Technological innovation has advanced exponentially over the past several decades, with AI emerging as a transformative force. The success of OpenAI’s ChatGPT, for instance, has sparked widespread public interest and speculation about AI’s future role. Generative AI, a subset of this technology, uses a combination of deep and machine learning models to generate content, such as words and images, in response to complex prompts.(1) Today, AI is being applied across diverse industries to address a range of challenges, from virtual assistance and facial recognition to medical diagnosis.(2) As the capabilities of AI expand, its influence on society continues to grow rapidly. For example, Chen and Decary(3) highlight how AI is transforming healthcare administration by optimizing workflow processes such as data management, resource allocation, and decision-making, paving the way for more effective and streamlined healthcare management. These advancements not only are reshaping industries but also are creating new opportunities for graduate students in health administration to lead AI-driven innovations in healthcare systems. For instance, AI-powered tools are enabling administrators to predict patient admission rates, optimize staffing schedules, and reduce operational costs, all of which are critical skills for future healthcare leaders.
As AI becomes more integrated into healthcare, graduate programs must adapt their curriculums to ensure students are equipped with the technical and ethical knowledge needed to harness these technologies effectively.
Artificial Intelligence in Healthcare
AI’s transformative impact on industries is particularly evident in healthcare, where it offers innovative solutions for both medical practice and education. AI is revolutionizing healthcare as physicians increasingly integrate this technology into their workflows.(4) Dave and Patel(5) examine the status and challenges of AI in medicine, emphasizing its applications in diagnostic support, personalized medicine, and drug discovery, while addressing critical ethical considerations. For example, AI algorithms are being used to analyze medical imaging with greater accuracy than human radiologists can achieve, reducing diagnostic errors and improving patient outcomes.( )In medical education, AI-powered tools are enhancing training programs in fields such as radiology and ophthalmology by providing students with realistic, adaptive simulations that respond to their actions in real time.(6,7) These simulations allow students to practice complex procedures in a risk-free environment, bridging the gap between theory and practice.
Beyond training, AI is proving invaluable in public health research, as AI algorithms analyze EHRs to identify health trends, predict disease outbreaks, and inform preventative strategies.(8) For instance, during the COVID-19 pandemic, AI models were used to predict infection hotspots and allocate resources efficiently. Additionally, machine learning and deep learning technology show promise in enhancing accuracy in disease diagnosis and prediction.(9) AI’s role in the healthcare industry will continue to grow and shape the future of healthcare, as highlighted by Charow et al.,(10) who emphasize the urgent need for AI education programs to prepare healthcare professionals for overseeing AI applications in patient care. Graduate health administration programs also are evolving to include AI-driven curriculum components, such as data analytics and AI ethics, to equip students with the skills needed to navigate this rapidly changing landscape. For example, courses on AI applications in healthcare management are becoming essential, teaching students how to leverage AI for operational efficiency and strategic decision-making.
AI in Education
AI is increasingly being leveraged to address educational challenges, offering innovative solutions to enhance learning experiences. AI-driven chatbots, for instance, are being used as personal tutors to assist students by identifying knowledge gaps.(11) In addition, AI chatbots provide real-time feedback and also automate routine tasks, such as creating flashcards and study guides, thereby improving the overall quality of education. Educators believe that integrating AI chatbots into classrooms will allow them to focus more on instructional planning and fostering student engagement.(12) For example, AI-powered platforms such as ChatGPT are being used to create personalized learning plans for students, adapting to their individual needs and pacing. Although some instructors express concerns about the potential impact on students’ problem-solving and critical-thinking abilities, studies have shown that students using AI chatbots demonstrate greater self-efficacy and better learning attitudes and motivation compared with those without AI assistance.(13,14)
As these benefits become more evident, the adoption of AI in education is expected to grow significantly. Chen et al., further underscore this trend in their review of AI in education, highlighting how AI applications have enhanced administrative functions, improved teaching quality, and personalized learning materials for students.(15) For graduate health administration students, this means access to AI-powered simulations and case studies that prepare them for real-world challenges, such as optimizing hospital workflows and managing patient data. For instance, students can use AI-driven tools to simulate hospital operations, predicting patient flow and identifying bottlenecks in real time.(16,17) These hands-on experiences are critical for developing the skills needed to lead AI-driven healthcare systems in the future.
AI in Public Health Education
The integration of AI also is gaining momentum in public health education, with academic institutions leading the way. For example, the University of Michigan offered several courses for the Spring 2024 semester that cover AI enhancement of patient–provider interactions, the creation of AI-driven tools for mental health, and utilizing AI for targeted health campaigns.(18) Similarly, Harvard and Stanford have introduced lifelong learning courses focused on AI and healthcare.(19,20) Additionally, the University of Florida has launched an undergraduate certificate program in AI for Public Health and Healthcare.(21 )These initiatives highlight how public health education is evolving to equip future professionals with the AI competencies needed as the technology becomes more integrated into the field. Gray et al., emphasize the importance of AI education in medical training, particularly in areas such as ethics, machine learning, and human–machine interactions, while noting the lack of benchmarks or competencies for healthcare professionals working with AI.(22)
Graduate health administration programs also are addressing these gaps by incorporating interdisciplinary learning opportunities, where students collaborate with data scientists and clinicians to develop AI solutions for healthcare challenges. For example, students might work on projects involving predictive analytics to improve population health outcomes or develop AI-driven tools for managing chronic diseases.(23) These experiences not only enhance technical skills but also foster collaboration and innovation, preparing students for leadership roles in AI-driven healthcare environments.
AI and the Future of Public Health Education
As AI technology continues to advance, its relevance in public health will continue to grow. In the coming years, AI tools are expected to play a central role in public health research and practice. Educational programs already are taking proactive steps to prepare students by incorporating AI training into their curriculums. Universities are developing new courses and programs that explore the intersection of AI and public health, ensuring that students are equipped to harness these tools effectively. For instance, courses on AI ethics and governance are becoming essential, teaching students how to address challenges such as bias in algorithms and patient privacy concerns.(24)
As AI training becomes more accessible, it is likely that an increasing number of institutions will follow suit, further embedding AI into the fabric of public health education and practice. Benhayoun and Lang highlight the need for higher education to address the growing demand for AI skills, emphasizing the importance of interdisciplinary skills and sectoral knowledge to prepare graduates for the AI labor market.(25) For graduate health administration students, this means emerging career opportunities in roles such as AI healthcare strategist, health data analyst, and AI implementation specialist. These roles will require a blend of healthcare knowledge and technical expertise, as well as the ability to lead AI adoption initiatives and address ethical and regulatory challenges. For example, AI healthcare strategists might work with hospitals to implement AI-powered tools to optimize resource allocation, while health data analysts could use AI to identify trends in patient outcomes and inform policy decisions.(26)
By preparing students for these opportunities, graduate programs are ensuring that the next generation of health administrators is ready to shape the future of AI-driven healthcare. Furthermore, as AI continues to evolve, lifelong learning will become increasingly important, with professionals needing to stay updated and continuously refine their skills to remain competitive in their evolving field.
Conclusion
The rapid development of AI is reshaping the future of healthcare, education, and public health. From improving administrative efficiency to enhancing diagnostic precision and medical training, AI offers numerous benefits that can revolutionize healthcare leadership. As academic institutions integrate AI into their programs, future healthcare professionals must develop both technical expertise and ethical awareness to navigate its challenges. Ensuring responsible implementation will require balancing innovation with considerations such as data privacy, algorithmic fairness, and workforce adaptation. By embracing AI thoughtfully, healthcare leaders can drive meaning improvements in patient care, operational management, and public health strategies.
References
Lim WM, Gunasekara A, Pallant JL, Pallant JI, Pechenkina E. Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. ScienceDirect. 2023;21(2). https://doi.org/10.1016/j.ijme.2023.100790
Wang X, He X, Wei J, Liu J, Li Y, Liu X. Application of artificial intelligence to the public health education. Front Public Health. 2023;10. https://doi.org/10.3389/fpubh.2022.1087174
Chen M, Decary M. Artificial intelligence in healthcare: an essential guide for health leaders. Healthcare Management Forum. 2019;33(1):10-18. https://doi.org/10.1177/0840470419873123
Rahman A, Ernest J, Victoros E, Davis R, Shanjana Y, Islam R. Impact of artificial intelligence (AI) technology in healthcare sector: a critical evaluation of both sides of the coin. Clin Pathol. 2024;17. Accessed February 27, 2025. doi: 10.1177/2632010X241226887
Dave M, Patel N. Artificial intelligence in healthcare and education. Br Dent J. 2023;234:761-764. https://doi.org/10.1038/s41415-023-5845-2
Ellis L. Artificial intelligence for precision education in radiology—experiences in radiology teaching from a UK foundation doctor. Br J Radiol. 2019;92(1104):20190779. https://doi.org/10.1259/bjr.20190779
Valikodath NG, Cole E, Ting DSW, et al. Impact of artificial intelligence on medical education in ophthalmology. Transl Vis Sci Technol. 2021;10(7):14. https://doi.org/10.1167/tvst.10.7.14
Olawade DB, Wada OJ, David-Olawade AC, Kunonga E, Abaire O, Ling J. Using artificial intelligence to improve public health: a narrative review. Front Public Health. 2023;11. https://doi.org/10.3389/fpubh.2023.1196397
Ghaffar Nia N, Kaplanoglu E, Nasab A. Evaluation of artificial intelligence techniques in disease diagnosis and prediction. Discov Artif Intell. 2023;3(1):5. https://doi.org/10.1007/s44163-023-00049-5
Charow R, Jeyakumar T, Younus S, et al. Artificial intelligence education programs for health care professionals: scoping review. JMIR Medical Education. 2021;7(4):e31043. https://doi.org/10.2196/31043
Teng M, Singla R, Yau O, et al. Health care students’ perspectives on artificial intelligence: countrywide survey in Canada. JMIR Medical Education. 2022;8(1):e33390. https://doi.org/10.2196/33390
Labadze L, Grigolia M, Machaidze L. Role of AI chatbots in education: systematic literature review. International Journal of Educational Technology in Higher Education. 2023;20(1):56. https://doi.org/10.1186/s41239-023-00426-1
Seo K, Tang J, Roll I, Fels S, Yoon D. The impact of artificial intelligence on learner–instructor interaction in online learning. International Journal of Educational Technology in Higher Education. 2021;18(1):54. https://doi.org/10.1186/s41239-021-00292-9
Lee YF, Hwang GJ, Chen PY. Impacts of an AI-based chatbot on college students’ after-class review, academic performance, self-efficacy, learning attitude, and motivation. Education Tech Research Dev. 2022;70(5):1843-1865. https://doi.org/10.1007/s11423-022-10142-8
Chen L, Chen P, Lin Z. Artificial intelligence in education: a review. IEEE Access. 2020;8:75264-75278. https://doi.org/10.1109/ACCESS.2020.2988510
Sallam M, Salim N, Barakat M, Al-Tammemi A. ChatGPT applications in medical, dental, pharmacy, and public health education: a descriptive study highlighting the advantages and limitations. Narra J. 2023;3(1):103. https://doi.org/10.52225/narra.v3i1.103
Park SH, Do KH, Kim S, Park JH, Lim YS. What should medical students know about artificial intelligence in medicine? JEEHP. 2019;16. https://doi.org/10.3352/jeehp.2019.16.18
University of Michigan. Students harness AI for public health with new course. Accessed February 27, 2025. https://sph.umich.edu/news/2023posts/students-harness-ai-for-public-health-with-new-course.html .
Harvard University. Innovation with AI in health care. Harvard University. May 24, 2023. https://pll.harvard.edu/course/innovation-ai-health-care-0 . Accessed February 27, 2025.
Stanford University. Artificial intelligence in healthcare. August 6, 2020. https://online.stanford.edu/programs/artificial-intelligence-healthcare . Accessed February 27, 2025.
University of Florida. Artificial Intelligence in Public Health and Healthcare certificate. https://catalog.ufl.edu/UGRD/colleges-schools/UGPBH/PBH_UCT02/ . Accessed February 27, 2025.
Gray K, Slavotinek J, Dimaguila GL, Choo D. Artificial intelligence education for the health workforce: expert survey of approaches and needs. JMIR Medical Education. 2022;8(2):e35223. https://doi.org/10.2196/35223
Javaid M, Haleem A, Khan IH, Vaishya R, Vaish A. Extending capabilities of artificial intelligence for decision-making and healthcare education. Apollo Medicine. 2020;17(1):53-59. https://doi.org/10.4103/am.am_10_20
Filgueiras F. Artificial intelligence and education governance. Education, Citizenship and Social Justice. 2024;19:349-361. https://doi.org/10.1177/17461979231160674
Benhayoun L, Lang D. Does higher education properly prepare graduates for the growing artificial intelligence market? Gaps’ identification using text mining. Human Systems Management. 2021;40:639-651. https://doi.org/10.3233/HSM-211179
Lu S, Burton S. Man vs Robots? Future challenges and opportunities within artificial intelligence (AI) health care education model. November 7, 2017. https://doi.org/10.13140/RG.2.2.33500.85129