy for diabetes solutions

Regional dynamics fundamentally shape adoption pathways, reimbursement approaches, and supply chain architecture across the diabetes management landscape. In the Americas, health systems demonstrate a strong appetite for value-based models and remote monitoring capabilities, driving payer interest in outcomes-oriented partnerships and in products that can demonstrate measurable patient-level improvements. North American regulatory clarity around medical device software has encouraged pilot deployments within integrated delivery networks, while commercial payer dynamics influence how solutions are packaged and reimbursed.

In Europe, Middle East & Africa, heterogeneous regulatory environments and diverse care delivery contexts require adaptive market entry strategies that account for national reimbursement models, privacy standards, and infrastructure variability. Manufacturers seeking traction across this region must optimize for interoperability and localization, balancing centralized cloud architectures with on-premise or edge computing where bandwidth and data sovereignty concerns prevail. In the Asia-Pacific region, rapid technology adoption, high smartphone penetration, and increasing public investment in digital health create fertile ground for scalable AI-enabled solutions, yet market entrants must navigate varying clinical practice patterns, procurement rules, and localized expectations for affordability and after-sales support. Taken together, these regional nuances dictate differentiated commercial approaches, strategic partnerships, and regulatory engagement plans.

Strategic company-level insights that illuminate competitive positioning partnership models investment priorities and the capabilities that determine long-term leadership in AI-enabled diabetes care

The competitive landscape is defined by a mix of established medical device manufacturers expanding into software-enabled care, technology firms offering analytics and platform services, and nascent entrants focused on niche patient experiences or algorithmic innovation. Market leaders emphasize integrated portfolios that combine sensing hardware, cloud-based analytics, and clinician-facing decision support, while middleware providers concentrate on interoperability layers that connect disparate devices and electronic health records. Meanwhile, software-first companies differentiate through algorithmic sophistication and user interface design, targeting both consumer engagement and clinician workflow augmentation.

Investors and strategic partners are also influencing the trajectory of innovation by prioritizing companies that demonstrate robust clinical evidence, scalable deployment models, and clear pathways to reimbursement. Partnerships between device OEMs and cloud or analytics providers remain a dominant strategy to accelerate time-to-market and to broaden service offerings. For organizations assessing competitive positioning, attention should focus on product modularity, data governance practices, regulatory readiness, and the ability to demonstrate meaningful clinical outcomes in real-world settings.

Actionable recommendations for industry leaders to accelerate adoption build trust and create resilient commercial models that drive measurable clinical outcomes

Industry leaders should pursue a set of pragmatic actions to translate technological promise into measurable clinical and commercial outcomes. First, prioritize interoperability and open standards to ensure devices and analytics can integrate into diverse clinical workflows and electronic health records. This approach reduces friction for provider adoption and facilitates multi-vendor ecosystems that enhance patient choice. Second, invest in rigorous clinical validation that pairs algorithmic outputs with clinician adjudication and patient-reported outcomes to build trust and support reimbursement discussions. Such evidence is critical for transitioning pilots into standard care pathways.

Third, adopt supply chain resilience strategies that include dual sourcing, nearshoring where appropriate, and contractual flexibility to respond to trade-policy shifts. Fourth, design pricing and reimbursement models that align incentives across providers, payers, and patients, prioritizing value-based arrangements tied to demonstrable improvements in control and reduced acute events. Fifth, develop user-centered interfaces and mobile experiences that reduce cognitive load for patients and clinicians alike, ensuring adherence and sustained engagement. Finally, cultivate strategic partnerships across hardware, software, and clinical domains to accelerate innovation while mitigating execution risk.

A transparent mixed-methods research approach combining expert interviews literature synthesis and rigorous validation to produce actionable and reproducible insights

The research methodology underpinning this analysis combined qualitative and quantitative approaches to ensure robustness, triangulation, and practical relevance. Primary research consisted of in-depth interviews with clinicians, product leaders, procurement officers, and regulatory specialists, supplemented by expert roundtables that explored clinical adoption barriers and commercial pathways. Secondary research reviewed peer-reviewed literature, regulatory guidance, clinical trial registries, and company disclosures to contextualize primary findings and to identify prevailing technology trends and validation approaches.

Data synthesis employed thematic analysis for qualitative inputs and structured frameworks to assess technology readiness, interoperability, and business model viability. Where applicable, validation steps included cross-referencing interview insights with documented regulatory filings and publicly available clinical evidence. Ethical considerations were central to the methodology, with informed consent obtained from interview participants and careful anonymization applied where requested. The outcome is a research product that emphasizes reproducible reasoning, transparent assumptions, and evidence-based conclusions designed to inform strategic decisions without relying on undisclosed proprietary datasets.

A concise conclusion highlighting the imperative for coordinated action across clinical validation interoperability and commercial design to realize AI-driven diabetes care benefits

In conclusion, artificial intelligence and connected-device innovation are converging to create a fundamentally different model of diabetes care-one that emphasizes continuous monitoring, personalized insulin delivery, and data-driven decision support. Stakeholders who move proactively to align product design, clinical validation, and commercial models with evolving regulatory and reimbursement landscapes will capture early advantage. Conversely, organizations that treat AI as a feature rather than as an integral component of care pathways risk limited adoption and fragmented impact.

The path forward requires collaboration among device manufacturers, software vendors, clinicians, payers, and policy makers to ensure that technological advances translate into real-world clinical benefits. By leveraging interoperability, prioritizing robust evidence generation, and designing sustainable business models, the industry can accelerate the shift from reactive management to proactive, personalized diabetes care that improves outcomes and reduces system burden.

Table of Contents

1. Preface

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

2. Research Methodology

3. Executive Summary

4. Market Overview

5. Market Insights

  • 5.1. Integration of continuous glucose monitoring data with AI predictive algorithms to personalize insulin dosing based on real-time lifestyle patterns
  • 5.2. Deployment of machine learning models in wearable devices for early detection of hypoglycemic events among high-risk diabetic patients
  • 5.3. Use of natural language processing in virtual health assistants to provide tailored dietary and medication advice for diabetic individuals
  • 5.4. Development of federated learning frameworks to train AI diabetes management models across multiple institutions while preserving patient data privacy
  • 5.5. Adoption of AI-driven smartphone applications for automated meal recognition and insulin bolus recommendations using computer vision techniques
  • 5.6. Collaboration between pharma companies and tech firms to validate AI-enabled closed-loop insulin delivery systems in large-scale clinical trials

6. Cumulative Impact of United States Tariffs 2025

7. Cumulative Impact of Artificial Intelligence 2025

8. Artificial Intelligence in Diabetes Management Market, by Device Type

  • 8.1. Blood Glucose Meter
    • 8.1.1. Non Invasive Bg Meter
    • 8.1.2. Smbg
  • 8.2. Closed Loop System
    • 8.2.1. Fully Closed Loop
    • 8.2.2. Hybrid Closed Loop
  • 8.3. Continuous Glucose Monitor
    • 8.3.1. Intermittently Scanned Cgm
    • 8.3.2. Real Time Cgm
  • 8.4. Insulin Pump
    • 8.4.1. Patch Pump
    • 8.4.2. Tubed Pump

9. Artificial Intelligence in Diabetes Management Market, by Technology

  • 9.1. Cloud Computing
    • 9.1.1. Private Cloud
    • 9.1.2. Public Cloud
  • 9.2. Decision Support Systems
    • 9.2.1. Alert Generation
    • 9.2.2. Dose Recommendation
  • 9.3. Machine Learning
    • 9.3.1. Reinforcement Learning
    • 9.3.2. Supervised Learning
    • 9.3.3. Unsupervised Learning
  • 9.4. Mobile Applications
    • 9.4.1. Android
    • 9.4.2. Ios
  • 9.5. Predictive Analytics
    • 9.5.1. Glucose Trend Prediction
    • 9.5.2. Risk Prediction

10. Artificial Intelligence in Diabetes Management Market, by End User

  • 10.1. Clinic
    • 10.1.1. Diabetes Center
    • 10.1.2. General Clinic
  • 10.2. Home Care
    • 10.2.1. Remote Monitoring
    • 10.2.2. Self Monitoring
  • 10.3. Hospital
    • 10.3.1. Inpatient
    • 10.3.2. Outpatient
  • 10.4. Research Institute
    • 10.4.1. Academic
    • 10.4.2. Private

11. Artificial Intelligence in Diabetes Management Market, by Deployment Mode

  • 11.1. Cloud Based
    • 11.1.1. Hybrid Cloud
    • 11.1.2. Public Cloud
  • 11.2. On Premise
    • 11.2.1. Edge Computing
    • 11.2.2. Server Based

12. Artificial Intelligence in Diabetes Management Market, by Type

  • 12.1. Gestational
    • 12.1.1. First Trimester
    • 12.1.2. Second Trimester
    • 12.1.3. Third Trimester
  • 12.2. Type 1
    • 12.2.1. Adult Onset
    • 12.2.2. Juvenile Onset
  • 12.3. Type 2
    • 12.3.1. Insulin Dependent
    • 12.3.2. Non Insulin Dependent

13. Artificial Intelligence in Diabetes Management Market, by Component

  • 13.1. Hardware
    • 13.1.1. Pumps
    • 13.1.2. Sensors
    • 13.1.3. Wearable Devices
  • 13.2. Software
    • 13.2.1. Algorithms
    • 13.2.2. Data Management
    • 13.2.3. User Interface

14. Artificial Intelligence in Diabetes Management Market, by Region

  • 14.1. Americas
    • 14.1.1. North America
    • 14.1.2. Latin America
  • 14.2. Europe, Middle East & Africa
    • 14.2.1. Europe
    • 14.2.2. Middle East
    • 14.2.3. Africa
  • 14.3. Asia-Pacific

15. Artificial Intelligence in Diabetes Management Market, by Group

  • 15.1. ASEAN
  • 15.2. GCC
  • 15.3. European Union
  • 15.4. BRICS
  • 15.5. G7
  • 15.6. NATO

16. Artificial Intelligence in Diabetes Management Market, by Country

  • 16.1. United States
  • 16.2. Canada
  • 16.3. Mexico
  • 16.4. Brazil
  • 16.5. United Kingdom
  • 16.6. Germany
  • 16.7. France
  • 16.8. Russia
  • 16.9. Italy
  • 16.10. Spain
  • 16.11. China
  • 16.12. India
  • 16.13. Japan
  • 16.14. Australia
  • 16.15. South Korea

17. Competitive Landscape

  • 17.1. Market Share Analysis, 2024
  • 17.2. FPNV Positioning Matrix, 2024
  • 17.3. Competitive Analysis
    • 17.3.1. Medtronic plc
    • 17.3.2. Abbott Laboratories
    • 17.3.3. Dexcom, Inc.
    • 17.3.4. F. Hoffmann-La Roche Ltd
    • 17.3.5. Insulet Corporation
    • 17.3.6. Tandem Diabetes Care, Inc.
    • 17.3.7. Teladoc Health, Inc.
    • 17.3.8. Omada Health, Inc.
    • 17.3.9. Bigfoot Biomedical, Inc.
    • 17.3.10. Glooko Inc.

LIST OF FIGURES

  • FIGURE 1. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, 2018-2032 (USD MILLION)
  • FIGURE 2. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DEVICE TYPE, 2024 VS 2032 (%)
  • FIGURE 3. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DEVICE TYPE, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 4. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TECHNOLOGY, 2024 VS 2032 (%)
  • FIGURE 5. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TECHNOLOGY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 6. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY END USER, 2024 VS 2032 (%)
  • FIGURE 7. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY END USER, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 8. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DEPLOYMENT MODE, 2024 VS 2032 (%)
  • FIGURE 9. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DEPLOYMENT MODE, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 10. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TYPE, 2024 VS 2032 (%)
  • FIGURE 11. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TYPE, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 12. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COMPONENT, 2024 VS 2032 (%)
  • FIGURE 13. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COMPONENT, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 14. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REGION, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 15. AMERICAS ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SUBREGION, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 16. NORTH AMERICA ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 17. LATIN AMERICA ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 18. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SUBREGION, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 19. EUROPE ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 20. MIDDLE EAST ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 21. AFRICA ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 22. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 23. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GROUP, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 24. ASEAN ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 25. GCC ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 26. EUROPEAN UNION ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 27. BRICS ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 28. G7 ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 29. NATO ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 30. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 31. ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SHARE, BY KEY PLAYER, 2024
  • FIGURE 32. ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET, FPNV POSITIONING MATRIX, 2024

LIST OF TABLES

  • TABLE 1. ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SEGMENTATION & COVERAGE
  • TABLE 2. UNITED STATES DOLLAR EXCHANGE RATE, 2018-2024
  • TABLE 3. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, 2018-2024 (USD MILLION)
  • TABLE 4. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, 2025-2032 (USD MILLION)
  • TABLE 5. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DEVICE TYPE, 2018-2024 (USD MILLION)
  • TABLE 6. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DEVICE TYPE, 2025-2032 (USD MILLION)
  • TABLE 7. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY BLOOD GLUCOSE METER, 2018-2024 (USD MILLION)
  • TABLE 8. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY BLOOD GLUCOSE METER, 2025-2032 (USD MILLION)
  • TABLE 9. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY BLOOD GLUCOSE METER, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 10. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY BLOOD GLUCOSE METER, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 11. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY BLOOD GLUCOSE METER, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 12. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY BLOOD GLUCOSE METER, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 13. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY BLOOD GLUCOSE METER, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 14. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY BLOOD GLUCOSE METER, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 15. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY NON INVASIVE BG METER, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 16. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY NON INVASIVE BG METER, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 17. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY NON INVASIVE BG METER, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 18. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY NON INVASIVE BG METER, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 19. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY NON INVASIVE BG METER, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 20. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY NON INVASIVE BG METER, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 21. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SMBG, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 22. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SMBG, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 23. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SMBG, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 24. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SMBG, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 25. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SMBG, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 26. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SMBG, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 27. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOSED LOOP SYSTEM, 2018-2024 (USD MILLION)
  • TABLE 28. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOSED LOOP SYSTEM, 2025-2032 (USD MILLION)
  • TABLE 29. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOSED LOOP SYSTEM, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 30. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOSED LOOP SYSTEM, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 31. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOSED LOOP SYSTEM, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 32. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOSED LOOP SYSTEM, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 33. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOSED LOOP SYSTEM, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 34. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOSED LOOP SYSTEM, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 35. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY FULLY CLOSED LOOP, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 36. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY FULLY CLOSED LOOP, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 37. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY FULLY CLOSED LOOP, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 38. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY FULLY CLOSED LOOP, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 39. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY FULLY CLOSED LOOP, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 40. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY FULLY CLOSED LOOP, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 41. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HYBRID CLOSED LOOP, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 42. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HYBRID CLOSED LOOP, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 43. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HYBRID CLOSED LOOP, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 44. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HYBRID CLOSED LOOP, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 45. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HYBRID CLOSED LOOP, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 46. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HYBRID CLOSED LOOP, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 47. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CONTINUOUS GLUCOSE MONITOR, 2018-2024 (USD MILLION)
  • TABLE 48. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CONTINUOUS GLUCOSE MONITOR, 2025-2032 (USD MILLION)
  • TABLE 49. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CONTINUOUS GLUCOSE MONITOR, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 50. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CONTINUOUS GLUCOSE MONITOR, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 51. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CONTINUOUS GLUCOSE MONITOR, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 52. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CONTINUOUS GLUCOSE MONITOR, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 53. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CONTINUOUS GLUCOSE MONITOR, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 54. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CONTINUOUS GLUCOSE MONITOR, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 55. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INTERMITTENTLY SCANNED CGM, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 56. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INTERMITTENTLY SCANNED CGM, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 57. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INTERMITTENTLY SCANNED CGM, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 58. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INTERMITTENTLY SCANNED CGM, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 59. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INTERMITTENTLY SCANNED CGM, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 60. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INTERMITTENTLY SCANNED CGM, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 61. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REAL TIME CGM, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 62. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REAL TIME CGM, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 63. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REAL TIME CGM, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 64. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REAL TIME CGM, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 65. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REAL TIME CGM, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 66. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REAL TIME CGM, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 67. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INSULIN PUMP, 2018-2024 (USD MILLION)
  • TABLE 68. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INSULIN PUMP, 2025-2032 (USD MILLION)
  • TABLE 69. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INSULIN PUMP, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 70. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INSULIN PUMP, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 71. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INSULIN PUMP, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 72. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INSULIN PUMP, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 73. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INSULIN PUMP, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 74. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INSULIN PUMP, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 75. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PATCH PUMP, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 76. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PATCH PUMP, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 77. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PATCH PUMP, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 78. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PATCH PUMP, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 79. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PATCH PUMP, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 80. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PATCH PUMP, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 81. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TUBED PUMP, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 82. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TUBED PUMP, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 83. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TUBED PUMP, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 84. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TUBED PUMP, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 85. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TUBED PUMP, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 86. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TUBED PUMP, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 87. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TECHNOLOGY, 2018-2024 (USD MILLION)
  • TABLE 88. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TECHNOLOGY, 2025-2032 (USD MILLION)
  • TABLE 89. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOUD COMPUTING, 2018-2024 (USD MILLION)
  • TABLE 90. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOUD COMPUTING, 2025-2032 (USD MILLION)
  • TABLE 91. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOUD COMPUTING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 92. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOUD COMPUTING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 93. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOUD COMPUTING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 94. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOUD COMPUTING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 95. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOUD COMPUTING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 96. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOUD COMPUTING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 97. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PRIVATE CLOUD, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 98. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PRIVATE CLOUD, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 99. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PRIVATE CLOUD, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 100. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PRIVATE CLOUD, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 101. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PRIVATE CLOUD, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 102. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PRIVATE CLOUD, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 103. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PUBLIC CLOUD, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 104. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PUBLIC CLOUD, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 105. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PUBLIC CLOUD, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 106. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PUBLIC CLOUD, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 107. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PUBLIC CLOUD, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 108. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PUBLIC CLOUD, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 109. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DECISION SUPPORT SYSTEMS, 2018-2024 (USD MILLION)
  • TABLE 110. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DECISION SUPPORT SYSTEMS, 2025-2032 (USD MILLION)
  • TABLE 111. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DECISION SUPPORT SYSTEMS, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 112. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DECISION SUPPORT SYSTEMS, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 113. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DECISION SUPPORT SYSTEMS, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 114. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DECISION SUPPORT SYSTEMS, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 115. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DECISION SUPPORT SYSTEMS, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 116. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DECISION SUPPORT SYSTEMS, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 117. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ALERT GENERATION, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 118. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ALERT GENERATION, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 119. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ALERT GENERATION, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 120. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ALERT GENERATION, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 121. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ALERT GENERATION, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 122. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ALERT GENERATION, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 123. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DOSE RECOMMENDATION, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 124. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DOSE RECOMMENDATION, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 125. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DOSE RECOMMENDATION, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 126. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DOSE RECOMMENDATION, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 127. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DOSE RECOMMENDATION, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 128. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DOSE RECOMMENDATION, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 129. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MACHINE LEARNING, 2018-2024 (USD MILLION)
  • TABLE 130. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MACHINE LEARNING, 2025-2032 (USD MILLION)
  • TABLE 131. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MACHINE LEARNING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 132. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MACHINE LEARNING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 133. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MACHINE LEARNING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 134. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MACHINE LEARNING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 135. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MACHINE LEARNING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 136. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MACHINE LEARNING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 137. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REINFORCEMENT LEARNING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 138. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REINFORCEMENT LEARNING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 139. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REINFORCEMENT LEARNING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 140. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REINFORCEMENT LEARNING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 141. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REINFORCEMENT LEARNING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 142. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REINFORCEMENT LEARNING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 143. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SUPERVISED LEARNING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 144. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SUPERVISED LEARNING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 145. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SUPERVISED LEARNING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 146. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SUPERVISED LEARNING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 147. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SUPERVISED LEARNING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 148. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SUPERVISED LEARNING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 149. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY UNSUPERVISED LEARNING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 150. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY UNSUPERVISED LEARNING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 151. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY UNSUPERVISED LEARNING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 152. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY UNSUPERVISED LEARNING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 153. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY UNSUPERVISED LEARNING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 154. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY UNSUPERVISED LEARNING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 155. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MOBILE APPLICATIONS, 2018-2024 (USD MILLION)
  • TABLE 156. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MOBILE APPLICATIONS, 2025-2032 (USD MILLION)
  • TABLE 157. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MOBILE APPLICATIONS, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 158. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MOBILE APPLICATIONS, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 159. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MOBILE APPLICATIONS, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 160. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MOBILE APPLICATIONS, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 161. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MOBILE APPLICATIONS, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 162. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MOBILE APPLICATIONS, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 163. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ANDROID, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 164. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ANDROID, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 165. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ANDROID, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 166. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ANDROID, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 167. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ANDROID, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 168. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ANDROID, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 169. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY IOS, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 170. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY IOS, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 171. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY IOS, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 172. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY IOS, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 173. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY IOS, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 174. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY IOS, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 175. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PREDICTIVE ANALYTICS, 2018-2024 (USD MILLION)
  • TABLE 176. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PREDICTIVE ANALYTICS, 2025-2032 (USD MILLION)
  • TABLE 177. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PREDICTIVE ANALYTICS, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 178. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PREDICTIVE ANALYTICS, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 179. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PREDICTIVE ANALYTICS, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 180. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PREDICTIVE ANALYTICS, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 181. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PREDICTIVE ANALYTICS, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 182. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PREDICTIVE ANALYTICS, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 183. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GLUCOSE TREND PREDICTION, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 184. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GLUCOSE TREND PREDICTION, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 185. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GLUCOSE TREND PREDICTION, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 186. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GLUCOSE TREND PREDICTION, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 187. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GLUCOSE TREND PREDICTION, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 188. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GLUCOSE TREND PREDICTION, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 189. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY RISK PREDICTION, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 190. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY RISK PREDICTION, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 191. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY RISK PREDICTION, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 192. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY RISK PREDICTION, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 193. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY RISK PREDICTION, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 194. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY RISK PREDICTION, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 195. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY END USER, 2018-2024 (USD MILLION)
  • TABLE 196. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY END USER, 2025-2032 (USD MILLION)
  • TABLE 197. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLINIC, 2018-2024 (USD MILLION)
  • TABLE 198. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLINIC, 2025-2032 (USD MILLION)
  • TABLE 199. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLINIC, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 200. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLINIC, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 201. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLINIC, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 202. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLINIC, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 203. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLINIC, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 204. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLINIC, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 205. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DIABETES CENTER, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 206. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DIABETES CENTER, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 207. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DIABETES CENTER, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 208. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DIABETES CENTER, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 209. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DIABETES CENTER, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 210. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DIABETES CENTER, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 211. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GENERAL CLINIC, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 212. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GENERAL CLINIC, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 213. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GENERAL CLINIC, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 214. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GENERAL CLINIC, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 215. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GENERAL CLINIC, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 216. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GENERAL CLINIC, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 217. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOME CARE, 2018-2024 (USD MILLION)
  • TABLE 218. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOME CARE, 2025-2032 (USD MILLION)
  • TABLE 219. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOME CARE, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 220. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOME CARE, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 221. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOME CARE, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 222. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOME CARE, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 223. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOME CARE, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 224. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOME CARE, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 225. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REMOTE MONITORING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 226. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REMOTE MONITORING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 227. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REMOTE MONITORING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 228. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REMOTE MONITORING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 229. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REMOTE MONITORING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 230. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REMOTE MONITORING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 231. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SELF MONITORING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 232. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SELF MONITORING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 233. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SELF MONITORING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 234. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SELF MONITORING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 235. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SELF MONITORING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 236. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SELF MONITORING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 237. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOSPITAL, 2018-2024 (USD MILLION)
  • TABLE 238. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOSPITAL, 2025-2032 (USD MILLION)
  • TABLE 239. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOSPITAL, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 240. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOSPITAL, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 241. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOSPITAL, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 242. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOSPITAL, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 243. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOSPITAL, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 244. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOSPITAL, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 245. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INPATIENT, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 246. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INPATIENT, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 247. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INPATIENT, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 248. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INPATIENT, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 249. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INPATIENT, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 250. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INPATIENT, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 251. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET