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Licensed Practical NursesvsRegistered Nurses

Registered Nurses is 25 points more exposed than Licensed Practical Nurses (34 against 9) and its window opens 3 years earlier.

Licensed Practical Nurses
Registered Nurses

Exposure

Licensed Practical Nurses
9

Low exposure

More exposed than 1% of 250 roles

Registered Nurses
34

Moderate exposure

More exposed than 18% of 250 roles

Window · adoption

7–15 yrs

until most of the change has landed

Low-Medium adoption

4–9 yrs

until most of the change has landed

Medium adoption

In one line

AI touches charting, scheduling and monitoring alerts, but bedside care, medication rounds and patient observation remain hands-on work.

AI augmenting diagnostics, monitoring, and administrative tasks.

Inputs behind the score · scaled 0–100

Task applicability

7

Observed usage

0

Official exposure tier

10

Labour-market trajectory

n/a

Published adoption rating

25

Task applicability

24

Observed usage

8

Official exposure tier

70

Labour-market trajectory

36

Published adoption rating

40

What is driving it

  1. Low generative-AI task overlap
  2. Health record documentation features
  3. Patient monitoring and early-warning systems
  4. Automated dispensing and supply logistics
  5. Workforce shortages
  6. Slow adoption in long-term care
  1. Need to Improve Patient Outcomes & Safety
  2. Shortage of Healthcare Professionals & Staff Burnout
  3. Advancements in AI for Medical Image Analysis & Diagnostics
  4. Availability of Large Healthcare Datasets (for AI training)
  5. Demand for More Efficient Healthcare Delivery
  6. Rise of Telehealth & Remote Patient Monitoring
  7. Focus on Personalized Medicine & Care
  8. Pressure to Reduce Healthcare Costs
  9. Integration of AI into Electronic Health Record (EHR) Systems
  10. Patient Expectations for More Accessible & Proactive Care

Skills worth building

  1. Clinical observation and assessment
  2. Hands-on procedural competence
  3. Working with monitoring systems
  4. Health record fluency
  5. Communication and reassurance
  6. Career progression planning
  1. Clinical Judgment & Critical Thinking
  2. Empathy & Patient Communication
  3. Technical Proficiency with AI Clinical Tools
  4. Data Interpretation & Validation
  5. Interdisciplinary Collaboration (with AI insights)
  6. Adaptability & Continuous Learning (of new tech)
  7. Ethical AI Application & Patient Privacy
  8. Patient Advocacy in an AI-Augmented Setting

Tools in the work now

  1. Epic
  2. Oracle Health
  3. Omnicell
  4. care.ai
  1. Epic / Cerner (EHRs with increasing AI capabilities)
  2. Viz.ai (AI for stroke detection and care coordination)
  3. Current Health / Biofourmis (Remote Patient Monitoring & AI Analytics)
  4. Nuance Dragon Medical One (Voice recognition for clinical documentation)
  5. Various internal predictive models developed by hospital systems (e.g., for sepsis prediction)

Where the work moves

Medical Transcriptionists55

More exposed

Registered Nurses34

Different skills, growing

Healthcare Assistants19

Complementary, less exposed

Medical Records & Health Information Technicians (Basic data entry/coding)

More exposed

Healthcare Data Scientists / AI in Healthcare Developers

Different skills, growing

Physicians (Complex Diagnostics & Treatment Planning)

Complementary, less exposed

Full report

Read Licensed Practical Nurses
Read Registered Nurses

Scores are the CareerGuard Exposure Index v2: the same five inputs and weights for every role, so a gap of ten points means the same thing wherever it appears. How scores are built.