Artificial Intelligence (AI) in Diabetes Management - Global Strategic Business Report

The global market for Artificial Intelligence (AI) in Diabetes Management was estimated at US$13.2 Billion in 2024 and is projected to reach US$21.4 Billion by 2030, growing at a CAGR of 8.3% from 2024 to 2030. This comprehensive report provides an in-depth analysis of market trends, drivers, and forecasts, helping you make informed business decisions. The report includes the most recent global tariff developments and how they impact the Artificial Intelligence (AI) in Diabetes Management market.

Global Artificial Intelligence (AI) in Diabetes Management Market - Key Trends & Drivers Summarized

Is AI Revolutionizing Personalized Care in Diabetes Management?

Artificial Intelligence (AI) is redefining the landscape of diabetes management by enabling unprecedented levels of personalization, precision, and proactive care. Traditionally, diabetes treatment has been characterized by reactive and generalized approaches, relying heavily on periodic glucose measurements, standard medication schedules, and patient self-monitoring. However, with the advent of AI-powered systems, diabetes care is transitioning into a dynamic, real-time, and individualized model. Machine learning algorithms can now analyze massive streams of data from continuous glucose monitors (CGMs), insulin pumps, fitness trackers, and electronic health records to identify patterns and predict fluctuations in blood glucose levels before they happen. These insights empower patients to take preventive actions, such as adjusting their diet or activity level, even before symptoms arise. AI-enabled platforms also support real-time insulin dosing recommendations and closed-loop systems, often referred to as “artificial pancreas” technologies, which automatically administer insulin based on predictive analytics. Moreover, these systems provide tailored coaching and lifestyle guidance through mobile apps, enhancing adherence and long-term outcomes. Natural language processing is further being used to extract insights from unstructured clinical notes, while AI chatbots offer 24/7 support and reminders. Collectively, these innovations are reducing the cognitive burden on patients, minimizing complications, and making diabetes management more responsive and sustainable. As AI continues to learn from diverse patient populations and evolving medical data, it is setting a new standard for intelligent, patient-centric diabetes care.

How Are Digital Health Ecosystems and Remote Monitoring Expanding AI's Role?

The expanding digital health ecosystem is providing fertile ground for AI to play a central role in comprehensive diabetes management, especially through remote monitoring and telemedicine solutions. The COVID-19 pandemic accelerated the adoption of digital health tools, and diabetes care was among the areas that experienced the most significant transformation. With increased reliance on virtual consultations, AI-enabled platforms became critical for monitoring patient conditions outside of clinical settings. Remote glucose monitoring devices paired with AI algorithms are now used to alert healthcare providers and patients to dangerous trends, such as hyperglycemia or hypoglycemia, in real time. These systems help clinicians prioritize interventions and reduce emergency hospital visits. AI also supports dynamic risk stratification, enabling physicians to allocate resources and customize care plans based on individual risk profiles. Integration with wearable devices and smartphones allows for the collection of contextual data like physical activity, sleep, and food intake which AI models analyze to give holistic insights into patient health. Such comprehensive tracking is particularly beneficial in managing Type 1 and Type 2 diabetes in patients with coexisting conditions. Moreover, AI is enabling large-scale population health management by aggregating anonymized data to identify regional trends, medication effectiveness, and gaps in care delivery. In rural or underserved areas, where access to endocrinologists may be limited, AI-driven virtual care platforms are bridging the gap, providing timely and consistent care. As digital health ecosystems become more sophisticated, AI is poised to become the central intelligence layer connecting devices, providers, and patients in an integrated care continuum.

Is AI Changing the Paradigm of Early Detection and Predictive Intervention?

AI is proving to be a game-changer in the early detection and prediction of diabetes-related complications, fundamentally shifting the focus of care from treatment to prevention. One of the most powerful applications of AI in diabetes management lies in its predictive capabilities. Using vast datasets from electronic health records, genetic profiles, imaging results, and biometric data, machine learning models can identify early warning signs of diabetes onset, long before symptoms become apparent. For individuals at risk of developing Type 2 diabetes, AI tools can generate risk scores and recommend targeted lifestyle changes, thus preventing disease progression. In diagnosed patients, AI is being used to anticipate complications such as diabetic retinopathy, nephropathy, neuropathy, and cardiovascular disease by detecting subtle patterns that are invisible to the human eye. AI-enhanced retinal imaging systems, for example, are being deployed in primary care clinics to screen for diabetic eye disease without the need for specialist intervention. Similarly, AI models are helping clinicians determine the likelihood of hospitalization or insulin resistance, enabling timely intervention. AI is also revolutionizing clinical trial design by identifying suitable patient cohorts, predicting treatment adherence, and monitoring outcomes with greater precision. As a result, pharmaceutical companies and healthcare systems are increasingly investing in AI tools to enhance research, reduce costs, and personalize care pathways. This proactive approach not only improves clinical outcomes but also reduces long-term healthcare expenditures. In essence, AI is pushing diabetes management upstream toward earlier identification, predictive action, and ultimately, disease prevention.

What Is Driving the Rapid Global Adoption of AI in Diabetes Management?

The growth in the artificial intelligence (AI) in diabetes management market is driven by several factors rooted in technology advancement, healthcare transformation, and evolving patient expectations. The increasing global prevalence of diabetes estimated to affect over half a billion people has created an urgent need for scalable, cost-effective solutions that go beyond traditional clinical models. AI's ability to deliver real-time,>

Key Insights:

• Market Growth: Understand the significant growth trajectory of the Diagnostic Devices segment, which is expected to reach US$14.0 Billion by 2030 with a CAGR of a 9.3%. The Glucose Monitoring Devices segment is also set to grow at 7.0% CAGR over the analysis period.
• Regional Analysis: Gain insights into the U.S. market, valued at $3.6 Billion in 2024, and China, forecasted to grow at an impressive 13.1% CAGR to reach $4.7 Billion by 2030. Discover growth trends in other key regions, including Japan, Canada, Germany, and the Asia-Pacific.

Why You Should Buy This Report:

• Detailed Market Analysis: Access a thorough analysis of the Global Artificial Intelligence (AI) in Diabetes Management Market, covering all major geographic regions and market segments.
• Competitive Insights: Get an overview of the competitive landscape, including the market presence of major players across different geographies.
• Future Trends and Drivers: Understand the key trends and drivers shaping the future of the Global Artificial Intelligence (AI) in Diabetes Management Market.
• Actionable Insights: Benefit from actionable insights that can help you identify new revenue opportunities and make strategic business decisions.

Key Questions Answered:

• How is the Global Artificial Intelligence (AI) in Diabetes Management Market expected to evolve by 2030?
• What are the main drivers and restraints affecting the market?
• Which market segments will grow the most over the forecast period?
• How will market shares for different regions and segments change by 2030?
• Who are the leading players in the market, and what are their prospects?

Report Features:

• Comprehensive Market Data: Independent analysis of annual sales and market forecasts in US$ Million from 2024 to 2030.
• In-Depth Regional Analysis: Detailed insights into key markets, including the U.S., China, Japan, Canada, Europe, Asia-Pacific, Latin America, Middle East, and Africa.
• Company Profiles: Coverage of players such as Abbott Laboratories, Apple Inc., Beta Bionics, Bigfoot Biomedical, Inc., and more.
• Complimentary Updates: Receive free report updates for one year to keep you informed of the latest market developments.

Some of the 47 companies featured in this Artificial Intelligence (AI) in Diabetes Management market report include:

• Abbott Laboratories
• Apple Inc.
• Beta Bionics
• Bigfoot Biomedical, Inc.
• Dexcom, Inc.
• Diabeloop SA
• DreaMed Diabetes Ltd.
• Eyenuk, Inc.
• Glooko Inc.
• Google Inc.
• IBM Corporation
• Insulet Corporation
• Medtronic PLC
• Nemaura Medical Inc.
• Novo Nordisk A/S
• Roche Holding AG
• Sanofi SA
• Tandem Diabetes Care, Inc.
• Virta Health Corp.
• Wellthy Therapeutics Pvt. Ltd.

This edition integrates the latest global trade and economic shifts as of June 2025 into comprehensive market analysis. Key updates include:

• Tariff and Trade Impact: Insights into global tariff negotiations across 180+ countries, with analysis of supply chain turbulence, sourcing disruptions, and geographic realignment. Special focus on 2025 as a pivotal year for trade tensions, including updated perspectives on the Trump-era tariffs.
• Adjusted Forecasts and Analytics: Revised global and regional market forecasts through 2030, incorporating tariff effects, economic uncertainty, and structural changes in globalization. Includes segmentation by product, technology, type, material, distribution channel, application, and end-use, with historical analysis since 2015.
• Strategic Market Dynamics: Evaluation of revised market prospects, regional outlooks, and key economic indicators such as population and urbanization trends.
• Innovation & Technology Trends: Latest developments in product and process innovation, emerging technologies, and key industry drivers shaping the competitive landscape.
• Competitive Intelligence: Updated global market share estimates for 2025, competitive positioning of major players (Strong/Active/Niche/Trivial), and refined focus on leading global brands and core players.
• Expert Insight & Commentary: Strategic analysis from economists, trade experts, and domain specialists to contextualize market shifts and identify emerging opportunities.
• Complimentary Update: Buyers receive a free July 2025 update with finalized tariff impacts, new trade agreement effects, revised projections, and expanded country-level coverage.