Strategies to Close AI Literacy Gaps Among Nursing Professionals Through Academic Curricula and Continuous Bedside Learning Approaches

The integration of artificial intelligence (AI) within healthcare is changing how patient care is given across the United States. Nurses, especially, are at the front of this change. They use advanced digital tools to help with clinical decisions, monitor patients, and handle administrative work. Even though AI is becoming more common, many nurses find it hard to use these technologies well because they lack AI knowledge. Medical practice managers, clinic owners, and IT staff need to know how to close these knowledge gaps to keep healthcare safe, efficient, and compliant.

This article talks about current methods for addressing AI knowledge gaps among nurses by improving nursing school programs and ongoing learning at the bedside. It also looks at how workflow automation using AI tools can improve clinical and office tasks.

The Importance of AI Literacy in Nursing

Artificial intelligence is not just a new technology; it affects patient safety, care quality, and how clinical work flows. Nurses use AI applications to watch patient vital signs, predict health issues, manage electronic health records (EHR), and help communication between healthcare workers. Without enough AI understanding, nurses may find it hard to correctly read AI results or notice when AI makes mistakes or is biased.

Stephanie H. Hoelscher and Ashley Pugh wrote in Nursing Outlook (Volume 73, Issue 4, July–August 2025) that knowing AI is necessary for safe and good patient care. They suggest a framework called N.U.R.S.E.S., which means:

• Navigate AI basics
• Utilize AI strategically
• Recognize AI pitfalls
• Skills support
• Ethics in action
• Shape the future

This framework helps bring together AI knowledge, ethical use, and skill building so nurses can keep up with fast technology changes in clinical settings across the U.S.

Closing AI Literacy Gaps Through Academic Curricula

Nursing schools in the U.S. play a key role in preparing nurses for technology-filled healthcare. But studies show there are big gaps in how AI and related digital health ideas are taught. This causes differences in skills and knowledge among new nurses.

Several ways have worked well to add AI learning into nursing education:

1. Embedding AI Fundamentals into Core Curricula

Teaching AI basics—like how algorithms work, learning by machines, and AI uses in healthcare—should be part of required nursing classes. This basic knowledge helps students get familiar with AI’s growing role, from helping diagnosis to automating workflow.

For example, Dr. Errol S. Luders studied 339 undergraduate nursing students using digital skills toolkits that include AI and data analysis. These toolkits were liked for being useful and easy to use, helping students keep learning.

2. Using Simulation-Based Learning and AI-Powered Tools

Simulation training lets nursing students practice what they learn in safe, real-like situations. Creighton University College of Nursing made an AI chatbot for practicing tough conversations near the end of life. This tool lets students repeat practice and gain confidence while learning how AI works in clinical talks.

Simulations let students try clinical cases with AI help, growing their thinking skills without stress. This better prepares students to make smart choices when using AI in hospitals.

3. Emphasizing Critical Thinking About AI Limitations

It’s important to teach students about problems AI might cause, like biased data or ethical questions. AI that learns from unfair data can give wrong or unfair advice. Nurses must learn to spot and fix these problems when caring for patients.

Classes about ethics and discussion groups on AI use help students learn about patient privacy, data safety, and being clear when using AI tools. This focus on responsible AI matches the advice of Stephanie H. Hoelscher and Ashley Pugh.

4. Offering Targeted Online and Blended Learning Modules

Online classes about digital health information have shown good results. For example, a study in China found targeted online training helped nursing students know more and feel better about digital tools. Nursing programs in the U.S. can do the same by giving flexible, easy-to-access courses that fit busy work schedules.

Blended learning, which mixes online lessons with in-person workshops or mentoring, supports different learning styles and helps keep improving skills over time.

Continuous Bedside Learning for Practicing Nurses

While initial training is needed, AI keeps changing fast. Practicing nurses need ongoing education. Connecting school learning with real work needs planned bedside learning methods.

1. Mentorship and Peer Learning

In busy hospitals, mentorship programs help bring AI knowledge into everyday work. Experienced nurses who know digital tools guide others in understanding AI workflows and machine-made recommendations. Learning from peers also helps share good ideas, fix AI problems, and keep improving.

2. Simulation and Workshops in Clinical Environments

Besides school simulations, practice in hospitals lets nurses refresh and grow AI skills safely. Workshops offer hands-on practice with new AI tools linked to electronic records, remote monitoring, and clinical decision support systems (CDSS).

These close-to-real experiences build nurse confidence and skills, lowering mistakes made by guessing during patient care.

3. Integrating AI Literacy Into Mandatory Continuing Education

Healthcare groups like The Joint Commission and Centers for Medicare & Medicaid Services require nurses to do yearly continuing education. Adding AI learning and ethics to these courses makes sure nurses update skills and stay aware of new AI rules.

AI and Workflow Enhancements in Nursing Practice

Healthcare work is becoming more digital and often depends on AI automation. This changes not just care but also front-office and admin work needed for clinics and hospitals to run well.

1. Front-Office Phone Automation and AI Answering Services

Companies like Simbo AI focus on front-office phone automation using AI. In medical offices, front-desk staff handle many calls about appointments, patient questions, and insurance. Automating these calls cuts down human work and helps answer patients faster without lowering service quality.

AI answering systems can sort calls, send patients to the right places, and free front-desk teams to focus on harder tasks. This helps nurses by making communication easier and letting them concentrate on patient care rather than paperwork.

2. AI-Driven Clinical Decision Support and Documentation

In clinical work, AI tools help nurses by reading lots of patient data, sending alerts about possible problems, and suggesting treatments based on evidence. Automation saves time on paperwork, improves accuracy, and stops mistakes.

Electronic health records that work with AI make decision-making faster and safer. Nurses with AI knowledge can use these tools better, improving their teamwork in patient care.

3. Enhanced Workflow Through Predictive Analytics

AI-based predictive tools help nurses guess patient needs early, like fall risks, infections, or medicine reactions before signs get worse. These early warnings let nurses act faster and give care suited to each patient.

Adding this technology in daily nursing work needs training so nurses can understand alarms and respond right. This shows why ongoing AI education is important.

Recommendations for Healthcare Administrators and IT Managers

For those managing nursing workflows in U.S. healthcare, here are some ways to help close AI knowledge gaps:

• Work with Nursing Educators: Join with local nursing schools to create curricula that cover AI basics and clinical uses related to your facility.
• Invest in Simulation Tools: Buy and use simulation programs like AI chatbots and virtual training for both students and working nurses.
• Create Mentorship Programs: Find nurse leaders familiar with digital tools to coach others for smooth AI use in daily work.
• Update Continuing Education: Add AI and digital health knowledge to required skills learning to keep nurses up to date.
• Check AI Workflow Solutions: Work with vendors such as Simbo AI to bring AI automation into front-office and admin tasks, freeing nurses’ time for patient care.
• Support Ethical AI Use: Set policies based on the N.U.R.S.E.S framework to guide fairness, privacy, and reducing bias in AI systems used at your organization.

Final Thoughts

Closing the AI knowledge gap among nurses is key for good, safe, and efficient healthcare in the U.S. Nursing schools must include digital health and AI skills in their classes. Healthcare organizations should create ongoing bedside learning chances that keep nurses updated on new technology. AI workflow automation, such as front-office phone systems made by companies like Simbo AI, helps lower administrative work and supports nurses in their care roles.

By combining education changes, continuous learning, and thoughtful AI use, healthcare managers and IT staff can help nursing teams confidently handle the future of healthcare tech.