A university leader models a proactive approach.
GUEST COLUMN | by Edgar Chabolla
SAMUEL MERRITT UNIVERSITY
When AI first gained traction in education, fear dominated the conversation. The faculty worried about academic dishonesty, and universities responded with strict policies. But at SMU, we took a different approach—embracing AI as a tool to enhance learning and prepare students for an evolving workforce. While education for which pedagogy and academic traditions shape adoptions, often responds to new technology with caution, industry expects graduates to understand AI’s capabilities, ethical considerations and practical applications. Rather than focusing on misuse, we chose to be proactive—informing faculty about AI’s potential, guiding ethical use and integrating it where it adds value to education.
‘Rather than focusing on misuse, we chose to be proactive—informing faculty about AI’s potential, guiding ethical use and integrating it where it adds value to education.’
AI as a learning partner, not a shortcut
When used effectively, AI can enhance student learning by helping them generate ideas, refine their thinking and engage in self-assessment. It’s not about replacing human creativity, it’s about augmenting it.
AI has become a valuable asset in competency-based education. The American Association of Colleges of Nursing requires schools to align learning outcomes with specific competencies, a time consuming process that traditionally involved faculty manually mapping course objectives to accreditation standards. With AI, this process has become far more efficient. Faculty can now feed program objectives, course syllabi and accreditation standards into AI-powered tools, which then analyze the content and generate alignment recommendations. This not only saves time but also helps ensure that no key competencies are overlooked.
Beyond alignment, AI also supports faculty in identifying gaps in curriculum coverage. By analyzing vast amounts of course content, AI can highlight areas where certain competencies are underrepresented, allowing educators to make real-time adjustments. This has been particularly impactful in nursing education, where evolving healthcare standards require frequent curriculum updates to stay relevant.
Preparing students for AI-integrated workplaces
Beyond the classroom, AI is rapidly reshaping the healthcare industry, and we’re making sure our students are ready. Kaiser Permanente, one of our primary clinical partners, now has a VP of AI and Emerging Technologies. They are actively integrating AI into clinical practice. If our students are going to work in these environments, they need to understand how AI functions and how to use it responsibly.
One way our faculty prepares students is by teaching them to develop their own AI-driven case simulations. In healthcare education, simulation cases are essential for hands-on learning, yet opportunities to engage with them are often limited. AI expands these opportunities by enabling students to generate diverse patient scenarios, analyze potential diagnoses and test their decision-making skills in a controlled environment. This not only enhances their clinical reasoning but also allows for more personalized and iterative learning experiences. This is a game-changer for applied learning.
Faculty adoption: The challenge and the opportunity
While many faculty have embraced AI, others remain skeptical. It’s understandable—redesigning a course takes time and faculty are already stretched thin. But AI isn’t going away and our role as educators is to ensure students develop the critical thinking skills needed to use these tools effectively.
‘…AI isn’t going away and our role as educators is to ensure students develop the critical thinking skills needed to use these tools effectively.’
Taking a grassroots approach can help faculty integrate AI more effectively. Rather than enforcing a rigid, top-down policy, universities can encourage departments to develop guidelines tailored to their unique disciplines and needs. For example, our MSN program has developed a clear AI policy that outlines when and how students can use AI tools for case studies. This approach ensures ethical AI use while maintaining academic integrity.
Ethical AI use and the evolving role of educators
One of the most pressing concerns surrounding AI is ethics. When students use AI, where does their original thought end and the tool’s output begin?
This is why schools implementing AI should also emphasize AI literacy—students must understand how to use AI transparently and ethically. That means citing AI-generated content where appropriate and being upfront about their usage. Students need to know what is allowed, what isn’t and how to properly disclose their use of AI.
The road ahead: AI as a transformational force
Looking forward, AI’s role in education will only expand. Right now, AI helps students analyze data, generate case studies and assist with curriculum alignment. In the future, it is going to fundamentally change the way we conduct research and teach critical thinking
However, as industry races to the adoption of AI, education approaches AI with caution. Universities focus the integration of AI around topics such as ethics, pedagogy, and long term learning outcomes. Often leaving education in a position to catchup to a fast evolving workplace.
Ultimately, our goal is to equip students with the knowledge and ethical framework to navigate an AI-driven world. We can’t afford to ignore AI or fear it. Instead, we must harness its potential to create more engaging, effective and forward-thinking education.
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Edgar Chabolla is Executive Director for Academic and Instructional Innovation at Samuel Merritt University (SMU). Connect with Edgar on LinkedIn.
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