Task augmentation, automation, and hybridization in nursing: A conceptual framework for artificial...

Area of Science:

• Nursing Informatics
• Healthcare Management
• Sociotechnical Systems Theory

Background:

• Artificial intelligence (AI) integration is transforming nursing roles and tasks.
• A lack of a guiding framework exists for understanding AI's interaction with nursing practice.

Purpose of the Study:

• To propose a conceptual framework for AI in nursing.
• Utilizes sociotechnical systems theory and task-technology fit.
• Illustrates AI's potential to augment, automate, and hybridize nursing work.

Main Methods:

• Exploratory literature review.
• Covered nursing, organizational theory, information systems, and management.
• Identified patterns in task characteristics, human-technology interaction, and organizational context.

Main Results:

• Framework links AI interaction types (augmentation, automation, hybridization) with task categories (manual, cognitive, routine).
• Routine tasks are suitable for automation.
• Complex tasks benefit from augmentation or hybridization, influenced by governance.

Conclusions:

• Provides a structured approach for nurse leaders, educators, and clinicians.
• Aids in anticipating AI's impact on nursing practice.
• Supports ethical AI implementation and curriculum development for future nursing care.