Stop Waiting For ‘AI-Native’ Clinicians, Invest in Upskilling Now

Published on February 1, 2026

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Urgent Message: Invest in artificial intelligence upskilling across your organization by dedicating resource time and funding for educational activities. It’s a critical strategy for urgent care operators to improve staff retention and operational readiness.

Keywords: clinician upskilling; AI literacy; workflow adoption; clinical documentation; decision support; change management

Burnout remains a serious consideration across healthcare, and urgent care is no exception. At the same time, artificial intelligence (AI) is reshaping how we deliver and manage care. To retain and re-engage our people while preparing for the AI era, we have to remove the 2 real barriers to learning AI: the time commitment and the up-front costs of upskilling. When we address time and cost barriers, people actually put AI into practice. When they practice, they get better. When they get better, they stay.[1]

Why This Matters Right Now

The need for AI skills is rising faster than clinician and staff confidence in such skills. In national polling, clinicians identify AI as the top clinical/technical skill they’ll need in the next 5 years, yet few feel comfortable using AI today. Employers largely agree that AI training is a priority, but many struggle to provide on-the-job resources that make learning realistic. Participation in education benefits remains low not because people don’t care but because of practical barriers—time and cost—stand in the way. Give staff time on the clock and up-front funding (not educational reimbursement after the fact) for AI upskilling, and participation climbs.¹

At the same time, retention is a challenge—more than half of early-career employees say they’ll look for a new role in the next year. Education benefits are powerful loyalty drivers that can improve retention, especially for early-career staff. If we want to stabilize teams, upskilling cannot be a perk reserved for a few. It has to become part of how we run our organizations.¹

We’re All ‘Techies’

In urgent care, AI excellence isn’t about turning everyone into a coder or a “prompt guru.” The people who thrive with AI tend to be good at breaking down complex tasks, troubleshooting, anticipating points of confusion, and keeping human judgment at the forefront—key strengths many top clinicians and managers already possess. When we create space to practice with AI, those human strengths accelerate forward progress.[2]^,[3]

Even so, the benefits aren’t limited to a few early adopters. For knowledge workers, AI can lift speed and quality substantially, with the largest gains accruing among below-median performers. In other words, if we help everyone learn AI tasks—and teach them how to supervise the output—our whole clinic improves, not just our stars.

Meanwhile, physician use of health AI has increased sharply as more physicians aim to reduce administrative burdens. The question is whether leaders let such learning happen haphazardly or whether well organized funding, time allocation, policies, and coaching are delivered with consistent, safe practices across all roles in the organization.[4]^,[5]

Focus on Workflows

Too many AI initiatives start with a tool, even though the value isn’t in the tool itself; it’s in how we redesign the workflow so people and technology work together. That means mapping the steps—clinical, operational, and administrative—then deciding where AI adds speed or quality and where human sign-off is mandatory. Sometimes the right solution might include rules-based automation, smart templates, or a targeted model behind a simple checklist.[6]

Trust is earned through evaluation of the output by end-users. Treat new AI models like a new hire: give them a clear job description, onboard them, evaluate performance against real tasks, and provide feedback so they improve over time. Build observability into the workflow so you can see if anything went wrong—and fix it.⁶

Lead Like a Gardener

Another trap is trying to build out an entire AI program from the top down. The organizations that pull ahead are those that behave more like gardeners than carpenters: They look for the sprouts of innovation already growing on the front lines and help those ideas spread. That requires incentives that reward learning and knowledge-sharing—not just usage. It also means running lots of small experiments with clear hypotheses, reporting honestly on what worked and what didn’t, and capturing the “why” so others can gain from the takeaways. Over time, that builds institutional memory as an enterprisewide advantage.[7]

For example, if a nurse practitioner has figured out a safer, faster way to create patient education materials with AI, or a registrar has learned how to clarify insurance requests with AI assistance, we should nurture those patterns, refine them together, and scale what works. That is the fastest path to real value.^3,7

Upskilling Is For Everyone

AI can improve the performance of nearly every position in urgent care if we invest in skills. That includes physicians, nurse practitioners, physician assistants, medical assistants, front desk and registration, radiology techs, billing, human resources, and center managers. State the goal and constraints clearly; break work into steps; ask AI to draft, summarize, retrieve, or check; verify the AI result; and decide where human sign-off is required on the output. Those habits will endure even as the  tools themselves change.^2,3,6

Just as important: upskilling isn’t only about “prompt engineering.” It’s about understanding how your processes actually run, where your data lives, how reliable the data is, who the stakeholders are, and how to structure questions so the model returns something useful. The best training programs are tailored to your workflows and embedded into daily work, not bolted on as one-off experiences.

CME As An AI Upskilling Lever

The good news is that many urgent care organizations already fund continuing medical education (CME) stipends for clinicians, while also allowing dedicated time for CME activities. Across specialties, CME allowances commonly land in the $2,000–$4,000 range, with many physicians receiving 5-10 CME days annually. Emergency medicine leaders may provide a $4,000 CME/business expense benefit for their teams. For advanced practice providers, stipends in the $2,000–$3,000 range are common. Those are meaningful resource investments that we can deploy more strategically.[8]^{,[9],[10],[11]}

Two CME policy changes can encourage AI education:

1. Count AI learning toward CME benefits when possible. Accredited offerings in clinical AI, informatics, documentation support, patient safety, and equity have expanded recently. When training qualifies, use CME time and funds to cover it.
2. Update education policies to fund non-CME AI training that clearly builds job skills. Some of the highest-yield learning—hands-on practice with vendor tools, courses on data literacy and retrieval-with-citations, workflow “copilot” patterns, and basic evaluation techniques—may not provide CME credit. Cover them anyway. Treat these the same way you treat other employer-sponsored education: front the cost and schedule practice time on the clock.

How It Pays You Back

Here’s the return on investment proposition for urgent care:

• Pay for time. Give every clinician and staff member 30–60 minutes per week of protected “AI practice.” Label it explicitly so it doesn’t get swallowed by the day’s chaos.
• Front the cost. Shift from “pay now, reimburse later” to up-front funding. Two in 3 employees can’t afford to prepay their education fees.¹
• Keep it cross-functional and vendor-agnostic. Have mixed teams practice the same patterns of goal-setting, stepwise execution, verification, and sign-off. Reuse what works across roles.
• Measure simply and show your work. Tie participation to a handful of metrics you already trust, such as education-benefit utilization; 12-month retention; vacancy days; and just a few operational indicators your team cares about. Share your wins quarterly to keep up the team momentum.

This is a retention strategy as much as a capability strategy. Early-career clinicians—especially Gen Z—respond to employers who invest in their growth.

Here’s The Trade

Every urgent care runs tight. Blocking an hour per person per week can feel impossible. But compare that to the cost of turnover and the drag of constant backfill. A few hours of scheduled learning and a few thousand dollars in up-front education support are cheap relative to recruiting and onboarding—especially when the learning targets a capability we’ll need for the next 5 years or more. And because AI tends to lift the middle of the performance curve most, the benefits show up quickly across the team.[12]

The Commitment And The Ask

It’s not about becoming an “AI guru.” It’s about allocating time, fronting the cost, and practicing together with human judgment in charge. The landscape is moving weekly, not yearly. The leaders who win won’t wait for “AI-native” hires or a perfect product. They will build a learning culture that encourages trial and error, celebrates shared knowledge, and treats evaluation and safety as part of the craft.

If we do just that, we’ll turn anxiety into readiness and readiness into retention. We’ll have calmer clinics, more capable teams, and better care—no waiting required.

References

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1. [1]. Strategic Education Inc; The Harris Poll. Workforce Education Report: Healthcare 2025. September 2025. Accessed at https://www.strategiceducation.com/healthcare-workforce-survey/
2. [2]. Mollick E. Co-Intelligence: Living and Working with AI. New York, NY: Portfolio/Penguin; 2024.
3. [3]. McKinsey & Company. We’re all techies now: Digital skill building for the future. 2024. Accessed at https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/we-are-all-techies-now-digital-skill-building-for-the-future
4. [4]. American Medical Association. 2 in 3 physicians are using health AI—up 78% from 2023. News release. February 26, 2025. Accessed at https://www.ama-assn.org/practice-management/digital-health/2-3-physicians-are-using-health-ai-78-2023
5. [5]. American Medical Association. Physician enthusiasm grows for health care AI. News release. February 12, 2025. Accessed at https://www.ama-assn.org/press-center/ama-press-releases/ama-physician-enthusiasm-grows-health-care-ai
6. [6]. McKinsey & Company. One year of agentic AI: Six lessons from the people doing the work. September 2025. Accessed at https://www.mckinsey.com/capabilities/quantumblack/our-insights/one-year-of-agentic-ai-six-lessons-from-the-people-doing-the-work
7. [7]. McKinsey & Company. The learning organization: How to accelerate AI adoption. July 2025. Accessed at https://www.mckinsey.com/capabilities/strategy-and-corporate-finance/our-insights/the-learning-organization-how-to-accelerate-ai-adoption
8. [8]. Physician Side Gigs. Average CME Allowance and Days. Updated May 13, 2025. Accessed at https://www.physiciansidegigs.com/creative-and-unique-ways-to-use-cme-fund-money
9. [9]. American Medical Seminars. CME Allowances and Reimbursement: A Practitioner’s Guide. March 26, 2024. Accessed at https://www.americanmedicalseminars.com/cme-allowances-and-reimbursement/
10. [10]. American College of Emergency Physicians. 2025 Salary Survey Findings. August 11, 2025. Accessed at https://www.acep.org/siteassets/sites/acep/media/compensation-report/2025-salary-survey-findings.pdf
11. [11]. American Academy of PAs. Continuing Medical Education Optimization. 2024. Accessed at https://www.aapa.org/career-central/career-advancement-and-transitions/continuing-medical-education-optimization/
12. [12]. Dell’Acqua F, McFowland III E, Mollick E, et al. Navigating the jagged technological frontier: Field experimental evidence of the effects of AI on knowledge worker productivity and quality. Harvard Business School Working Paper 24-013; 2023. Accessed at https://www.hbs.edu/faculty/Pages/item.aspx?num=64700