The university training of journalists in the context of Articial
Intelligence: a systematic review
La formación universitaria de periodistas en el contexto de la Inteligencia Articial:
una revisión sistematizada
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ISSN: 1696-019X / e-ISSN: 2386-3978
How to cite this article:
Sivira Camacaro, R. (2025). e university training of journalists in the context of Articial Intelligence: a systematic review.
Doxa
Comunicación
, 40, pp. 513-529.
https://doi.org/10.31921/doxacom.n40a2225
Rosmir Sivira Camacaro.
Journalist with over 10 years of experience and a Master’s in Applied Linguistics, specializing
in content generation, communications management, and discourse analysis. I have a research focus on discursive
interaction. I worked for 9 years at
El Impulso
, the oldest newspaper in Venezuela, as a journalist and editor for Tourism
and Gastronomy, later as a journalist for Economy and Business. I also participated in foundations supporting rural
tourism and wrote for specialized magazines. In Chile, I have worked as a reporter for media outlets and in institutional
journalism for companies in the education sector. Additionally, I have led national digital social campaigns with funding
from the Undersecretary of Social Security´s Educational Funds in Chile. Currently, I serve as Secretary of Studies and an
academic in the Journalism program at the Universidad Autónoma de Chile, Talca campus.
Autonomous University of Chile, Chile
[email protected]
ORCID:
0000-0002-5266-7371
is content is published under Creative Commons Attribution Non-Commercial License. International License CC BY-NC 4.0
Recibido: 19/03/2024 - Aceptado: 27/09/2024 - En edición: 19/11/2024 - Publicado: 01/01/2025
Resumen:
La Inteligencia Articial (IA) gana terreno en la industria de las comuni
-
caciones y se hace cargo de labores que habitualmente realizan los perio
-
distas. Sin embargo, la aplicación de herramientas de la tecnología de la
información exige competencias especícas. El objetivo del presente estu
-
dio es analizar los planteamientos de formación periodística en institu
-
ciones de educación superior, para el desarrollo de competencias relacio
-
nadas con la Inteligencia Articial y el periodismo automatizado. Para
ello se realizó la revisión sistematizada de 107 artículos cientícos. Entre
los hallazgos, se destacó que las universidades no abordan de manera
especíca y profunda contenidos sobre IA, sumado a que los docentes de
-
claran no contar con competencias para impartir asignaturas anes a la
aplicación de la IA en periodismo, conocimiento que ya se exige en el mer
-
cado del trabajo. Se concluye que existen importantes deciencias en la
Received: 19/03/2024 - Accepted: 27/09/2024 - Early access: 19/11/2024 - Published: 01/01/2025
Abstract:
Articial Intelligence (AI) is gaining ground in the communications
industry, taking over tasks traditionally performed by journalists.
However, the application of information technology tools requires
specic competencies. e aim of this study is to analyze the
training approaches for journalism in higher education institutions
concerning the development of skills related to Articial Intelligence
and automated journalism. A systematic review of 107 scientic
articles was conducted. Among the ndings, it was noted that
universities do not specically and deeply address content related
to AI, and educators reported lacking the competencies to teach
courses related to the application of AI in journalism, knowledge
that is already demanded in the job market. It is concluded that there
are signicant deciencies in university training in AI for journalists,
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formación universitaria en IA para periodistas, resaltando la necesidad
de actualizar los programas de estudio e incorporar enfoques interdisci
-
plinarios. Se sugiere capacitar a docentes y promover la colaboración con
expertos en tecnología para preparar a los futuros periodistas en el uso
ético y crítico de herramientas automatizadas.
Palabras clave:
Inteligencia articial; periodismo automatizado; formación
periodística; perl y rutinas de trabajo.
highlighting the need to update study programs and incorporate
interdisciplinary approaches. It is suggested to train educators and
promote collaboration with technology experts to prepare future
journalists for the ethical and critical use of automated tools.
Keywords:
Articial Intelligence; automated journalism; journalistic training;
prole and work routines.
1. Introduction
Articial Intelligence (AI) is increasingly being implemented in journalism, leading to the development of a protable industry
in the communications sector (Sánchez and Ruiz, 2020). However, the widespread use of these technological tools, along with
their greater accessibility, has generated uncertainty among journalism professionals due to a general lack of understanding
about their applications and consequences. is highlights the necessity of learning to use AI as a means of evolving, adapting,
and surviving (del Águila, 2023).
One recognized application area is the automation of news writing, also known as automated journalism (Graefe, 2016). is
phenomenon is spreading within the profession, alongside systems for topic detection, content verication, source checking,
video analysis, among others (Cohen et al., 2011; García-Marín, 2022). e various uses have sparked a debate about whether
tools like ChatGPT will replace journalists (Terol, 2023).
e introduction of new logics driven by technological evolution, particularly AI, is changing the workplace and its dynamics,
necessitating changes in education at all levels to create new proles that go beyond mere digitalization (Bocîi and Ursua,
2023).
In the specic case of journalism, journalists in media newsrooms are reshaping work organization, reecting a change in how
they confront the profession and machines (Parratt-Fernández et al., 2021). However, the authors argue that as a profession that
requires intellectual, creative, and emotional skills, journalism faces various challenges in adapting to Articial Intelligence
(Meso et al., 2023).
It is essential for both current practitioners and journalism students to acquire knowledge relevant to the profession, along
with the tools and skills to work alongside AI (Salazar, 2018). is context demands a renewal of university educational models
to teach digital tools and develop technological environments aligned with the job market (Ocaña-Fernández et al., 2019).
e aim of this research is to analyze the training approaches in journalism within higher education institutions and their
relationship with the competencies demanded by the job market in the context of articial intelligence and automated
journalism, based on a systematic review of recent scientic literature.
It may be thought that this topic is not extensively covered in universities and specialized journalism programs, given its
recent rise and the complexities of adapting curricula to continually evolving themes. However, there is scientic literature
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demonstrating that the journalistic prole demanded by the job market has evolved in response to changes brought about by
information technologies.
2. Method
is study follows a methodological design of systematic literature review with a descriptive approach to scientic texts
regarding the implementation of content on Articial Intelligence in journalist training for the development of competencies
in automated journalism.
Systematic review was used as the main methodology due to its ability to integrate and synthesize previous studies, identifying
patterns, gaps, and trends (Manchado et al., 2009) in the relationship between Articial Intelligence and journalist training.
is approach provides a solid foundation for critical reection on the competencies required in automated journalism and
how these are addressed in journalism training programs.
us, this approach allows for the identication of trends and shortcomings in the training of competencies related to AI in
the university context, providing a more comprehensive perspective. Established protocols were followed for the selection of
relevant articles, based on thematic and temporal criteria (Begoña et al., 2018).
e selection of articles was conducted in several stages. First, studies were identied through academic databases (Scielo,
Dialnet, Google Scholar), using the descriptors (Table 1) “articial intelligence,” “journalistic training,” and “automated
journalism”.
Table 1. Descriptors and Search Criteria
Search
Descriptor 1Descriptor 2Search Criteria
1
Journalist ProleArticial IntelligenceAutomated Journalism and Articial Intelligence.
2
Journalistic TrainingArticial IntelligenceJournalistic Training and Articial Intelligence.
3
Journalism ProgramArticial IntelligenceJournalism Program and +Articial Intelligence.
Source: Sivira, R. (2024)
e inclusion criteria were: 1) articles in Spanish published between January 2022 and December 2023, 2) studies that explicitly
address the relationship between AI and journalist training, and 3) open access to ensure the replicability of the study and that
the results can be contrasted and reviewed. Articles were excluded if they: 1) did not mention the key descriptors, 2) focused
on AI applied to social media or marketing rather than journalism, and 3) were published prior to the dened search period.
It is worth noting that the established timeframe for reviewing published research articles is due to the exponential growth of
AI in journalism by that date and the emergence of generative tools like ChatGPT 4 (Lopezosa et al., 2023) and other Natural
Language Processing (NLP) systems. Additionally, in the post-pandemic phase, between 2022 and 2023, eorts to adopt AI
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technologies intensied across various sectors, such as journalism and education (Álvarez and Biurrun, 2022; Migueláñez,
2022).
2.1. Population and Sample of the Scientic Literature
e total number of scientic articles considered in this review was 107 documents, extracted from databases and academic
search engines, which were selected according to the predened search criteria for the study.
After the initial selection, the articles underwent reective reading and categorization based on their relevance to the research
topic. A qualitative content analysis technique was employed to identify the key areas in which Articial Intelligence has been
integrated into journalism training programs.
e articles were evaluated across three main categories: 1) incorporation of AI into university curricula, 2) technological
competencies required by journalism students, and 3) ethical and deontological implications of AI in journalism. ese
criteria facilitated a comparative analysis that highlighted common patterns and areas where training gaps still exist.
e initial number was reduced to 71 articles, which, based on a data extraction form designed for the research, were
systematized according to their direct relevance to the study’s objectives. From this, 13 scientic publications were selected as
a sample for analysis and discussion (Figure 1).
Figure 1. Diagram of the Article Selection Process for Analysis
Source: Sivira, R. (2024)
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To ensure the validity of the ndings, a methodological triangulation strategy was applied, which included the review of
previous studies and the comparison of results across dierent databases. Additionally, a double review by the author was
conducted to ensure the consistency and quality of the conclusions. ese measures provided a more accurate view of the
state of AI training within the journalistic eld.
2.2. Selected Articles for Analysis
Tables 2 and 3 present a summary of the 13 research articles selected and analyzed for this study, based on the previously
mentioned search criteria and the objectives of the systematic review.
e bibliometric method was applied following the procedures outlined by authors such as Canavilhas and Giacomelli (2023),
who indicate that this methodology enhances clarity in the literature review process in qualitative research. is encompasses
everything from the development of the research question, conceptual framework, and construction of selection criteria to the
selection of studies, evaluation of their quality, synthesis, and reporting of results.
For the content analysis, the main categories were coded: 1) integration of AI in university programs, 2) technological
competencies taught, and 3) perceived impact on professional journalism routines. is provided a structured view of how AI
training is addressed in educational institutions and in the scientic literature.
e preselection of articles was carried out under strict relevance criteria, ensuring that each study included was directly
related to the central themes of the analysis: the incorporation of AI in journalistic training and the impact of automated
journalism on educational programs. Only those that oered a rigorous and explicit treatment of how AI is being implemented
or discussed in the eld of journalism education were selected.
Care was taken to ensure that the sample was representative of dierent methodological approaches and geographical areas
within the Spanish-speaking world.
Table 2. Selected Articles According to Search Criteria 1
N°Author/sArticle
Year of
publication
Objective
Methodology or Research
Technique
1
Fieiras-Ceide, C.,
Vaz-Álvarez, M., &
Túñez-López, M.
Strategies of Articial
Intelligence in European
Public Broadcasting: Uses,
Provisions, and Future
Challenges.
2023
To analyze the presence
of AI tools in public
audiovisual corporations.
In-depth, semi-structured
interviews with a
convenience sample of
15 corporations from
12 countries (Germany,
Belgium, Denmark, Spain,
Finland, France, Great
Britain, Netherlands,
Ireland, Italy, Sweden,
Switzerland, and members
of the EBU).
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2
Lopezosa, C., Codina,
L., & Ferran-Ferrer, N
Application of Articial
Intelligence in Journalism:
ChatGPT and the Uses
and Risks of an Emerging
Technology.
2023a
To outline the current
landscape of AI usage in
newsrooms by providing
an overview of applicable
AI tools.
Analysis of benchmarking
or performance comparison
of AI tools applied to
journalism. Conduct a
“walk-through” experience
or essay with ChatGPT,
involving the participation of
12 journalists from various
age groups and sectors.
3
Peña-Fernández,
S., Meso Ayerdi, K.,
Larrondo Ureta, A., &
Díaz Noci, J.
Without Journalists, ere
Is No Journalism: e Social
Dimension of Generative
Articial. .Intelligence in the
Media.
2023
To identify the main social
and epistemological chal
-
lenges posed by the adop
-
tion of generative AI in the
media.
Systematic Review of Re
-
search on the Implementa
-
tion of AI in the Media Since
2000.
4
Sandoval-Martín, T.,
& La-Rosa Barrolle
-
ta, L.
Research on the Quality of
Automated News in Inter
-
national Scientic Produc
-
tion: Methodologies and
Results.
2023
To identify the dominant
methodologies concerning
the quality of automated
news.
Systematic Review of the
Scientic Literature: Search
for Articles on “Journalism”
and “Articial Intelligence”
(N=670) from 2008—when
data journalism emerged as
we know it today—through
2022. Content analysis
and comparison of formal,
quantiable, and method
-
ological aspects.
5
Aramburú Moncada,
L. G., López-Redon
-
do, I., & López Hidal
-
go, A.
Articial Intelligence in
RTVE at the Service of
Empty Spain: Project for
Automated News Coverage
for the 2023 Municipal
Elections.
2023
To understand the function
-
ing of the project proposed
by RTVE and the applica
-
tion of Articial Intelligence
in this specic case, includ
-
ing benets and negative
eects, economic and tech
-
nical viability, characteris
-
tics of the generated infor
-
mational content, and the
impact on the population.
Systematic Review of Ex
-
isting Literature on the
Subject.
Open interviews with four
key stakeholders from the
companies involved.
6
Terol, T. M.
Mediatica Innovation:
Applications of Articial
Intelligence in Journalism
in Spain.
2023
To identify the various uses
of Articial Intelligence (AI)
in the production routines
of media organizations.
In-depth interviews with
journalism professionals
from RTVE, El País, and
Newtral, along with a litera
-
ture review.
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7
Canavilhas, J., &
Giacomelli, F.
Articial Intelligence in
Sports Journalism: Brazil
and Portugal.
2023
To understand whether
sports media in Brazil and
Portugal use AI in their
newsrooms (news produc
-
tion process) and to explore
expectations regarding the
use of these technologies.
Survey of media executives
from both countries.
Source: Sivira, R. (2024)
Table 3. Selected Articles According to Search Criteria 2
N°Author/sArticle
Year of
publication
Objective
Methodology or research
technique
1
Masip, P., López-
García, X., Díaz
Noci, J., Palomo, B.,
Salaverría, R., & Meso
Ayerdi, K
Past, Present, and Future
of University Education in
Cyberjournalism: Methods
and Trends.
2022
To understand the prole of
education related to digital
journalism in Spain.
Documentary review of
the teaching programs
for all subjects related to
cyberjournalism (n = 119)
published online by Spanish
universities, along with a
survey of their instructors
(n = 51).
2
Fernández Torralvo,
Nerea.
Between Lights and
Shadows: Articial
Intelligence in Journalism
and Its Professional, Ethical,
and Social Challenges.
2023
To understand current
attempts to implement
AI technologies in the
eld of journalism, as well
as the most innovative
integrations for the
future.
To
investigate how this
implementation is aecting
the development of the
profession, both in the labor
context and in ethical and
moral dimensions.
Systematic review of existing
literature.Semi-structured
interviews with journalists
and communication
experts.Quantitative and
qualitative analysis of the
undergraduate training
oerings of journalism
faculties in Spain registered
with the Registry of
Universities, Centers, and
Degrees (RUCT), focusing
on courses related to
digitalization and AI, as well
as their implications for the
profession in both labor and
ethical dimensions.
3
Lopezosa, Carlos and
Codina, Lluís and
Pont-Sorribes, Carles
and Vállez, Mari
Use of Generative Articial
Intelligence in Journalist
Training: Challenges, Uses,
and Educational Proposals.
2023b
To study generative AI
from the perspective of
journalistic and educational
interests.
Conducting of 4 in-depth
interviews in Spain.
Conducting 28 semi-
structured interviews with
university professors and
researchers in Latin America.
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4
De Vega Martín, A. L.
Digital Teaching
Competencies in Vocational
Training for Image and
Sound.
2023
To analyze the presence
of digital competencies
in the ocial curricula
of programs related to
future communication
professionals. To describe
the self-perception of
vocational training teachers
in Image and Sound
regarding their digital
competencies and the
importance they assign to
these skills in their students’
studies.
Mixed design of concurrent
triangulation.
Non-random quantitative
sample, of teachers
involved in the training
of future information
professionals. Analysis
of the presence of digital
competence in the ocial
curricula of studies related
to future communication
professionals.
5Gómez-Diago-G.
Perspectives on Addressing
Articial Intelligence in
Journalism Education: A
Review of Research and
Teaching Experiences.
2022
To identify perspectives and
experiences that provide
pathways for introducing
AI into communication
studies, specically in
journalism education.
Analysis of international
research projects and
international teaching
experiences that address
articial intelligence
and
integrate it into journalism
education.
6
Mancero Mosquera,
A. E., & Suárez
Ramírez, J. D.
Use of Articial
Intelligence Tools in the
Communication. Products
of Communication
Students.
2023
To identify the advantages
of using AI tools by students
in the production of
communication content.
Survey of students in the
Communication program at
the State University of Santa
Elena Peninsula, Ecuador.
Interview with professionals
in the eld
Source: Sivira, R. (2024)
3. Results
e qualitative analysis of the reviewed articles was deepened, focusing on academic trends and perspectives regarding the
incorporation of articial intelligence in journalism education. is allows for not only assessing current practices but also
proposing future directions for teaching AI to journalists.
Out of the 13 articles reviewed, only 3 explicitly mention the inclusion of AI in journalism curricula, and these are limited to
the introduction of basic technological tools without a focus on competency development.
In the case of universities oering courses on AI, there are notable limitations in integrating ethical and critical aspects, which
could impact the comprehensive training of future journalists.
e results also indicate that the majority of instructors lack specic training in AI, which limits their ability to teach these
contents eectively.
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3.1. e Application of AI Requires New Professional Proles
Fieiras-Ceide (2023) studied the application of articial intelligence in European public broadcasting, recognizing that its
implementation is limited and slow. e author emphasized the need to develop journalistic proles with a strong technological
component.
Lopezosa et al. (2023) analyzed the use of AI in newsrooms, focusing on currently available tools. ey identied signicant
benets in content production but also noted a shift in professional routines. is change could transform the required
professional proles, highlighting the need for greater specialization in these areas.
Peña-Fernandez (2023) systematically reviewed research on the implementation of AI in media since 2000. e study concluded
that AI has enabled the automation of routine journalistic tasks, such as writing simple news articles, monitoring social media,
and real-time fact-checking. However, the author warned that this implementation should not be limited to technical aspects;
it must also be viewed from a social perspective, considering its impact on audiences and the work dynamics of journalists.
In this regard, Aramburú et al. (2023) analyzed the use of AI in RTVE’s coverage of the 2023 municipal elections. ey
concluded that AI provides competitiveness, exibility, uidity, and speed to journalism. However, this paradigm shift must
be constrained by an ethical code regulating its use.
Sandoval-Martín and La Rosa (2023) identied dominant methodologies in the production of automated news and analyzed
the quality of the material produced. ey concluded that new methodological approaches are required, both from academia
and the media, to develop a human-centered perspective on AI in journalism.
Terol (2023) identied the uses of articial intelligence in journalistic routines within media outlets in Spain. e study pointed
out the lack of professional competencies for applying AI projects, indicating the necessity for new journalistic proles with
enhanced technological training and a focus on cognitively enriching content tasks.
Canavilha and Giacomelli (2023) studied the use of AI by sports journalists in Brazil and Portugal. ey concluded that
the penetration of AI in media is slow due to the lack of technical and professional capacities in articial intelligence. ey
suggest that human resources should be trained in AI and that these competencies should be integrated into higher education
curricula.
3.2. Journalism Education and Study Programs
Masip et al. (2022) analyzed the curricula of subjects related to cyber journalism and communication technologies in Spanish
universities. ey determined that, in a context of rapid and continuous changes, it is challenging to keep subjects updated.
However, the emergence of new job proles compels universities to be less resistant to change. e research noted that
undergraduate programs do not include AI in their content.
On his part, Gómez-Diago (2022) identied perspectives and experiences for introducing AI into journalism training programs.
e study found that while AI is taught from a critical perspective focused on competency acquisition, development is limited,
and there are few research initiatives on this topic.
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In this regard, brief case studies extracted from the reviewed literature were integrated to provide concrete examples of how
certain universities have begun to incorporate AI into their journalism programs. ese studies oer better insight into the
practical and pedagogical approaches emerging in this eld.
Fernández (2023) analyzed the eects of AI on the profession and described the development of this topic in digital subjects
within journalism faculties in Spanish universities. e conclusion was that programs do not address AI in a regulated, in-
depth, and organized manner. Content is only covered in a testimonial way –focused on web design and writing for digital
media– often viewed through the lens of data journalism (algorithms, databases, and spreadsheets) or its ethical implications.
Lopezosa et al. (2023) studied generative AI from both educational and journalistic perspectives. ey emphasized that an
AI course in journalism programs should meet the needs of students and the profession from an interdisciplinary approach,
connecting work with technical (engineers and IT professionals) and social (linguists and psychologists) areas.
Likewise, De Vega (2023) examined digital competencies among educators in professional training for image and sound, areas
of communication. e study found scant specic content on AI in the curricula, and teachers reported limited training in the
subject. Nonetheless, they acknowledged that students must acquire this knowledge for the future.
Mancero and Suárez (2023) identied the advantages of using AI tools in the products created by students in the Communication
program at the Universidad Estatal de la Península de Santa Elena in Ecuador. ey found that the program did not fully adopt
AI, resulting in students being unaware of the benets this new technology oers. e study highlighted that when training
future journalists in AI, ethical training, critical thinking, and responsibility must take precedence.
4. Discussion
Regarding the analysis of the state of the art on the approaches to journalism training in higher education institutions and
their relationship with the competencies demanded by the job market in the context of articial intelligence and automated
journalism, a review, selection, and study of scientic articles on the topic were conducted. It was found that research on AI in
the media and the academic oerings of journalism based on the changes generated by AI is limited compared to other topics
such as social media, which could be a hindrance.
e aforementioned relates to what Fieiras-Ceide (2023) states, highlighting the need for journalists with proles focused
on technologies related to the platforms used in the media, as well as a greater societal awareness of articial intelligence;
otherwise, employment opportunities in media with implemented AI will be limited.
However, as technology advances, so do the dangers and deceptions due to the credibility of AI-generated content, similar to
what authors like Franganillo (2023) and Marta-Lazo et al. (2020) have stated, indicating that it is necessary to increase public
awareness about the use and consumption of this new technology. It is therefore reected that the prole of the communicator
should be that of a professional capable of understanding and managing digital transformation, without neglecting the
foundations of the communicative process.
is relates to what the Coordination Committee for Teaching and Learning of the European University Association (2023) has
proposed, which identies the benets and limitations of using AI. It emphasizes that these applications generate changes
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in work proles or roles, as they transform journalistic routines, as already outlined by Lopezosa et al. (2023a). Journalists,
therefore, must continuously train in areas related to journalism and technology.
erein lies the reason for the necessary specialization in algorithms, therefore for journalists, regarding the need to increase
the level of knowledge required for the development of tasks related to AI, which contributes to the information process but
demands greater specic preparation.
However, to promote such planning spaces, it is required that the planned logics and methodologies center around audiences
and journalists, as Peña-Fernández (2023) suggests. Technological advancement must be understood, developed, and applied
as a social construction capable of transforming the relationship between humans and their reality (Tabarez and Correa, 2014).
AI not only works with artifacts and algorithms but also incorporates symbolic elements and social values that inuence its
interaction with the environment. What ethical implications does the adoption of AI in journalism pose, and how are these
addressed in university training?
e biases present in the data that feed AI systems can reproduce social stereotypes, as research on the use of AI in news
media has demonstrated (Gómez-Diago, 2022). is poses ethical challenges that must be considered in the design and
implementation of these systems.
It is reected that the use of AI in journalism requires updated methodologies that place humans at the center of decisions
and processes, thereby promoting a combination of technical knowledge and critical skills that allow journalists to analyze,
interpret, and enrich automated content. is involves an interdisciplinarity that should include collaboration among
communication professionals, AI engineers, as well as experts in ethics and linguistics (Lópezosa et al., 2023), in order to
ensure responsible and ethical journalism.
Such a proposal is directly related to what Porcello (2020) indicates, recognizing the need for an ethical code that ensures
accountability and transparency of algorithmic systems in decision-making. Additionally, norms regarding responsibility and
fairness based on human oversight are required.
ese logics imbue journalism with characteristics such as competitiveness, exibility, uidity, and speed. However, it is
reiterated that given the implications of AI, this paradigm shift must regulate its use (Aramburú et al., 2023), which brings back
the humanistic logic that in communicative practice, AI will be benecial as long as its application does not undermine the
ethical progress of journalistic activity, based on principles such as explainability, accountability, and self-regulation.
However, the collected data shows that the lack of technical competencies in AI among personnel in journalistic companies
limits the penetration of this technology (Canavilhas and Giacomelli, 2023; and Casallas, 2021), leading to poor management
and control of processes, which can have negative results at the level of mass communication and inuence on public opinion.
In this regard, it is essential that universities, in their duty of professional training, recognize that companies seek to hire
personnel aligned with the digital age.
In this sense, the question arises: What are the most in-demand competencies in the labor market, and how are training
programs responding?
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Changes in the tasks performed by media outlets have been identied, leading journalistic companies to demand technical
skills applicable to AI projects (Terol, 2023). erefore, as Marta-Lazo et al. (2020) note, the training of professionals must be
accompanied by the enhancement of cognitive skills that enrich journalistic tasks. is is a reality that has forced universities
to rethink the proles of journalism graduates, adapting their competencies and skills to new media and types of audiences.
Unlike automated AI, journalists not only gather and present data but also interpret the sociocultural, political, and ethical
context of events, oering a narrative that can challenge power structures, unmask biases, and highlight nuances that an AI
cannot detect. ese skills include empathy, which allows journalists to understand and represent the diversity of voices;
linguistic creativity, which enriches the narrative through the use of metaphors, irony, and complex rhetorical devices; and
critical thinking, essential for challenging ocial versions, asking deep questions, and avoiding simplications, as proposed by
journalism theorists, mass communication scholars, and thinkers like Kapuscinski (2002), Eco (2004), and Habermas (2014).
erefore, based on what Masip et al. (2022) propose, the emergence of new professional proles in journalism requires
universities to be more receptive to change, adapting their programs to technological and market demands. To achieve this,
it is necessary to analyze the phenomenon of articial intelligence and measure its impact in order to have a diagnosis that
allows for the identication of the weaknesses in current curricula and to adjust them for the training of professionals capable
of employing new technologies.
Universities and their journalism programs are beginning to adapt their curricula to the changes brought about by AI. However,
the specic subjects and proposals dedicated to the transformations of journalistic work due to AI and its applications are
limited in scope (Calvo-Rubio and Ufarte-Ruiz, 2020).
e resistance to adapting traditional pedagogical paradigms to AI is concerning, as failing to align with the models and
competencies demanded by society will result in outdated education with little inuence on social dynamics. is is evident
from studies like that of Fernández (2023), who argues that study programs including articial intelligence in their content do
not address it in a regulated and in-depth manner, which is related to the limited number of studies analyzing the application
of AI content in university curricula.
In most cases, the available analyses refer to the use of articial intelligence as a means or resource for the application of
teaching and learning methodologies (Aguilar et al., 2023; Yanqui, 2023; Falla-Falcón, 2023; Gutierrez, 2023), which is far
from training new journalistic proles and competencies in response to the demands of the communication and information
industry (Peña et al., 2020).
erefore, there is a need for new subjects to train proles in direct relation to both more technical professionals, such as
engineers, and social professionals, such as linguists, based on a model grounded in the foundations of AI and the technical
and ethical competencies required for its use (Lopezosa et al., 2023b). According to Liu (2023), the rapid application of AI
makes it necessary for educational practices to be constantly updated and adhere to ethical considerations, as well as critical
and responsible thinking.
is aligns with what De Vega (2023) proposes, stating that these new educational practices require academics trained in the
use of AI tools in the teaching-learning process and in journalistic practice, so that professional training meets the demands
required by communication companies. However, teachers report lacking sucient competencies to address AI-related
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content. is is why an AI Literacy Plan is needed to allow teachers to train in technical, ethical, and philosophical areas, which
would also change the teaching prole (Flores-Vivar and García-Peñalvo, 2023).
Although the application of AI in education is in its early stages, it is becoming an increasingly utilized tool (Adalid, 2023), thus
requiring professionals with critical thinking who can contribute to the social environment. e inclusion of AI in curricula
and teaching should therefore be approached from a critical perspective and with a focus on competency acquisition (Gómez-
Diago, 2022).
Journalism students enrolled in university programs that claim to include AI content are unaware of the benets it oers
in professional practice, as the adoption of the topic is not comprehensive (Mancero and Suárez, 2023). However, modern
education must be aligned with the sociocultural reality of the environment in which it takes place.
erein lies the reason why universities, in formulating their curricula, must include essential elements that allow for the
training of competent professionals with the potential to navigate their workspaces, with quality serving as an indicator
of education that is fully recognized by society. is includes content on articial intelligence applicable to areas such as
journalism.
Despite the revealing results, it is important to acknowledge that the language barrier limited the scope of the research by
restricting the review to studies in Spanish. is reduced the number of available articles and excluded relevant research
in other languages, particularly in English. Nevertheless, the results obtained fulll the objective of analyzing the academic
trends and perspectives regarding the incorporation of articial intelligence in journalistic training.
5. Conclusions
e applicability of articial intelligence in the eld of journalism is still under development, and the characteristics of
its integration depend on the competencies of the professionals within the industry, responsible for executing automated
journalism projects.
e advantages and benets of AI in journalistic work are recognized, as well as the need to formulate new professional
proles that address the demands of the media. Progressively, and based on economic reasons, the communication industry is
adopting tools from articial intelligence, which is why journalists with greater technological training and a focus on cognitive
and human tasks that enrich content are needed.
Currently, university training in AI for journalists presents signicant deciencies. Many university educators admit that their
knowledge on the subject is limited, which aects the quality of teaching. erefore, universities must prioritize the updating
of their study programs, incorporating specic modules on AI that include both its technical use and the ethical implications
of its implementation.
us, universities face the challenge of renewing their content and adopting an interdisciplinary approach that integrates
technical skills, such as AI programming, along with traditional competencies, such as critical and ethical analysis of discourse.
One possible strategy is to include specialized subjects in automated journalism and practical courses where students work
with AI in simulated journalistic writing tasks.
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To facilitate this process, it is essential to train educators in these areas and promote interdisciplinary collaboration with
experts in technology and social sciences, so that future journalists can play an active role in transforming the industry. In this
way, future journalists will be prepared to integrate automated tools into their routines while maintaining a critical and ethical
perspective in their work, thus collaborating with articial intelligence for the benet of the communication process.
To delve deeper into the topic, it is proposed to conduct a detailed review of journalism study programs, which will allow for
the collection of primary data on the integration of AI-related competencies. Additionally, it will be valuable to complement
this analysis with interviews or surveys of those responsible for academic programs to gain insights into how curricula are
adapting to the new demands of automated journalism.
Future research lines are also proposed, such as the need for longitudinal studies that follow the evolution of AI teaching in
journalism or evaluating pilot programs at universities that are already implementing AI in their curricula.
6. Acknowledgments
is article has been translated into English by the team at the Research Directorate of the Universidad Autónoma of Chile
(DIUA), and we would like to thank them for their work.
7. Conict of Interest
e author declares that there is no conict of interest contained in this article.
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