AI And The Healthcare Workforce: What Changes First
Across interviews with health leaders, one theme kept coming up: AI is here to assist, not replace. Expect work to shift, capacity to rise and new skills to matter more than job titles.
This is a practical look at where automation lands first, which roles will feel it, and how to prepare teams without losing what makes care human.
Where Automation Hits First
Repetitive, protocol-driven work is the low-hanging fruit. Eyal Zimlichman at Sheba points to frontline administration, call centers and office management. Several leaders echoed that documentation, scheduling and routine coordination are squarely in scope.
- Medical scribes and stenographers are most exposed (Orr Inbar).
- Revenue cycle, prior auth and other back-office workflows face steady automation pressure (Matt Cybulsky).
- Chart summarization, basic reporting, reminders and data gathering get offloaded to AI "assistants" (Cherry Drulis, Julius Bruch, Ricky Bloomfield).
- Imaging: first-pass triage, prioritization and motion correction can be automated, letting radiology teams focus on difficult reads (Roland Rott).
Clinical Work: Augmented, Not Replaced
Leaders were clear: clinicians stay in the loop. AI strips away routine tasks so nurses and doctors can work at the top of their license (Zimlichman). It compresses documentation time and reduces cognitive load so attention goes back to patients (Julia Strandberg).
In practice, that means faster access to the right data at the right moment, and fewer fragmented workflows. Radiologists, technologists and therapists keep the judgment and the patient conversations; AI helps with throughput, prioritization and decision support (Rott, Bruch, Drulis).
There's also a caution: automation should not dilute clinical judgment or context (Cybulsky). Use AI to reduce burden and close care gaps, not to replace trust (Bloomfield).
New Roles And Skills Will Emerge
Expect fresh talent pipelines: systems engineering, industrial design and product disciplines that build tools clinicians actually want to use (Daryl Tol). Health systems will also need people who oversee algorithms, audit bias and translate outputs into safe, usable actions (Shlomi Madar).
As routine tasks fall away, redeploy staff into higher-value coordination and patient-facing work that needs nuance and accountability (Edmund Jackson). This is capacity expansion without a one-for-one increase in headcount (Shai Policker).
What This Means For Your Team
- Map work by task, not title. Flag repetitive, rules-based steps for automation: intake, registration, scheduling, chart summaries, basic messages.
- Lock in human-in-the-loop points. Define what only clinicians do, and what AI drafts that humans review.
- Upskill quickly. Build AI literacy for clinicians and admins, from prompt craft to verification. If you want structured options, see AI courses by job.
- Stand up governance. Bias audits, performance monitoring, incident paths and rollback plans. For reference, review the WHO guidance on AI for health and the FDA's AI/ML SaMD resources.
- Measure what matters. Track throughput, no-shows, time-to-treatment, staff time saved, error rates and burnout signals. Reinvest saved time into patient touchpoints.
- Redeploy, don't discard. Transition scribes to care coordination, quality review or patient access. Move admin staff into navigation and outreach.
Roles Most Likely To Shift In 2026
- Most affected by automation: medical scribes/stenographers; call center agents; registration/front desk; revenue cycle specialists; imaging pre-read triage; routine office management.
- Augmented by AI: nurses, physicians, therapists, radiologists, technologists, care navigators, health coaches. These roles keep judgment, empathy and accountability while offloading busywork.
- Emerging roles: clinical AI leads, algorithm safety/QA, bias auditors, operational designers, data-centric product managers and "AI translators" between IT and care teams.
Bottom Line
No mass replacement. Work changes. The organizations that win will be the ones that remove low-value tasks, protect clinical judgment and redeploy people into higher-impact care.
Start small, measure outcomes, and build trust through reliable systems. The goal isn't fewer people; it's fewer distractions and better patient care with the team you already have.
Your membership also unlocks:
