Empathic and agentic artificial intelligence in nursing: perspectives on a human-centered framework for cancer care navigation in the United States
Researchers propose a human-centered AI framework designed to support nurses in cancer care navigation by integrating empathic and agentic approaches grounded in nursing ethics. The framework aims to address gaps in care coordination in under-resourced areas of the United States where trained nurse navigators are scarce, augmenting rather than replacing human clinical judgment.
This perspective addresses a critical healthcare infrastructure gap in the United States where cancer patients in under-resourced regions lack adequate nurse navigation support. The proposed framework represents a pragmatic approach to healthcare technology that prioritizes human-centered design principles rather than full automation, acknowledging that nursing fundamentally involves empathy and ethical decision-making that cannot be entirely delegated to machines.
The context reflects broader healthcare trends where AI-enabled digital tools proliferate without sufficient consideration for integration with existing clinical workflows or alignment with professional ethical standards. Most current digital health solutions operate independently rather than supporting nurses' core responsibilities, creating friction rather than facilitating care delivery. This article highlights how technology adoption in healthcare requires grounding in professional values and practice realities.
For healthcare technology developers and health systems, the framework offers guidance on designing AI tools that enhance rather than undermine clinical relationships. By anchoring AI development in the American Nurses Association's code of ethics, the authors demonstrate how technology governance can balance innovation with professional integrity. This approach could influence how healthcare institutions evaluate and implement AI solutions, potentially creating market demand for ethically-aligned platforms.
Looking forward, successful implementation depends on healthcare systems' willingness to invest in nurse-centric technology design and clinical validation studies demonstrating improved outcomes. The emphasis on under-resourced areas suggests potential policy implications regarding healthcare equity and technology funding priorities. Developers who align AI solutions with clinical professional standards may gain competitive advantages in healthcare markets increasingly scrutinized for ethical AI deployment.
- →AI frameworks for healthcare must prioritize augmenting rather than replacing human clinical judgment and empathy in nursing practice.
- →Integrating professional ethical standards (ANA code of ethics) into AI design improves alignment with clinical workflows and patient care goals.
- →Under-resourced healthcare areas represent significant opportunities for responsible AI deployment that addresses care coordination gaps.
- →Healthcare technology adoption requires grounding in how clinical professionals actually work, not just technical capabilities.
- →Nurse-centric AI design may create competitive advantages for developers in increasingly regulated healthcare technology markets.