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<p>Artificial intelligence (AI) is rapidly transforming the landscape of chronic medical conditions, such as cardio-kidney-metabolic (CKM) issues linked to type 2 diabetes and obesity. It creates new opportunities to shift from reactive to proactive, data-driven care. Recent advances include predictive algorithms for hypoglycemia and hyperglycemia, decision-support tools for insulin titration, and generative and agentic AI applications that can enhance patient engagement, streamline clinical workflows, and provide personalized education. For individuals with chronic conditions, AI-powered technologies offer hope in reducing disease burden, supporting self-management, and improving quality of life. For clinicians, AI offers opportunities to analyze and interpret large amounts of glucose, medication, and behavioral data, thus supporting personalized care and freeing more time to focus on psychosocial and lifestyle factors. Despite these benefits, challenges remain, such as ensuring equitable access, integrating AI into primary care, building trust among clinicians and patients, and addressing ethical issues related to data use. This review will synthesize current evidence on AI’s impact on diabetes and CKM care and education, highlight opportunities for interdisciplinary teams to utilize AI tools, and outline future directions for research and clinical practice. By examining AI’s potential and limitations, this article aims to equip clinicians with the knowledge needed to adopt AI-enabled approaches to better manage chronic diseases.</p>

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Artificial intelligence in cardio-kidney-metabolic care: Transforming integrated disease management through data-informed innovation

  • 期刊论文

  • 发表日期：

    2026年6月1日

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  • Clipper F. Young,
  • Janice MacLeod

摘要

Artificial intelligence (AI) is rapidly transforming the landscape of chronic medical conditions, such as cardio-kidney-metabolic (CKM) issues linked to type 2 diabetes and obesity. It creates new opportunities to shift from reactive to proactive, data-driven care. Recent advances include predictive algorithms for hypoglycemia and hyperglycemia, decision-support tools for insulin titration, and generative and agentic AI applications that can enhance patient engagement, streamline clinical workflows, and provide personalized education. For individuals with chronic conditions, AI-powered technologies offer hope in reducing disease burden, supporting self-management, and improving quality of life. For clinicians, AI offers opportunities to analyze and interpret large amounts of glucose, medication, and behavioral data, thus supporting personalized care and freeing more time to focus on psychosocial and lifestyle factors. Despite these benefits, challenges remain, such as ensuring equitable access, integrating AI into primary care, building trust among clinicians and patients, and addressing ethical issues related to data use. This review will synthesize current evidence on AI’s impact on diabetes and CKM care and education, highlight opportunities for interdisciplinary teams to utilize AI tools, and outline future directions for research and clinical practice. By examining AI’s potential and limitations, this article aims to equip clinicians with the knowledge needed to adopt AI-enabled approaches to better manage chronic diseases.