Introducing the AI Insights Series: Keeping the “Humanness of Health” in the Age of AI

Human at the Core: How AI, Leaders and Community Partnerships Are Shaping the Future of Human-centered Health Workforce Recruitment, Hiring, Retention and Development

According to the U.S. Bureau of Labor Statistics, the demand for health professionals—especially nurses, medical technicians, and mental health providers—is expected to grow significantly through 2030. Simultaneously, public health departments face budget constraints and staffing shortages, exacerbated by the COVID-19 pandemic and the recent administration’s federal government budget cuts. Finding the right talent in such a high-stakes, critically important and vastly underfunded field involves more than filling a role; it’s about ensuring the right skills, credentials, and cultural fit in a highly regulated and mission-driven environment.  As the U.S. healthcare and public health sectors confront these mounting workforce shortages, the need for smarter, faster, and more equitable hiring has never been greater. In the U.S., healthcare and public health organizations face persistent challenges in hiring qualified professionals due to the workforce shortages, burnout, and an increasingly complex regulatory environment. AI-driven recruitment tools are emerging as powerful solutions to streamline hiring, reduce costs, and ultimately improve health outcomes. 

The 2024 Public Health Workforce Interests and Needs Survey (PH WINS) findings illustrate rising burnout rates across agencies coupled with key training gaps in budget and financial management, policy engagement along with systems and strategic thinking. Furthermore these results indicate a strong desire for individuals in the public health space to gain skills which will allow them to adapt accordingly to their communities needs. This particular sector of skills training and capacity building could be one of many endeavors prioritized with the use of AI through curriculum construction and community engagement programs to ultimately improve community outcomes and workforce satisfaction. With the continuous pressures and demands of these organizations, artificial intelligence (AI) offers targeted, scalable solutions that can enhance workforce development and resilience. Retention and development of health workers remains a long-term goal and has much to gain from AI. In recent years, AI has reshaped industries across the globe through data-driven workforce planning, predictive analysis, career pathing, and upskilling yet the health workforce has not seen much of these innovative approaches due to the increased regulatory environments that most healthcare and public health organizations must adhere to.

Within the public health sector, the biggest gains are yet to be seen. AI can transform how community health centers and local health departments recruit staff by streamlining resume screening, candidate matching, and interview scheduling. For example, Cleveland Clinic used AI tools to rapidly hire qualified nurses by analyzing resumes, predicting candidate fit, and automating outreach, cutting recruitment time dramatically. This technology is especially valuable for smaller centers that often lack large HR teams, helping them compete for talent more effectively and respond quickly to urgent public health needs. By reducing administrative burden and improving hiring accuracy, AI allows these organizations to focus more on delivering care to their communities.

In addition to finding workers, AI can help keep them. By identifying skill gaps, early burnout signals, limited leadership access and low awareness of new concepts, organizations can invest in their workers with budget friendly and impactful AI solutions. AI-powered tools can personalize training, identify hidden skill gaps, and provide adaptive learning experiences in areas such as strategic thinking, public health finance, and systems leadership. Predictive analytics can flag staff at risk of leaving, enabling agencies to intervene early with mentorship, career pathing, and well-being support. Moreover, AI-driven internal gig platforms and competency mapping open doors for emerging leaders, giving non-supervisory staff greater access to innovative projects and professional growth. By integrating AI into talent development, public health organizations not only respond to the immediate workforce crisis but also lay the groundwork for a smarter, more agile, and future-ready workforce.

Within recruitment and retention, many health organizations have also begun utilizing AI tools. From resume, CV screenings and candidate matching of positions to reviewing applicant responses and scheduling interviews, there are various different ways AI can be helpful in the recruiting process (Hunkenschroer et al, 2023). However, this implementation of AI should be guided by regulatory practices at the federal, state, and local levels. 

Across the country, states like Illinois are beginning to pass AI legislation in relation to employment practices. Legislation like HB 3773, states civil rights may be violated if employers use AI in ways that cause discrimination against protected groups or specific zip codes. Additionally, employers must be transparent with employees about the use of AI (Illinois General Assembly, 2024). The Washington State Department of Social and Health Services (DSHS) has an internal (Administrative Policy No. 15.28: Use of Artificial Intelligence). It sets out expectations “to ensure legal, ethical, equitable, and secure use of any artificial intelligence (AI) technology including, but not limited to, generative AI.” The policy defines acceptable and prohibited uses and obligations for the department in development or use of AI models/systems. New York City has one of the strongest local laws regulating automated/AI hiring tools (Local Law 144 and implementing rules). That law applies to employers and city agencies using automated employment decision tools. The New York City Department of Health and Mental Hygiene operates under those rules when using AI for hiring or promotion.

As more talk of AI emerges, so does the fear of how AI will dehumanize our environments. While AI offers powerful tools to streamline recruitment, hiring, retention, and development, it cannot replace the human insight, empathy, and community connection that are essential to building a resilient, mission-driven workforce. Proximate Learning partners with health departments, hospital systems, and community health centers to thoughtfully integrate AI into strategic alignment and development of employees ensuring that technology enhances, rather than replaces, the humanness of the health workforce.

Main Takeaways:

• Public health departments face budget constraints and staffing shortages, exacerbated by the COVID-19 pandemic and the recent administration’s federal government budget cuts and the solution may lie in AI assisted recruitment tools.

• Recently, AI has reshaped industries globally through things like data-driven workforce planning but these innovative approaches are missing in the health workforce due to the increased regulatory environments.

• Organizations like Cleveland Clinic use AI tools to hire qualified nurses by analyzing resumes, predicting candidate fit, and automating outreach, cutting recruitment time dramatically. 

• Health organizations eager to integrate AI into their workforce should mirror regulatory policies with a layer of auditing of these systems for recruitment bias and data protection.

• By identifying skill gaps, early burnout signals, limited leadership access and low awareness of new concepts, organizations can invest in their workers with budget friendly and impactful AI solutions. 

• Proximate Learning partners with health departments, hospital systems, and community health centers to thoughtfully integrate AI into strategic alignment and development of employees ensuring that technology enhances, rather than replaces, the humanness of the health workforce.

References 

Chen Z. (2023). Collaboration among recruiters and artificial intelligence: removing human prejudices in employment. Cognition, technology & work (Online), 25(1), 135–149. https://doi.org/10.1007/s10111-022-00716-0

Hunkenschroer, A. L., & Kriebitz, A. (2023). Is AI recruiting (un)ethical? A human rights perspective on the use of AI for hiring. AI and ethics, 3(1), 199–213. https://doi.org/10.1007/s43681-022-00166-4

Illinois General Assembly. (2024). House Bill 3773: An Act concerning business (103rd Gen. Assemb.). Public Act 103-0804.https://legiscan.com/IL/bill/HB3773/2023.