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DOI: https://doi.org/10.56712/latam.v7i1.53=
39
Mexican youth=
on
AI: Their visions of tomorrow
Jóvenes mexicanos ante la IA: =
sus visiones
del mañana
Á=
ngel
Téllez Tula[1]
https://orcid.org/000=
0-0002-7925-9271
Beneméri=
ta
Universidad Autónoma de Puebla
Puebla –
México
Tutaleni
Asino
tasino@andrew.c=
mu.edu
https://orcid.org/0000-0002-9667-8603
Carnegie Mellon
University
Pittsburgh,
Pensilvania – Estados Unidos
Benjam&i=
acute;n
Gutiérrez Gutiérrez
benjamin.gutierrez@co=
rreo.buap.mx
https://orcid.o=
rg/0000-0003-2716-9108
Beneméri=
ta
Universidad Autónoma de Puebla
Puebla –
México
Norma El=
ena
Mendoza Zaragoza
https://orcid.org/000=
9-0009-9214-5082
Universidad de
Colima
Colima –
México
Laura
Herrera Corona
laurahc32@gmail=
.com
https://orcid.org/000=
9-0002-8572-0383
Universidad
Anáhuac Campus Querétaro
Querétaro
– México
Artículo recibido: 13 de octubre=
de
2025. Aceptado para publicación: 16 de febrero de 2026.
Conflictos de Interés: Ninguno que declarar.
Abstract
Artificial Intelligence (AI) has become increasingly embedded in the
daily lives of young people, yet its educational, social, and ethical
implications remain insufficiently explored in secondary school contexts in
Mexico. This study examines the perceptions, levels of familiarity, frequen=
cy
of use, and educational expectations regarding AI among Generation Z studen=
ts
enrolled in technical junior high schools. A mixed-methods exploratory desi=
gn
with quantitative dominance was employed. Data were collected through an on=
line
questionnaire administered to 560 students aged 11 to 15, combining
closed-ended items with open-ended questions. Quantitative data were analyz=
ed
descriptively to identify general trends, while qualitative responses were
examined through thematic analysis to capture interpretative categories rel=
ated
to students’ views on AI. The findings reveal widespread exposure to =
AI
technologies, accompanied by predominantly functional rather than conceptual
understanding. Students expressed neutral or ambivalent perceptions regardi=
ng
AI’s impact on Mexico’s future and employment, alongside freque=
nt,
often unreflective, use of AI-based applications. Despite these uncertainti=
es,
a majority demonstrated openness toward AI-related educational opportunitie=
s and
identified education as the sector most likely to benefit from AI
implementation. Qualitative results further revealed a dual discourse that
simultaneously recognizes AI’s usefulness and expresses ethical conce=
rns
related to dependency, creativity, and academic integrity. The study highli=
ghts
the need for educational strategies that move beyond incidental interaction
with AI toward structured, critical, and ethically grounded AI literacy. Th=
ese
findings contribute empirical evidence to ongoing debates on the responsible
integration of artificial intelligence in secondary education within the
Mexican context.
Keywords: artificial intelligence, education, Mexico,
generation Z, student perceptions
Resumen
La inteligencia artificial (IA) se ha integrado de manera creciente=
en
la vida cotidiana de las y los jóvenes; sin embargo, sus implicacion=
es
educativas, sociales y éticas continúan siendo poco explorada=
s en
el nivel de educación secundaria en México. El presente estud=
io
analiza las percepciones, el nivel de familiaridad, la frecuencia de uso y =
las
expectativas educativas relacionadas con la IA en estudiantes de la
Generación Z inscritos en secundarias técnicas. Se emple&oacu=
te;
un diseño exploratorio de métodos mixtos con predominio
cuantitativo. La información se recolectó mediante un
cuestionario en línea aplicado a 560 estudiantes de entre 11 y 15
años, que incluyó reactivos cerrados y preguntas abiertas. Los
datos cuantitativos se analizaron de forma descriptiva, mientras que las re=
spuestas
cualitativas se examinaron mediante análisis temático para
identificar categorías interpretativas sobre las percepciones
estudiantiles. Los resultados muestran una alta exposición a
tecnologías basadas en IA, acompañada de una comprensió=
;n
principalmente funcional más que conceptual. Las y los estudiantes
manifestaron percepciones mayoritariamente neutrales o ambivalentes respect=
o al
impacto futuro de la IA en México y en el empleo, así como un=
uso
frecuente —en muchos casos poco reflexivo— de aplicaciones basa=
das
en IA. A pesar de ello, se observa una amplia disposición hacia la
formación en IA y una percepción de la educación como =
el
ámbito con mayor potencial de beneficio. El análisis cualitat=
ivo
evidencia, además, un discurso dual que reconoce la utilidad de la I=
A,
pero también expresa preocupaciones éticas relacionadas con la
dependencia tecnológica, la creatividad y la integridad
académica. El estudio subraya la necesidad de diseñar estrate=
gias
educativas que promuevan una alfabetización en IA crítica,
ética y contextualizada, más allá del uso incidental d=
e la
tecnología, aportando evidencia empírica relevante para el de=
bate
sobre la integración responsable de la inteligencia artificial en la
educación secundaria en México.
Palabras clave: inteligencia artificial, educación, estudiantes de secundar=
ia,
percepción estudiantil, generación Z
<= o:p>
<= o:p>
Todo el contenido de LATAM Revista Latinoamerica=
na
de Ciencias Sociales y Humanidades, publicado en este sitio está
disponibles bajo Licencia Creative Commons.
Cómo
citar: Téllez Tula,
Ángel, Asino, T., Gutiérrez Gutiérrez, B., Mendoza
Zaragoza, N. E., & Herrera Corona, L. (2026). Mexican youth on AI. L=
ATAM
Revista Latinoamericana de Ciencias Sociales y Humanidades 7 (1), 1235 R=
11; 1251.
https://doi.org/10.56712/latam.v7i1.5339
INTRODUCTION
Context and Rationale
At present, a technological transformation =
is
underway, characterized by the progressive integration of artificial
intelligence (AI) into human relationships, social behaviors, and instituti=
onal
structures. This process has been interpreted as a new stage of social
development, following the agricultural, industrial, informational, and
connectivity waves described by Toffler, in which AI assumes a central role=
in
the reorganization of social, educational, and productive life (Montgomery,
2016). Within this context, it becomes necessary to understand the phenomen=
on
of artificial intelligence and to analyze its implications for everyday lif=
e.
The study of AI acquires particular relevan=
ce
in national contexts such as Mexico, where its use has expanded progressive=
ly
within universities and organizations, generating transformations in
educational and labor processes. In this regard, understanding the percepti=
ons
of younger generations is essential, not only because they will interact mo=
st intensively
with these technologies, but also because they will actively participate in
shaping their future uses. The literature indicates that AI directly influe=
nces
how work, education, and learning processes are conceived (May, 2024; Abbas=
s,
2021).
From a generational perspective, various
studies suggest that each cohort maintains a differentiated relationship wi=
th
technology, shaped by the social and technological conditions of its
developmental context. In particular, Generation Z is characterized by havi=
ng
grown up in highly digitalized environments, with continuous access to
platforms and devices that incorporate artificial intelligence into everyday
life (Chan & Lee, 2023). Unlike previous generations, this group has not
experienced educational or social settings devoid of technologies such as
virtual assistants, recommendation systems, or automated content generation
tools.
Technical secondary education represents a
pertinent context for analyzing these perceptions, as it combines general
academic training with technology-oriented content aimed at developing
practical skills. This type of institution prepares students both for the
continuation of their studies and for their future entry into the labor mar=
ket,
making it especially relevant to explore how they interpret the use of
artificial intelligence and its relationship with learning processes.
METHODOLOGY
Research Approach
This study employed a mixed-methods explora=
tory
design with a quantitative-dominant approach, complemented by qualitative
thematic analysis. The quantitative component was used to describe
students’ levels of familiarity, perceptions, and attitudes toward
artificial intelligence through closed-ended survey items, while the
qualitative component provided interpretive depth through the analysis of
open-ended responses.
The design is exploratory in nature, as it
seeks to identify patterns and tendencies in students’ perceptions of
artificial intelligence within an educational context where empirical evide=
nce
remains limited. Quantitative data were analyzed descriptively to establish
general trends, whereas qualitative data were examined using thematic analy=
sis
to capture recurring meanings and interpretative categories emerging from
students’ responses. The integration of both components allowed for
triangulation between numerical trends and students’ subjective
interpretations, strengthening the internal coherence of the findings.
Study Design
This study followed a mixed-methods explora=
tory
design with quantitative dominance. Closed-ended survey items were used to
describe overall trends in students’ familiarity, perceptions, and
attitudes toward AI, while open-ended responses were analyzed through thema=
tic
analysis to provide interpretive depth. The integration of both components
supported a triangulated interpretation of the results.
Participants
The research was carried out in three public
technical secondary schools in the state of Puebla, Mexico: Technical Secon=
dary
School 61 and Technical Secondary School 125, located in the municipality of
San Martín Texmelucan, and Technical Secondary School 23, located in=
San
Pedro Cholula. The sample consisted of 560 students aged between 11 and 15
years, enrolled in public technical secondary education.
Inclusion criterio: Students enroll=
ed
in secondary education, aged between 11 and 15 years, and attending exclusi=
vely
public technical secondary schools were included.
Exclusion criterio: Students from
private schools, from other educational systems, as well as from general or
teacher-training (non-technical) secondary schools were excluded.
Sampling method: A non-probabili=
stic
sampling method was used, based on the researcher’s judgment.
Data Collection Instruments
An online questionnaire developed using Goo=
gle
Forms was employed. It consisted of nine items, seven of which were
closed-ended questions and two open-ended questions. The design of the
instrument was based on a prior review of the literature on youth perceptio=
ns
and the educational use of artificial intelligence (Chan & Lee, 2023; F=
averio
& Tyson, 2023).
To ensure content validity, the instrument =
was
reviewed by three experts in educational technology and research methodolog=
y,
whose observations were incorporated to improve the clarity and relevance of
the items. Subsequently, a pilot test was conducted with 30 students, which
allowed for adjustments to the questionnaire prior to its final administrat=
ion.
Procedure
The instrument was administered asynchronou=
sly.
The questionnaire was distributed through the corresponding school supervis=
ion
authorities. The data collection period lasted approximately one month, bet=
ween
June and July 2025.
Data Analysis
Data analysis was based on a triangulation
process that integrated the empirical data obtained, the theoretical and
experiential knowledge of specialized researchers, and the interpretation of
the principal investigator, with the aim of strengthening the validity and
reliability of the results (Hernández, Fernández, & Bapti=
sta,
2006).
Responses to closed-ended questions were
analyzed using descriptive statistics (frequencies and percentages) for
exclusively contextual purposes. Open-ended responses were examined through
thematic analysis, which made it possible to identify emergent categories b=
ased
on the opinions expressed by the students. The interpretation of qualitative
findings was conducted consensually among the researchers through discussion
and comparison of the identified categories, as a strategy to enhance
interpretive validity.
Ethical Considerations
This research was conducted in accordance w=
ith
ethical standards for studies involving minors in educational settings. Pri=
or
to data collection, formal authorization was obtained from the participating
schools. Ethical approval for the study was granted by the school superviso=
r,
who acted as the institutional authority responsible for overseeing the
research process. Given the non-interventional nature of the study and its
alignment with regular educational activities, review by a formal ethics co=
mmittee
was not required.
Informed consent was obtained from parents =
or
legal guardians of all participating students, and assent was obtained from=
the
students themselves. Participation was voluntary, and participants were
informed that they could decline or withdraw at any stage without any acade=
mic
or personal consequences.
No personally identifiable information was
collected. All data were gathered anonymously and used exclusively for acad=
emic
and research purposes. The study respected the principles of confidentialit=
y,
autonomy, and protection of participants’ rights and well-being
throughout the research process.
DEVELOPMENT
The specialized literature defines artifici=
al
intelligence as the ability of computational systems to perform complex
activities that have traditionally required human cognitive processes, such=
as
reasoning, decision-making, and content generation (May, 2024). From a
complementary perspective, Abbass (2021) argues that AI can be understood b=
oth
as the automation of cognition and as a social and cognitive phenomenon that
enables machines to integrate into human contexts through the exchange of
information.
In recent years, generative artificial
intelligence has gained prominence due to its increasing use in educational=
and
communicative applications, relying on deep learning models and neural netw=
orks
capable of processing natural language and generating diverse forms of cont=
ent
(Çayak, 2024). Within the educational field, several international
studies have examined university students’ perceptions of AI use,
highlighting both its potential as an academic support tool and the challen=
ges
associated with its institutional and pedagogical integration (Ka, 2024;
Christ-Brendemühl, 2024; Amani & Maslihatul Bisriyah, 2025).
However, research focused on younger
populations remains limited. Some studies indicate that Generation Z studen=
ts
maintain a daily relationship with technologies based on artificial
intelligence, although they do not always possess a deep conceptual
understanding of how these systems function or of their long-term implicati=
ons
(Chan & Lee, 2023). In the Mexican context, this gap is even more
pronounced, as most existing studies focus on higher education levels or on
contexts other than secondary education.
This landscape underscores the need to gene=
rate
empirical research that analyzes the perceptions of technical secondary sch=
ool
students in Mexico regarding the use of artificial intelligence, in order to
provide relevant information for examining its integration into educational
processes.
The expansion of artificial intelligence us=
e in
educational and digital environments has generated growing interest in
understanding how students interpret its presence and its impact on learning
processes. Although the international literature has documented university
students’ perceptions of AI and its academic applications, empirical
evidence focused on younger populations remains scarce, particularly at the
secondary education level and in contexts such as Mexico (Ka, 2024; Christ-=
Brendemühl,
2024; Amani & Maslihatul Bisriyah, 2025).
Research problem
Several studies indicate that Generation Z
maintains a daily relationship with technologies based on artificial
intelligence; however, this familiarity is not always accompanied by a deep=
understanding
of how these technologies function or of their educational and social
implications (Chan & Lee, 2023). In the educational context, this situa=
tion
raises questions regarding how students perceive the use of AI, its influen=
ce
on learning, and its potential impact on future scenarios. The absence of
systematic research in technical secondary education in Mexico limits the
understanding of these perceptions and hinders the development of
evidence-based educational strategies.
In this sense, the research problem focuses=
on
the need to analyze how technical secondary school students perceive the us=
e of
artificial intelligence, considering their everyday experience with these
technologies and their relationship with learning processes, within an educ=
ational
context where AI is becoming increasingly visible.
Objectives and Research Questions
The general objective of the study is to
investigate students’ perceptions and opinions regarding the use of
artificial intelligence in future scenarios.
Based on this general objective, the follow=
ing
main research question is proposed:
●●●● Graphic 1 How familiar are you with the concept of
artificial intelligence? Source: authors’
elaboration. The data reveals a spectrum of familiarity =
with
AI among participants: 41% were moderately familiar, 30% slightly familiar,=
and
18% quite familiar. Only a small minority (7%) reported being very familiar=
. Perception of AI's Impact on Mexico's Futur=
e To examine students’ perceptions of t=
he
broader societal implications of artificial intelligence, participants were
asked to evaluate its potential impact on Mexico’s future. The follow=
ing
figure summarizes their responses, reflecting how students position artific=
ial
intelligence in relation to national development. Graphic 2 Do you consider the development of artifici=
al
intelligence to be positive, negative, ¿or neutral for the
Source: authors’
elaboration. When asked about the impact of AI on Mexico=
's
future, more than half of the respondents (54%) expressed a neutral stance,
while 25% viewed it positively, 7% negatively, and 14% were uncertain. Frequency of AI Use in Daily Life To explore the extent to which artificial
intelligence is integrated into students’ everyday routines, particip=
ants
were asked about the frequency with which they use applications or devices =
that
incorporate AI technologies. The following figure presents the distribution=
of
responses related to daily AI use. Graphic 3 How often do you use applications or devices
that incorporate Artificial Intelligence in your daily life (e.g., voice
assistants, personalized recommendation systems, facial and image recogniti=
on)?
Source: authors’
elaboration. A significant portion of participants (32%)
reported using AI-powered applications or devices several times a week, with
another 14% using them several times a month. Only 4% claimed to never use =
AI. Perceived Impact on Employment To assess students’ expectations
regarding the relationship between artificial intelligence and employment,
participants were asked to evaluate whether AI would create more jobs than =
it
eliminates in Mexico’s future. The following figure summarizes their
responses. Graphic 4 Source: authors’
elaboration. The data regarding AI's impact on employment
reveals a landscape characterized by significant uncertainty. When asked wh=
ether
AI will create more jobs than it eliminates in Mexico's future, nearly half=
of
the participants (49%) expressed uncertainty. A substantial proportion, 33%,
believed that AI would not result in a net creation of jobs, while a notably
smaller segment of only 18% held an optimistic outlook. Openness to AI Education To examine students’ openness toward
formal education in artificial intelligence, participants were asked whether
they would be interested in taking AI-related courses or workshops if offer=
ed
at their schools. The following figure presents their responses. Graphic 5 Would you be interested in taking courses or
workshops on Artificial Intelligence if they were available at your school?=
Source: authors’
elaboration. A strong majority of students (59%) express=
ed
interest in taking AI courses or workshops if offered at their schools, whi=
le
16% were not interested. This high level of receptivity is characteristic of
Gen Z, identified as the most AI-receptive generation in Mexico (19°
Estudio sobre los hábitos de usuarios de internet en México,
2023). Area of Perceived Greatest Positive Impact<=
o:p> To identify the sectors in which students
perceive the greatest potential benefits of artificial intelligence,
participants were asked to indicate the area they believe would experience =
the
most significant positive impact of AI in Mexico. The following figure
summarizes their responses. Graphic 6 Which area do you think will have the most
significant positive impact in terms of Artificial Intelligence in Mexico?<=
o:p> Source: authors’
elaboration. When asked which area would benefit most fr=
om
AI in Mexico, 37% of participants identified education, followed by health
(19%) and security (13%). Qualitative Findings: Students’ Perce=
ptions
of Artificial Intelligence The qualitative analysis of the open-ended
responses provides interpretative depth to the quantitative findings by
revealing the semantic frameworks through which students conceptualize
artificial intelligence. Responses to the prompt requesting a three-word
description of AI were examined through thematic analysis, resulting in six
emergent categories: positive valuation, ambivalence, concern or distrust, =
lack
of knowledge, transformative vision, and technical or conceptual references=
. A substantial number of participants expres=
sed
positive valuations of artificial intelligence, using descriptors such as
“useful,” “efficient,” “fast,” and
“helpful,” as well as functional expressions related to problem
solving and academic support. These perceptions are consistent with the
Technology Acceptance Model, which posits that perceived usefulness and eas=
e of
use are central determinants of favorable attitudes toward technology adopt=
ion
(Davis, 1989). Recent empirical evidence suggests that these dimensions
continue to shape young people’s acceptance of AI-based systems in
contemporary digital environments (Maslej et al., 2024). Ambivalence emerged as a dominant qualitati=
ve
pattern, reflected in responses combining positive and negative evaluations,
such as “good and bad” or “helpful but dangerous.” =
This
dual stance aligns with findings reported by Faverio and Tyson (2023), who =
note
that young people often engage with AI through mixed cognitive frameworks t=
hat
simultaneously acknowledge its benefits and express concern about its broad=
er
social and ethical implications. Such ambivalence suggests an emerging crit=
ical
awareness rather than unconditional acceptance, indicating that students
perceive AI as context-dependent and shaped by its modes of application and
regulation. Expressions of concern or distrust constitu=
ted
another salient category. Participants associated AI with risks such as job
displacement, dependency, deception, and dehumanization. These concerns
resonate with ongoing ethical debates regarding automation and its potential
impact on labor, identity, and well-being (West, 2019; Selwyn, 2020). In
particular, apprehensions related to excessive reliance on AI and its effec=
ts
on mental health and social interaction are consistent with warnings raised=
in
psychological and educational literature addressing adolescents’
vulnerability to technological overuse (American Psychological Association,
2023). A smaller yet relevant group of responses
reflected uncertainty or lack of knowledge, including neutral or indetermin=
ate
expressions. This absence of a clear evaluative stance may be linked to une=
ven
levels of digital literacy and limited opportunities for structured reflect=
ion
on AI within formal education, a gap widely documented in research on
educational responses to emerging technologies (Williamson & Eynon, 202=
0). In contrast, some students articulated a
transformative or future-oriented vision of artificial intelligence, employ=
ing
terms such as “progress,” “future,” and “inno=
vation.”
These responses frame AI as a driver of societal change and align with broa=
der
narratives that position artificial intelligence as a defining force in
contemporary technological evolution (Luckin, 2018; Luckin et al., 2016). F=
inally,
a limited number of participants demonstrated familiarity with technical
terminology, referencing concepts such as machine learning or artificial
intelligence classifications, suggesting prior exposure to formal or inform=
al
AI-related knowledge. Taken together, these qualitative findings
reveal that students’ perceptions of artificial intelligence are neit=
her
homogeneous nor simplistic. Instead, they reflect a complex interplay of
optimism, caution, limited understanding, and emerging critical awareness. =
This
semantic diversity reinforces the need for educational approaches that addr=
ess
not only functional engagement with AI, but also ethical reflection, concep=
tual
understanding, and critical literacy, as emphasized in current research on
artificial intelligence in education (Selwyn, 2020; Holmes et al., 2021). DISCUSSION The findings of this study reveal a complex=
and
nuanced relationship between Generation Z students and artificial intellige=
nce,
characterized by frequent exposure, functional engagement, and persistent
uncertainty regarding its broader social, educational, and national
implications. Although AI is widely present in students’ everyday dig=
ital
environments, their understanding remains predominantly practical rather th=
an
conceptual, as students interact regularly with AI-based systems without fu=
lly
recognizing how these technologies operate or how they may influence social,
economic, and institutional structures. This limited conceptual understandi=
ng
helps explain the predominantly neutral perceptions observed regarding
AI’s future impact in Mexico. Rather than reflecting indifference, su=
ch
neutrality appears to stem from insufficient access to contextualized
information that would allow students to evaluate artificial intelligence a=
s a
socio-technical phenomenon with concrete societal consequences. Similar
patterns have been documented in broader populations, where individuals
simultaneously acknowledge AI’s potential benefits and express concer=
n or
uncertainty about its risks and long-term implications (Faverio & Tyson,
2023). In the Mexican educational context, these findings suggest the absen=
ce
of structured curricular or institutional spaces that promote critical
discussion of AI beyond its instrumental or functional use. The frequency of AI use reported by students
highlights the extent to which artificial intelligence has become embedded =
in
daily routines. Rather than being perceived as a distinct technological too=
l,
AI appears to function as an infrastructural component of digital environme=
nts,
shaping access to information, personalization processes, and automated
interactions. This normalization of AI use may contribute to its perceived
invisibility, reducing opportunities for critical reflection on its role and
consequences. Prior research has noted that such background integration can
limit users’ awareness of algorithmic influence, particularly among
younger populations who have grown up in digitally mediated environments
(Luckin et al., 2016; Robinson, 2025). Uncertainty is particularly salient in
students’ perceptions of AI’s impact on employment. The lack of
strongly polarized positions suggests that students are navigating competing
narratives that emphasize both economic opportunity and labor displacement.
This ambivalence reflects broader societal debates surrounding automation a=
nd
the future of work, as well as limited exposure to structured discussions a=
bout
how AI may reshape labor markets and skill demands. Similar concerns have b=
een
documented among Mexican workers, who recognize AI’s productive poten=
tial
while expressing apprehension about job security (Valladolid & Valladol=
id,
2024). Among younger students, such uncertainty underscores the need for
educational interventions that explicitly address the relationship between =
AI,
work, and future professional trajectories. At the same time, students’ openness
toward receiving formal education or training in artificial intelligence
indicates a strong expectation that schools should play an active role in
preparing them for technologically mediated futures. This disposition aligns
with characterizations of Generation Z as a digitally receptive cohort.
However, the presence of a resistant minority reveals ethical and pedagogic=
al
tensions that merit attention. Qualitative responses suggest concerns relat=
ed
to technological dependence, the potential erosion of creativity, and
challenges to academic integrity. These perceptions resonate with critical
perspectives in educational research that caution against uncritical adopti=
on
of AI in learning environments (Selwyn, 2020). The qualitative findings further reinforce =
the
complexity of students’ attitudes toward artificial intelligence. The
coexistence of positive descriptors such as “useful” and
“efficient” alongside cautionary or negative terms reflects a d=
ual
evaluative framework. This pattern aligns with the Technology Acceptance Mo=
del,
which posits that perceived usefulness supports acceptance, while perceived
risks moderate enthusiasm for technology adoption (Davis, 1989).
Students’ ambivalence suggests an emerging critical awareness rather =
than
unconditional acceptance, indicating that AI is viewed as beneficial under
certain conditions but potentially problematic if misused or insufficiently
regulated, a tendency also highlighted by Faverio & Tyson (2023). Students’ identification of education=
as
the sector most likely to benefit from artificial intelligence highlights t=
he
pedagogical framing of AI within this population. Rather than associating AI
primarily with economic growth or security, students perceive it as a tool
capable of supporting teaching and learning processes. This perception alig=
ns
with policy-level discourses that emphasize AI’s potential to enhance
educational practices and optimize instructional work (“AI Will Be at=
the
Service of Education and People in Mexico,” 2025). The convergence
between student expectations and institutional narratives positions educati=
on
as a strategic entry point for the responsible and socially grounded
integration of artificial intelligence. Finally, perceptions of academic preparedne=
ss
reveal a gap between the rapid evolution of artificial intelligence
technologies and the responsiveness of educational systems. Students freque=
ntly
reported limited curricular integration and insufficient institutional guid=
ance
regarding AI use. This disconnect has been widely critiqued as a structural
limitation of educational systems adapting to technological change (West,
2019). Importantly, students’ conditional acceptance of
AI—emphasizing responsible and ethical use—reflects a pragmatic
stance rather than technological determinism. Such perspectives align with
calls for educational approaches that position AI as a tool to augment human
judgment and higher-order thinking, rather than as a substitute for
intellectual effort (Luckin et al., 2016; Selwyn, 2020; Holmes et al., 2021=
). Implications Building on the findings discussed above,
particularly the normalization of artificial intelligence as an invisible
component of students’ daily practices and the persistent ambivalence
observed in their perceptions, the following implications outline key
considerations for educational practice and future research. The findings of this study have several
educational and policy-related implications. First, the predominance of
functional rather than conceptual familiarity with artificial intelligence
among secondary school students highlights the urgent need to incorporate
critical AI literacy into formal education. Educational institutions should
move beyond prohibitive or purely instrumental approaches and develop
curricular frameworks that explicitly address how AI systems operate, their
limitations, and their ethical implications. Second, the widespread uncertainty surround=
ing
AI’s impact on employment and society underscores the importance of
schools as spaces for informed dialogue. Educational systems can play a key
role in contextualizing AI within social, economic, and labor frameworks,
enabling students to develop realistic expectations about future profession=
al
pathways. Finally, students’ perception of
education as a primary sector for AI benefits suggests that schools are vie=
wed
as strategic actors in the responsible integration of emerging technologies.
Aligning educational policy with these expectations may contribute to a more
human-centered and socially responsible implementation of artificial
intelligence in Mexico. For further research Future research should expand the geographi=
cal
scope of this study to include additional regions of Mexico in order to exa=
mine
whether the patterns identified here persist across different social and
educational contexts. While the present research provides insight into
students’ perceptions in two regions of Puebla, broader sampling would
strengthen the generalizability of the findings. Methodologically, future studies could
incorporate qualitative instruments such as interviews or focus groups to
explore students’ reasoning, ethical concerns, and lived experiences =
with
artificial intelligence in greater depth. Additionally, comparative research
that includes teachers’ perspectives would offer a more comprehensive
understanding of how AI is currently approached, regulated, and interpreted
within school environments, informing more coherent and context-sensitive
educational strategies. CONCLUSION This study explored the perceptions of
Generation Z students enrolled in public technical junior high schools in
Puebla, Mexico, regarding artificial intelligence, its everyday presence, a=
nd
its perceived social, educational, and labor implications. The findings show
that artificial intelligence is already deeply embedded in students’
daily routines; however, their understanding of these technologies remains
primarily functional rather than conceptual. Students demonstrate frequent interaction w=
ith
AI-based systems and a generally open attitude toward learning about artifi=
cial
intelligence in formal educational contexts. At the same time, their respon=
ses
reveal persistent uncertainty about AI’s broader societal impact, par=
ticularly
in relation to employment and long-term national development. This ambivale=
nce
reflects limited access to structured information and the absence of clear
institutional narratives that frame artificial intelligence within social,
ethical, and economic contexts. The study highlights a gap between the rapid
integration of artificial intelligence into students’ everyday
environments and the limited educational frameworks available to support
critical understanding. Addressing this gap represents an important challen=
ge
for educational systems, which are increasingly perceived by students as key
spaces for fostering informed, ethical, and human-centered engagement with
artificial intelligence. In this context, the present research
contributes empirical evidence on how Generation Z students in technical
secondary education in Mexico perceive and interact with artificial
intelligence within their academic and digital environments. By integrating
quantitative trends with qualitative insights, the findings reveal a patter=
n of
functional familiarity accompanied by conceptual uncertainty and ethical
ambivalence. This combination underscores the need for educational approach=
es
that move beyond instrumental use and explicitly promote critical
understanding, ethical reflection, and future-oriented competencies related=
to
AI. Consequently, the study offers a contextualized contribution to current
debates on artificial intelligence in education, particularly in underexplo=
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