OPINION: Staten Island Can Strengthen Healthcare Career Ladders For Local Students

Editor’s note: This authors most recent opinion piece discography discussed the need for greater training and workforce development programs to better prepare students and career minded professionals for the emerging AI technology and advances.  AI is likely to be the most transformative technology humanity has yet faced, and it is being hurtled into headlong without any guardrails and with very few questioning whether this is the appropriate path in the first place. 

Staten Island is already giving teens paid, hands-on healthcare experience through a 2026 youth internship program. Stanford’s August 12 update finds employment among U.S. workers ages 22–25 in highly AI-exposed occupations about 19% below where it would be if it had kept pace with less-exposed peers. For Island employers, AI savings should buy more supervised judgment, not fewer first assignments. I propose a healthcare-focused exception ladder that moves junior workers from routine preparation into verification, patient communication, privacy decisions, and supervised problem-solving.

STATEN ISLAND SHOULD MAKE AI STRENGTHEN HEALTHCARE CAREER LADDERS

Staten Island has a useful model for the AI era sitting in plain sight: paid, supervised work experience.

A 2026 Staten Island youth internship program combines work-readiness training with six weeks of hands-on internships at local healthcare organizations. Participants practice professional communication, patient privacy, career planning, and real workplace behavior under supervision.

That is exactly the kind of learning employers should protect as AI becomes better at routine office preparation.

Stanford’s August 12 employment update uses ADP payroll data covering millions of U.S. workers through June 2026. Employment among workers ages 22–25 in highly AI-exposed occupations stands about 19% below where it would be if it had kept pace with similarly aged workers in less-exposed occupations. The comparable measure was 15% at the July 2025 data vintage. The adjustment appears mainly through reduced hiring, and experienced workers show no comparable gap.

That pattern should change how Staten Island healthcare employers deploy AI.

Automating routine preparation can be useful. AI can summarize background material, draft basic messages, organize notes, and help prepare standard documents. The management mistake is treating those saved minutes as a reason to remove the junior employee who would have learned from doing the work.

Instead, use the saved time to move that employee one rung higher.

A new hire who no longer spends an hour assembling routine information can spend that hour checking AI output against the record, identifying missing context, preparing questions for a supervisor, handling unusual cases, explaining next steps to patients or families, and learning when a standard procedure no longer fits the situation.

Healthcare makes the stakes concrete. Judgment about privacy, escalation, communication, and exceptions grows through repeated exposure to real situations. An organization cannot build that experience by giving every consequential case to senior staff and every routine task to software.

Managers should create an exception ladder for junior workers. Start with routine AI-assisted preparation. Then require verification. Next, assign low-risk exceptions under review. Add patient or colleague communication. Finally, move the employee toward independent decisions with a named experienced coach accountable for feedback.

The key metric should be time to independent competence. Cost per task and hours saved still matter, but they do not show whether the organization is producing the next generation of experienced workers.

Staten Island’s youth healthcare internships already recognize that people learn by doing real work with guidance. Employers adopting AI should carry that principle into full-time entry-level jobs. The best use of automation is to accelerate apprenticeship, so younger workers reach judgment-rich responsibilities faster.

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Banner Image: Artificial intelligence robot. Image Credit – Andy Kelly