Critical Care Nurses

Evaluate patients' vital signs or laboratory data to determine emergency intervention needs.

AI: Fully automatable - AI can analyze vital signs and laboratory data in real time to accurately identify patients who need emergency interventions and flag them for immediate action.

Compile and analyze data obtained from monitoring or diagnostic tests.

AI: Fully automatable - AI excels at aggregating, trend‑detecting, and analyzing monitoring and diagnostic data and can reliably compile and flag insights for clinicians in 2025.

Document patients' treatment plans, interventions, outcomes, or plan revisions.

AI: Fully automatable - By 2025 AI systems can accurately generate, populate, and update treatment plans and documentation from EHR data and clinician input, enabling full automation of note-writing and plan drafting (with human oversight for final responsibility).

Identify patients at risk of complications due to nutritional status.

AI: Fully automatable - AI models and clinical decision-support tools can analyze weight trends, labs, intake/output, and diagnoses to reliably identify patients at nutritional risk and trigger interventions.

Monitor patients for changes in status and indications of conditions such as sepsis or shock and institute appropriate interventions.

AI: Partial - AI can continuously monitor for deterioration and detect sepsis or shock early and recommend interventions, but cannot generally institute many required physical interventions without clinicians.

Set up and monitor medical equipment and devices such as cardiac monitors, mechanical ventilators and alarms, oxygen delivery devices, transducers, or pressure lines.

AI: Partial - AI can monitor device data and assist with configuration and alarms, but cannot reliably perform full physical setup, invasive line management, or hands-on device manipulation required in many cases.

Assess patients' pain levels or sedation requirements.

AI: Partial - AI can analyze vitals, facial expression, and monitoring data to estimate pain/sedation and provide decision support, but it cannot fully replace clinician judgment in complex critical care contexts.

Conduct pulmonary assessments to identify abnormal respiratory patterns or breathing sounds that indicate problems.

AI: Partial - Algorithms can detect abnormal respiratory patterns and analyze digital auscultation/ventilator waveforms, but bedside pulmonary assessment and nuanced interpretation still require clinicians.

Monitor patients' fluid intake and output to detect emerging problems, such as fluid and electrolyte imbalances.

AI: Partial - AI can compile intake/output from EHRs and sensors and detect trends or predict imbalances, but accurate measurement often depends on human-entered data and clinical validation.

Document patients' medical histories and assessment findings.

AI: Partial - AI can generate and populate medical histories and assessment notes from speech and data sources, but final documentation typically requires clinician verification and sign‑off.

Prioritize nursing care for assigned critically ill patients, based on assessment data or identified needs.

AI: Partial - AI can prioritize care by risk scoring and suggesting task lists from assessment data, yet complex prioritization in rapidly changing critical situations remains a clinician responsibility.

Administer blood and blood products, monitoring patients for signs and symptoms related to transfusion reactions.

AI: Partial - While AI can monitor for signs of transfusion reaction and alert staff, it cannot physically administer blood products or assume the attendant clinical responsibilities.

Collect specimens for laboratory tests.

AI: Partial - AI can guide, schedule, and in some experimental settings control robotic collection, but as of 2025 it cannot reliably perform sterile specimen collection across real-world clinical settings without human hands-on participation.

Collaborate with other health care professionals to develop and revise treatment plans, based on identified needs and assessment data.

AI: Partial - AI can synthesize data, propose treatment revisions, and facilitate communication, but true interdisciplinary collaboration and final plan decisions remain human duties.

Identify malfunctioning equipment or devices.

AI: Partial - AI can detect many device anomalies from logs, telemetry, and vision sensors and flag likely malfunctions, but it cannot yet comprehensively identify all hardware failures across diverse devices without human/technical confirmation.

Perform approved therapeutic or diagnostic procedures, based upon patients' clinical status.

AI: Partial - AI can assist decision-making, provide guidance, and in limited settings drive robotic procedures, but it cannot broadly perform the full range of approved therapeutic or diagnostic procedures autonomously in clinical practice by 2025.

Advocate for patients' and families' needs, or provide emotional support for patients and their families.

AI: Partial - AI can provide conversational support, resources, and decision aids and help prepare advocacy materials, but it cannot fully replace human advocacy and the nuanced emotional support provided by clinicians and family members.

Assess patients' psychosocial status and needs, including areas such as sleep patterns, anxiety, grief, anger, and support systems.

AI: Partial - AI can screen for psychosocial issues using questionnaires, passive data, and pattern recognition, but comprehensive, context-sensitive psychosocial assessment still requires human clinical judgment and rapport.

Assess family adaptation levels and coping skills to determine whether intervention is needed.

AI: Partial - AI can support assessment of family coping through structured surveys and synthesis of information, yet nuanced evaluation of family adaptation and the need for intervention remains primarily a human clinical task.

Ensure that equipment or devices are properly stored after use.

AI: Partial - AI and IoT can track equipment location, send reminders, and flag storage noncompliance, but physically ensuring devices are properly stored still depends on staff or robotic systems that are not universally deployed.

Coordinate patient care conferences.

AI: Partial - AI can schedule meetings, prepare agendas, and synthesize records to coordinate care conferences, but the interpersonal facilitation and final coordination across stakeholders typically require human leadership.

Identify patients' age-specific needs and alter care plans as necessary to meet those needs.

AI: Partial - AI can analyze patient data and age-specific guidelines to recommend care-plan adjustments but lacks clinical judgment and the hands-on assessment authority to do this fully.

Supervise and monitor unit nursing staff.

AI: Partial - AI can monitor staffing metrics, optimize schedules, and flag issues, but cannot fully replicate human supervisory duties such as leadership, delegation, conflict resolution, and real-time judgement.

Participate in professional organizations and continuing education to improve practice knowledge and skills.

AI: Partial - AI can curate continuing-education content, suggest learning plans, and automate tracking, but cannot genuinely participate in professional organizations, networking, or experiential learning that require human engagement.

Participate in the development, review, or evaluation of nursing practice protocols.

AI: Partial - AI can draft, review, and evaluate nursing protocols using evidence-based sources and simulations, but institutional review, clinical nuance, and stakeholder consensus still require human oversight.

Plan, provide, or evaluate educational programs for nursing staff, interdisciplinary health care team members, or community members.

AI: Partial - AI can design, deliver, and assess much of the educational content and evaluation, but cannot fully replace hands-on skills training, in-person facilitation, and adaptive teaching by experienced educators.

Administer medications intravenously, by injection, orally, through gastric tubes, or by other methods.

AI: Not automatable - Administering medications is a hands‑on clinical task requiring physical dexterity, real‑time judgment, and legal responsibility that AI cannot perform autonomously in 2025.

Assist physicians with procedures such as bronchoscopy, endoscopy, endotracheal intubation, or elective cardioversion.

AI: Not automatable - Assisting with invasive procedures requires hands‑on instrument handling, sterile technique, and situational responsiveness that AI cannot provide autonomously in typical clinical settings by 2025.

Provide post-mortem care.

AI: Not automatable - Post-mortem care requires hands-on, culturally sensitive physical tasks, legal handling, and emotional presence that AI cannot perform.