Applying artificial intelligence to the hypertension care cascade: Opportunities and challenges

In the United States, hypertension control curves have plateaued below what is achievable and acceptable. The persistence of suboptimal disease control—despite a robust clinical armamentarium—suggests failure points between guideline-directed and real-world care. This manuscript examines the potential of artificial intelligence (AI) to address the public health challenges undermining hypertension control. Using the hypertension care cascade (which comprises diagnosis, awareness, treatment, and control) as a guiding framework, we synthesize current evidence and identify promising applications of AI-enabled tools and technologies at each stage of the cascade. AI, indeed, offers a plausible pathway for addressing some of the most pernicious forces undermining sustained, scalable hypertension control; however, it is not without risks and limitations. Its deployment must, therefore, be paired with a comprehensive governance structure that safeguards patients and prioritizes safety, equity, and accountability. With these safeguards in place, AI holds promise for bridging hypertension's operational gaps and improving population health.