Provide advanced nursing care for patients with acute conditions such as heart attacks, respiratory distress syndrome, or shock. May care for pre- and post-operative patients or perform advanced, invasive diagnostic or therapeutic procedures.
U.S. Workers
3,282,010
Median Salary
$93,600
10-Year Growth
+4.9%
Annual Openings
189,100
Typical entry: Bachelor's degree
25 of 27 tasks have some AI capability
Exposure Trend
This score reflects estimated AI technical capability for tasks in this occupation. It does not predict employment changes, and it does not account for company-specific constraints, regulation, or adoption barriers.
Document data related to patients' care including assessment results, interventions, medications, patient responses, or treatment changes.
AI: Fully automatable - AI systems in 2025 can reliably generate, structure, and populate clinical documentation from inputs and EHR data end‑to‑end, with human review as needed for legal sign-off.
Interpret information obtained from electrocardiograms (EKGs) or radiographs (x-rays).
AI: Fully automatable - Validated AI models already interpret many EKGs and radiographs with high accuracy and can produce clinically useful reads autonomously for a large portion of cases.
Perform administrative duties that facilitate admission, transfer, or discharge of patients.
AI: Fully automatable - Most admission/transfer/discharge administrative tasks (forms, scheduling, documentation, notifications) are routine, structured, and automatable with EHR integration and workflow automation available by 2025.
Assist patients in organizing their health care system activities.
AI: Fully automatable - AI systems in 2025 can reliably automate care‑navigation tasks such as scheduling, reminders, referrals, and information coordination given appropriate data access and integrations.
Perform emergency medical procedures, such as basic cardiac life support (BLS), advanced cardiac life support (ACLS), and other condition stabilizing interventions.
AI: Partial - AI can guide and augment emergency procedures with instructions and monitoring, but cannot perform the requisite hands-on life‑saving interventions autonomously.
Manage patients' pain relief and sedation by providing pharmacologic and non-pharmacologic interventions, monitoring patients' responses, and changing care plans accordingly.
AI: Partial - AI can recommend analgesic/sedation plans, monitor responses, and suggest adjustments, but medication administration and nuanced bedside titration require clinician oversight and hands‑on care.
Administer blood and blood product transfusions or intravenous infusions, monitoring patients for adverse reactions.
AI: Partial - AI can monitor IV infusion data and detect early adverse-reaction signals or remind clinicians, but it cannot physically administer transfusions or assume full clinical responsibility for hands-on management.
Diagnose acute or chronic conditions that could result in rapid physiological deterioration or life-threatening instability.
AI: Partial - AI can assist with rapid risk detection and differential diagnosis for unstable conditions but cannot be entrusted to autonomously make final high‑stakes diagnoses without clinician confirmation.
Assess urgent and emergent health conditions using both physiologically and technologically derived data.
AI: Partial - AI can analyze physiologic and device-derived data to support triage and flag emergencies, but comprehensive urgent/emergent assessment requires in-person examination and clinical judgment.
Adjust settings on patients' assistive devices such as temporary pacemakers.
AI: Partial - AI can recommend optimal device settings and monitor telemetry, but the physical adjustment and legal/clinical responsibility for high‑risk devices like temporary pacemakers require trained clinicians.
Assess the impact of illnesses or injuries on patients' health, function, growth, development, nutrition, sleep, rest, quality of life, or family, social and educational relationships.
AI: Partial - AI can synthesize clinical and patient-reported data to characterize impacts on function and quality of life, but holistic assessment involving nuanced psychosocial context and judgment remains human-led.
Prescribe medications and observe patients' reactions, modifying prescriptions as needed.
AI: Partial - AI can generate medication recommendations, flag interactions, and suggest dose adjustments based on data, but autonomous prescribing and clinical responsibility for monitoring and modifying therapy remain clinician tasks under current regulations and safety limits.
Collaborate with patients to plan for future health care needs or to coordinate transitions and referrals.
AI: Partial - AI can generate care plans, identify needs, and coordinate logistics, but true collaboration with patients about goals and preferences requires human communication and shared decision-making.
Refer patients for specialty consultations or treatments.
AI: Partial - AI can identify indications and draft or automate referral paperwork based on guidelines, but initiating and authorizing referrals typically requires clinician judgment and workflow integration.
Set up, operate, or monitor invasive equipment and devices such as colostomy or tracheotomy equipment, mechanical ventilators, catheters, gastrointestinal tubes, and central lines.
AI: Partial - AI can monitor device parameters and assist with ventilator adjustments or alarms, but setting up and managing invasive equipment still requires hands-on clinical skills and sterile technique.
Discuss illnesses and treatments with patients and family members.
AI: Partial - AI can provide clear explanations and script or support difficult conversations, but sensitive discussions about illness and treatment generally require human empathy and professional responsibility.
Distinguish between normal and abnormal developmental and age-related physiological and behavioral changes in acute, critical, and chronic illness.
AI: Partial - AI can detect deviations from normative developmental and age-related patterns using data, yet distinguishing complex clinical versus adaptive changes in varied contexts still needs expert clinical interpretation.
Order, perform, or interpret the results of diagnostic tests and screening procedures based on assessment results, differential diagnoses, and knowledge about age, gender and health status of clients.
AI: Partial - AI can interpret many diagnostic tests and suggest screening decisions based on demographics and differential diagnoses, but cannot legally or physically perform or independently order tests without clinician oversight and hands‑on capability.
Collaborate with members of multidisciplinary health care teams to plan, manage, or assess patient treatments.
AI: Partial - AI can analyze records, suggest care plans, and draft contributions for team discussion but cannot fully assume the interpersonal coordination, clinical responsibility, and real‑time judgment a nurse provides in multidisciplinary collaboration.
Assess the needs of patients' family members or caregivers.
AI: Partial - AI tools can screen, suggest resources, and generate family‑education materials but lack the empathetic interviewing, nuanced psychosocial judgment, and rapport-building required for a complete family/caregiver assessment.
Read current literature, talk with colleagues, and participate in professional organizations or conferences to keep abreast of developments in acute care.
AI: Partial - AI can continuously monitor and summarize literature and synthesize professional updates, yet it cannot replace human networking, conference participation, and professional judgment about adopting innovations.
Provide formal and informal education to other staff members.
AI: Partial - AI can generate curricula, simulations, and educational content and can even deliver modules, but it cannot fully replicate in-person mentorship, adaptive teaching, and role-modeling that nurses provide.
Analyze the indications, contraindications, risk complications, and cost-benefit tradeoffs of therapeutic interventions.
AI: Partial - AI can synthesize evidence to analyze indications, contraindications, risks and cost–benefit tradeoffs, but patient‑specific value judgments and final therapeutic decision‑making still require clinician responsibility.
Participate in patients' care meetings and conferences.
AI: Partial - AI can prepare case summaries, suggest discussion points, and even join virtual meetings for information delivery, but it cannot fully replace a nurse's bedside advocacy, interpersonal communication, and responsibility in care conferences.
Participate in the development of practice protocols.
AI: Partial - AI can draft evidence‑based protocol proposals, analyze data, and simulate outcomes, but human clinicians must lead consensus, ethical decisions, and contextual adaptation for final protocol development.
Obtain specimens or samples for laboratory work.
AI: Not automatable - Obtaining specimens requires manual dexterity, infection-control technique, and hands-on procedural skills that AI systems cannot perform autonomously in typical clinical settings as of 2025.
Treat wounds or superficial lacerations.
AI: Not automatable - Treating wounds and lacerations is a hands‑on clinical procedure requiring manual skill, aseptic technique, and real‑time tactile assessment that AI cannot perform autonomously.