The rapid integration of artificial intelligence in healthcare, accelerated by the Trump administration's 2025 AI Action Plan and private sector innovations from companies like Nvidia and Hippocratic AI, poses urgent challenges for nursing and health policy. This policy analysis examines the intersection of federal AI initiatives, emerging healthcare technologies, and nursing workforce implications through document analysis of regulatory frameworks, the federal AI Action Plan's 90+ initiatives, and insights from the American Academy of Nursing's November 2024 policy dialogue on AI transformation. The analysis reveals that while AI demonstrates measurable improvements in discrete clinical tasks—including 16% better medication assessment accuracy and 43% greater precision in identifying drug interactions at 9 per hour compared to nurses’ median 41. 38 hourly wage—current federal policy lacks critical healthcare-specific safeguards. The AI Action Plan's emphasis on rapid deployment and deregulation fails to address safety-net infrastructure needs, implementation pathways for vulnerable populations, or mechanisms ensuring health equity. Evidence from the Academy dialogue indicates that AI's “technosocial reality” fundamentally alters care delivery while potentially exacerbating disparities in underserved communities, as demonstrated by algorithmic bias in systems like Optum's care allocation algorithm. The findings suggest that achieving equitable AI integration requires comprehensive regulatory frameworks coordinating FDA, CMS, OCR, and HRSA oversight; community-centered governance approaches redistributing decision-making power to affected populations; and nursing leadership in AI development to preserve patient-centered care values. Without proactive nursing engagement in AI governance, healthcare risks adopting technologies that prioritize efficiency over the holistic, compassionate care fundamental to nursing practice.
Yang et al. (Wed,) studied this question.