Alleviating the Caregiver Burden: AI as a Systemic Intervention

Zhang, Jingyi (Jesy)

European Journal of Public Health and Environmental Research, 2026, vol. 2, issue 1, 1-6

Abstract: This article examines the systemic crisis faced by millions of Americans juggling full-time work with unpaid family caregiving. Through a vignette, it illustrates the severe health and professional toll on caregivers, arguing that existing policies like the FMLA are misaligned with the unpredictable, episodic nature of modern care. As a solution, it proposes reimagining artificial intelligence (AI) as essential support infrastructure. By detailing AI's role in remote monitoring, care coordination, and enabling flexible work, the article demonstrates how technology can alleviate daily burdens, restore predictability, and prevent burnout. It counters cost concerns by framing caregiver support as a preventative economic investment and concludes that sustaining caregivers is an urgent public health and economic imperative for an aging society.

Keywords: family caregivers; work-care conflict; caregiver burnout; artificial intelligence (AI) in healthcare; remote patient monitoring; flexible work arrangements (search for similar items in EconPapers)
Date: 2026
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