The Critical Need For Nurses To Play An Active Role In AI Implementation

It is well recognized that artificial intelligence (AI) will transform the American industrial landscape and workforce dynamic. The implementation of AI in healthcare is no longer a futuristic concept, it is a current reality. Nurse executives and leaders must participate in decisions advancing AI in the workplace. As the largest healthcare workforce, nurses are the principal cohort tasked with implementing these technologies into patient care and daily workflows. Yet, their voices remain underrepresented in AI conversations and planning.

When considering barriers to adoption there are several worthy of mention, some broad, and some specific to nursing. The first is lack of technology knowledge and skill.  Nurses may not be well-versed in foundational AI concepts and the complexities of AI systems. This limits their ability to effectively partake in discussions and decisions around AI systems. The solution is threefold: first, comprehensive training programs should be introduced at both the academic and clinical levels. Second, hospital systems and vendors should include nurses early in product planning and provide real-time, case-based learning opportunities. Lastly, nurses must personally seek continuing education opportunities to improve their knowledge base of AI for continual professional improvement. 

Another barrier is resistance to change, which often stems from fear of the unknown. Without proper training and support, nurses may feel overwhelmed or reluctant to adopt AI tools. To overcome this, health systems and commercial AI developers should offer ongoing, nurse-specific professional development. Integrating AI champions or liaisons within units, nurses with specialized training in AI, can build local expertise and trust.

Data security concerns, though often viewed as a technical or administrative challenge, are directly relevant to nursing engagement. Nurses are on the front lines of patient interaction and will be tasked with explaining AI systems and ensuring patients feel safe. If nurses are not actively involved in conversations about AI security standards and patient education, trust in these systems may erode. Therefore, nurse leaders must advocate for transparent and comprehensible data practices and participate in interdisciplinary data governance committees.

Bias in AI and the importance of building trust are often cited in general AI discussions, but their relevance to nursing is specific and actionable. If AI systems are built or trained without the input of nurses, especially those serving diverse populations, critical blind spots may persist, potentially worsening health disparities. Nurses’ knowledge of social determinants of health, patient behaviors, and workflow realities is essential in creating fair, practical AI solutions. Their inclusion in the design, testing, and evaluation of these tools should not be optional, it is necessary.

Responsible use of AI is a barrier that incorporates several areas. I would contend that the most important, and one that should be completed first, is usability, vetting AI technology and specific platforms to clearly determine if it is solving a problem or bringing efficiency to a process. Companies can present compelling, attractive products, yet when you peel back the glossy cover, they do not actually address a current problem. This is not to say they don’t accomplish anything, they do perform a task or series of tasks, yet if thoroughly evaluated, the results may not be of added value. Bias is another area that must be assessed.  This requires knowledge of the different forms of AI (generative, supervised learning, etc.), what should be evaluated in training data sets, and how AI-driven decisions are made.  Collaboration and engagement are another important component of responsible use.  Stakeholders, including patients and affected communities, should be involved to ensure that AI technology aligns with values, needs, and goals. 

A promising development in its primary stages is a movement to include AI specific content in nursing education. Nursing schools are beginning to integrate AI into undergraduate coursework, and a select few universities are offering master’s in nursing concentrations in AI.  These developments highlight a broader trend of integrating AI education into programs to prepare future nurses for the evolving healthcare landscape. 

A novel approach to support nurses is the addition of a patient care technology technician role. The goal of the role is to assist in care, support, tracking and troubleshooting of patient care technology devices relieving nurses of non-clinical tasks. For decades, technology responsibilities have been added to nurses’ routines without additional support. Offloading these distractions enables nurses to practice at the top of their scope and focus on direct patient care.

It is not enough to talk about AI, nurses must act. While many have discussed the importance of AI, others, often outside of nursing, have been building and deploying it. Nurses can no longer afford to view this as tomorrow’s issue. We must step forward now.

AI holds the promise of improved healthcare delivery, enhanced patient outcomes, and empowering clinicians to focus time on patient relationships. For nursing to shape its future in an AI-driven world, its leaders and practitioners must be present, informed, and engaged in every step of its development and deployment. The profession’s authenticity, ethical grounding, and focus on patient-centered care make nurses indispensable to the responsible and effective implementation of healthcare AI.

Photo: saengsuriya13, Getty Images

This post appears through the MedCity Influencers program. Anyone can publish their perspective on business and innovation in healthcare on MedCity News through MedCity Influencers. Click here to find out how.