The key need for nurses to play an active role in AI implementation

It is well known that artificial intelligence (AI) will change the industrial landscape and workforce dynamics in the United States. The implementation of AI in healthcare is no longer a futuristic concept, but a current reality. Nursing executives and leaders must participate in decisions to advance AI in the workplace. As the largest healthcare workforce, nurses are the primary cohort for implementing these technologies into patient care and daily workflows. However, their voices remain insufficient in AI conversations and plans.

When considering adoption barriers, there are several worth mentioning, some are broad and some are care-specific. The first is the lack of technical knowledge and skills. Nurses may not have a good spirit on the complexity of basic AI concepts and artificial intelligence systems. This limits their ability to effectively participate in discussions and decision-making in AI systems. The solution is triple: First, a comprehensive training program should be introduced at the academic and clinical level. Second, hospital systems and suppliers should include nurses early in the product plan and provide case-based learning opportunities. Finally, nurses must personally seek opportunities for continuing education to improve the knowledge base of AI for continuous professional improvement.

Another obstacle is resistance to change, which is usually caused by fear of unknowns. Without proper training and support, nurses may feel overwhelmed or reluctant to adopt AI tools. To overcome this, health system and commercial AI developers should provide ongoing, nurse-specific professional development. Nurses who are specially trained in AI include AI champions or liaisons into the unit, which can build local expertise and trust.

Data security issues, while often seen as technical or administrative challenges, are directly related to nursing participation. Nurse is on the frontline of patient interaction and will be responsible for interpreting the AI ​​system and ensuring that patients feel safe. If nurses are not actively involved in conversations about AI safety standards and patient education, trust in these systems can erode. Therefore, nurse leaders must advocate transparent and understandable data practices and participate in the Interdisciplinary Data Governance Committee.

General AI discussions often cite AI bias and the importance of architectural trust, but their relevance to care is specific and actionable. Without the investment of nurses, especially those AI systems built or trained for the input of people with diverse populations, critical blind spots may persist and may exacerbate health disparities. Nurses’ understanding of the social determinants of health, patient behavior, and workflow reality is critical to creating equitable, practical AI solutions. Their included in the design, testing and evaluation of these tools should not be optional, which is necessary.

Responsible for using AI is a barrier to multiple areas. I think the most important thing to do is the usability, reviewing AI technology and specific platforms to clearly determine whether it is solving problems or bringing efficiency into the process. Companies can show off attractive products that are eye-catching, but when you peel off the glossy cover, they don’t actually solve the current problem. This is not to say that they are not accomplishing anything, they do perform a task or a series of tasks, but if they are thoroughly evaluated, the results may not add value. Bias is another area that must be evaluated. This requires understanding of different forms of AI (genericity, supervised learning, etc.), what should be evaluated in the training dataset and how AI-driven decisions are made. Collaboration and participation are another important component of responsible use. Stakeholders, including patients and affected communities, should be involved to ensure that AI technologies are aligned with value, needs and goals.

A promising development at its main stage is the movement to include AI-specific content in nursing education. Nursing schools are beginning to include artificial intelligence in undergraduate programs, and a few universities offer master's degrees in nursing concentration in AI. These developments highlight the plans to incorporate AI education into the program to prepare future nurses for the evolving health care landscape.

A new way to support nurses is to increase the role of patient care technicians. The purpose of this role is to assist in nursing, support, track and troubleshoot patient care technology equipment to alleviate non-clinical tasks of nurses. For decades, technical responsibilities have been added to the nurse’s daily work without additional support. Uninstalling these distractions allows nurses to practice at the top of the range and focus on direct patient care.

Talking about AI is not enough, nurses must act. Although many people discuss the importance of AI, others are often outside of care and are always building and deploying it. Nurse can no longer see it as tomorrow’s problem. We must move forward immediately.

AI has the hope of improving healthcare delivery, enhancing patient outcomes, and enabling clinicians to focus their time on patient relationships. For care to shape its future in an AI-driven world, its leaders and practitioners must be present, understand and participate in the steps of its development and deployment. The industry’s authenticity, ethical foundation and focus on patient-centered care make nurses essential for responsible, effective implementation of healthcare AI.

Photo: Saengsuriya13, Getty Images

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