AI’s integration in healthcare impacts the workforce, raising concerns about job displacement. Automation of administrative and diagnostic tasks may reduce the demand for certain healthcare roles, necessitating workforce reskilling initiatives (Huo et al., 2025). AI-powered systems are increasingly being used for administrative tasks, such as managing patient records, scheduling appointments, and handling billing processes. While these advancements enhance efficiency, they also reduce the need for traditional administrative roles, potentially displacing workers. Beyond administrative roles, AI is also transforming clinical decision-making. AI-powered diagnostic tools can analyze medical images, detect anomalies, and provide treatment recommendations. While these technologies support physicians, they also raise concerns about whether AI might eventually replace human expertise in some areas. For example, radiologists rely on AI to assist in detecting tumors in X-rays and MRIs, but if AI models continue improving, some fear that fewer radiologists will be needed in the future. To mitigate these concerns, healthcare institutions must invest in workforce reskilling programs, ensuring that medical professionals can effectively collaborate with AI systems rather than being replaced by them. Another social implication is the digital divide in AI accessibility. AI-powered healthcare solutions are more prevalent in developed countries with advanced infrastructure and extensive electronic health records. However, in low-resource settings, access to AI-driven diagnostics and treatment recommendations remains limited. Unequal access to AI-powered healthcare tools can exacerbate existing health disparities, as wealthier populations benefit from AI’s efficiencies while disadvantaged communities continue to rely on traditional, less advanced medical systems. Addressing these disparities requires policymakers to ensure equitable access to AI-driven healthcare, particularly in underserved areas.