AI’s Challenges and Strengths in Populations with Limited Health Literacy
Authors: Nancy Evelyn Navarro Ruiz1,2,3, Berenice Martínez Melendres1,2,3, Ana Lilia Fletes Rayas1,2,4, Jaime Briseño Ramírez1,2,3, Emma Alejandra García Olivares1,2,3, Felipe Alexis Avalos Salgado1,2,5, Adrián Enrique Hernández Muñóz1,6, Luis Enrique Colunga Lozano1,2,4, Ana María López Yañez1,2,3, Ramiro Israel Esparza Pérez1, Roberto Miguel Demián Negrete1,2,3
1. JBI Mexican Centre for Evidence-Based Health Care
2. Universidad de Guadalajara
3. Centro Universitario de Tlajomulco
4. Centro Universitario de Ciencias de la Salud
5. Centro Universitario de Ciencias Exactas e Ingenierías
6. Universidad Autónoma de Querétaro
Less than five years ago, the world was primarily focused on responding to a global pandemic, while AI remained largely confined to the realms of science fiction or highly specialised technological environments. Today, AI-powered tools, predictive algorithms, and decision support systems are accessible at the click of a button for entire populations with internet access. For healthcare professionals, it is undeniable that AI is increasingly becoming part of the tools used in clinical and community settings to provide more efficient care, and it is also being used by people seeking healthcare, yet questions hang in the air: Do people with low health literacy have the necessary skills and resources to use AI? Will its use be safe and effective? And most importantly, what can we as health professionals do to guide this transition?
AI tools hold the potential to help people better understand and manage their health. They make scientific information more accessible in plain language, allowing patients and their families to obtain answers, learn about their conditions, and engage more actively in decision-making. This AI potential contributes to democratising knowledge by facilitating the equitable distribution of information and strengthening health literacy across diverse settings. Nevertheless, our experience of working with communities has shown that access to information does not guarantee people’s understanding or informed action. It is also important to remember that people interpret health information through the lens of their cultural background (social determinants), educational experience, and personal beliefs. In this sense, AI is not a complete solution to reducing the gap between scientific evidence and healthcare realities.
In addition to the limitations of AI, it should be noted that these tools still require substantial adaptation to reflect the contextual realities of the diverse populations directly or indirectly contributing data that inform AI systems. However, those populations do not always appear to be adequately represented within the complex decision-making processes that these technologies support. Additionally, AI systems may generate suggestions based on the best available scientific evidence, but that evidence may have been predominantly produced in high-income countries with higher levels of health literacy than the populations of countries where these AI suggestions are being delivered. Consequently, recommendations that are scientifically accurate may not always be meaningful, feasible, or culturally appropriate for populations that face educational, digital, socioeconomic, linguistic, or geographical barriers. Effective implementation requires integrating professional expertise while considering the needs, values, and preferences of patients and communities based on the local context, with ‘people at the centre’.
Working in healthcare and academic settings in Mexico has allowed us to identify that health literacy and digital literacy are deeply disconnected. Let’s first consider digital literacy. AI remains outside the everyday reality of millions of individuals due to structural barriers linked to social determinants. In particular, persistent social inequality, poverty, limited access to the internet or inappropriate use of these services, and disparities in educational opportunities constrain the ability of many communities to benefit from technological advances. Within this context, in 2024, the National Institute of Statistics and Geography (INEGI) reported that 100.2 million people (83.2% of Mexico’s population) were internet users, with its use most prevalent in the 12–34 age group, while 18.6% of the population reported having purchased health-related products online.
Now, let’s consider health literacy. This is defined as individuals’ capacity to access, understand, appraise, and use health information in order to make informed decisions. When these skills are limited, the consequences can be significant. Individuals may experience difficulties adhering to their treatment, delays in seeking care, increased out-of-pocket expenditures, and greater vulnerability to misinformation. Beyond that, another consequence can be that patients substitute professional medical care with information obtained from AI or ‘Dr Google’ due to ease of access, costs, or a lack of professional care.
Throughout our work as healthcare providers, educators, and researchers in Mexico, we have promoted initiatives to increase health literacy and digital literacy among the population. Specifically, at the University of Guadalajara’s Tlajomulco University Center, health sciences students (medicine, nursing, nutrition, dentistry, psychology, and physiotherapy) carry out various community initiatives, visiting neighbourhoods, schools, and centres serving vulnerable populations to provide education on priority health topics – including the responsible and appropriate use of health technologies and AI. Nursing students, in particular, visit local public schools to improve health literacy among children and adolescents. This is important outreach, as while young people are the heaviest internet users, their generations are at risk of becoming disengaged from the healthcare system.
In addition to our centre’s initiatives for the benefit of the municipality of Tlajomulco, last year, the University of Guadalajara carried out the first Health Innovation Congress (CIS), which, for the first time, analysed the scope of AI in healthcare within the state of Jalisco. Additionally, the University of Guadalajara hosted the Innova Forum, a space designed to foster dialogue, collaboration, and the exchange of experiences regarding the challenges and opportunities facing higher education in the digital age. Within this context, it was highlighted that healthcare professionals who are being educated in the era of AI must be guided to recognise the immense potential that these technologies offer, particularly when directed toward vulnerable populations.
Today, we must confront a paradox: those who stand to benefit most from AI-enabled health information and decision support tools are often the same individuals who face the greatest challenges in accessing and using these technologies adequately. Importantly, access to AI tools depends not only on their availability but also on the development of competencies that enable individuals to engage critically with digital environments.
Lessons Learned
Our work to date with populations with limited health literacy and digital literacy has illustrated that the challenge facing future generations of healthcare professionals extends beyond learning how to maximise the capabilities of AI or adapting to the technological transformation of healthcare delivery. Beyond that, there is a risk that the indiscriminate use of AI may erode trust in healthcare systems, and an issue today is simply that the population lacks professional guidance on the use of these technologies. Consequently, healthcare education must cultivate a critical understanding of both the strengths and limitations of AI technologies. Going forward, the uptake of these tools must be culturally appropriate, linguistically accessible, and socially inclusive.
At the same time, healthcare training programs must not neglect the development of professionals’ competencies in the critical appraisal of scientific evidence. There is a growing risk of equating AI-generated information with scientific evidence, despite the fundamental differences between the two. To address this risk, academic curricula should incorporate digital literacy, critical information appraisal, artificial intelligence ethics, and the responsible use of AI as a tool for health education. Only through such an approach can AI become a mechanism for reducing, rather than exacerbating, existing health inequities and barriers to health literacy.
Finally, despite the efforts of various health institutions, such as the Mexican Social Security Institute (IMSS) and the Ministry of Health (SSa), there are currently no national programs focused on educating patients or communities on the use of AI for their health. In the absence of such programs, what can we as health professionals do to guide the transition toward the use of AI, promote people’s education on how to use AI appropriately, and most importantly, ensure that AI does not replace professional medical care? We, as health professionals, can become facilitators, helping the public use these technologies critically, ethically, and safely.
References
Alami, H., Rivard, L., Lehoux, P., Hoffman, S. J., Cadeddu, S. B. M., Savoldelli, M., Samri, M. A., Ag Ahmed, M. A., Fleet, R., & Fortin, J.-P. (2020). Artificial intelligence in health care: Laying the foundation for responsible, sustainable, and inclusive innovation in low- and middle-income countries. Globalization and Health, 16(1), 52. https://doi.org/10.1186/s12992-020-00584-1
Arrighi, E., Ruiz de Castilla, E. M., Peres, F., Mejía, R., Sørensen, K., Gunther, C., Fullam, J., Pelikan, J., & Van den Broucke, S. (2022). Scoping health literacy in Latin America. Global Health Promotion, 29(2), 78–87. https://doi.org/10.1177/17579759211016802
Centro Universitario de Tlajomulco. (n.d.). CUTlajomulco | Centro Universitario de Tlajomulco. Retrieved July 12, 2026, from https://cutlajomulco.udg.mx/
Government of Mexico, Ministry of Health. (n.d.). Secretaría de Salud. Retrieved July 13, 2026, from https://www.gob.mx/salud
Hospital Civil de Guadalajara. (n.d.). 1st Congress on Innovation and Health (CIS). Retrieved July 12, 2026, from https://cis.hcg.gob.mx/
Instituto Nacional de Estadística y Geografía. (2023). Encuesta Nacional sobre Disponibilidad y Uso de Tecnologías de la Información en los Hogares (ENDUTIH) [National Survey on the Availability and Use of Information Technologies in Households]. INEGI. https://www.inegi.org.mx/programas/dutih/2023/
Instituto Nacional de Estadística y Geografía. (2025, May 6). ENDUTIH 2024. INEGI. https://www.inegi.org.mx/contenidos/saladeprensa/boletines/2025/endutih/ENDUTIH_24_RR.pdf
Mexican Social Security Institute. (n.d.). Instituto Mexicano del Seguro Social (IMSS). Retrieved July 13, 2026, from https://www.imss.gob.mx/
Pan American Health Organization. (2024). AI readiness assessment and evaluation for public health. PAHO/World Health Organization. https://www.paho.org/en/documents/artificial-intelligence-public-health-readiness-assessment-toolkit
Sørensen, K., Van den Broucke, S., Fullam, J., Doyle, G., Pelikan, J., Slonska, Z., & Brand, H. (2012). Health literacy and public health: A systematic review and integration of definitions and models. BMC Public Health, 12, 80. https://doi.org/10.1186/1471-2458-12-80
Universidad de Guadalajara. (n.d.). Innova Forum 2026. Retrieved July 12, 2026, from https://innovaforum.udg.mx/
To link to this article - DOI: https://doi.org/10.70253/LFEX9561
Disclaimer
The views expressed in this World EBHC Day Blog, as well as any errors or omissions, are the sole responsibility of the author and do not represent the views of the World EBHC Day Steering Committee, Official Partners or Sponsors; nor does it imply endorsement by the aforementioned parties.
