Artificial Intelligence Literacy Research Articles

Advancing higher education with GenAI: factors influencing educator AI literacy

Artificial Intelligence (AI) literacy has emerged as a critical skill across various disciplines and industries, including education. This study aimed to identify the factors that influence educators' AI literacy and to examine the relationships among these factors. A sequential mixed methods approach was used to investigate the factors influencing faculty members' AI literacy, with qualitative data collected from 33 faculty members through focus group discussions and semi-structured interviews. Quantitative data were then gathered using the finalized survey instrument, completed by 538 faculty members from diverse disciplines and higher education institutions in Palestine. Data analysis was conducted using Smart PLS. The findings revealed several key factors that impact educators' AI literacy, including AI competencies, perceived usefulness of AI, ease of use, professional development, and community support. Additionally, prior experience with technology played a significant role in developing AI literacy. While the study's mixed methods design provided depth, one limitation was that the qualitative phase involved a relatively small sample. Future research should further explore the broader implications of AI in education and its integration across various academic fields.

Conceptualizing pre-service teachers’ artificial intelligence readiness and examining its relationship with various variables: The role of artificial intelligence literacy, digital citizenship, artificial intelligence-enhanced innovation and perceived threats from artificial intelligence

Artificial intelligence (AI) is a new field that leads to change and transformation in the field of education. As AI technologies develop, it becomes more important to investigate these new technologies as a subject to be included in educational levels. The contribution of AI to success in educational settings is closely linked to the preparation of teachers. On the other hand, AI is an important concept that should be learnt by all students regardless of their educational level. Therefore, it is important to understand how prepared future teachers are for AI learning to ensure the effective implementation of AI in schools. Furthermore, addressing the perceived threats and digital citizenship levels arising from the use of emerging AI-based technologies requires individuals to have effective AI-related knowledge, skills and values. The aim of this study is to reveal the relationship between pre-service teachers’ AI readiness levels and various variables. These variables are perceived threats from AI, AI-enhanced innovation, AI literacy, digital citizenship. A total of 816 pre-service teachers participated in the study. PLS-SEM was used to evaluate the relationships between the research variables. In addition, Multigroup Analysis (MGA) was applied to model sub-samples according to gender. It was found that AI-enhanced innovation levels were significantly affected by the dimensions of AI readiness: cognition, vision and ethics in teaching. Perceived threats from AI level was significantly affected by ability and ethics in teaching, which are the dimensions of AI readiness. Perceived threats from AI levels had a significant effect on AI literacy. AI-enhanced innovation was found to have a significant effect on AI literacy and digital citizenship. In addition, differences were found according to gender. The results of this study can also guide pre-professional development programs to be developed for pre-service teachers, which is an important factor to be considered in AI education.

ARTIFICIAL INTELLIGENCE AWARENESS ANDITS INFLUENCEON CAREER DECISION-MAKING AMONG UNIVERSITYSTUDENTS

This study investigates how university students' career decision-making is impactedbytheirawareness of artificial intelligence (AI). Few studies have looked at howstudents' understanding of AI influences their career choices and capacity to adjust to the changinglabor market, despite the fact that prior research has concentrated on AI's impact onemployment patterns. Analyzing differences in AI awareness and its impact across variousacademic fields, skill development, and career confidence is the aim of this study. Materialsand Methods: A survey of college students and a thorough literature evaluation of peerreviewed sources served as the foundation for this study. To evaluate AI familiarity, opinionsabout AI-driven employment opportunities, and its impact on career decision-making, astructured questionnaire was disseminated using Google Forms. Stratified randomsamplingwas used to ensure representation across fields among the 106 students who took part inthestudy. Data were analyzed using IBM SPSS Version 26, employing statistical tests suchasthe Chi-Square test, Independent Samples T-Test, and One-Way ANOVAto identifysignificant relationships. Results and Discussion: A statistical study showed that therearenotable variations in the ways that job ambitions are influenced by AI awareness. Studentswith high and low awareness of AI showed significantly different levels of career confidence(p < 0.05), according to the Independent Samples T-Test. Students in AI-intensive fieldsdemonstrated higher career adaptability and confidence in AI-driven job markets, accordingto the One-Way ANOVA test (p < 0.01). Students who knew more about AI were more likelyto look into occupations that involved AI, according to the Chi-Square test, which showeda strong association (p < 0.05) between AI awareness and career decisiondeterminants.Conclusion The study comes to the conclusion that university students' careerdecisions, skill development, and ability to adjust to changes in the labor market areall greatly impacted by their awareness of AI. Students who are more exposed to AI showgreater confidence in occupations powered by AI, but those who are less informed mayfindit more difficult to explore career options. Universities and legislators should incorporate careercounseling, skill-building initiatives, and AI-focused curricula to maximize career readiness. Future studies should examine the ethical implications of AI in professional development, cross-cultural differences, and AI literacy initiatives.

Artificial Intelligence Myths: Prevalence Among Turkish University Students and Comparative Analysis of ChatGPT Responses

Artificial intelligence (AI) has rapidly emerged as a transformative technology across various disciplines. However, its widespread adoption is accompanied by numerous myths, which are fueled by limited public understanding and can significantly shape how individuals perceive and interact with AI, often leading to negative consequences such as misunderstanding, fear, or resistance. Despite the importance of addressing these myths, research on the prevalence of such beliefs remains insufficient, particularly in the Turkish context. This study aims to determine the prevalence of AI myths among Turkish university students, investigate the factors influencing the adoption of these myths, and compare student perceptions with ChatGPT's responses to the same myths. The study analyzed survey data from 288 students (102 males, 35.4%, and 186 females, 64.6%) using an AI-myth survey consisting of 18 items. Both descriptive and inferential analyses were conducted to determine the prevalence of AI myths and investigate how factors such as academic background, gender, AI-related training, and media consumption influence the adoption of these myths. A comparative analysis was also performed between student responses and ChatGPT’s reactions to these myths. Analysis showed that certain AI myths are particularly prevalent among students. Students from technical disciplines demonstrated a greater ability to identify these myths, while prior AI training and media consumption had minimal impact. ChatGPT’s responses highlighted areas where better communication about AI is needed. The findings suggest that improving AI literacy and dispelling myths are essential for preparing students for more informed engagement with AI technologies.

The Role of Artificial Intelligence in Teaching and Administrative Tasks: Perspectives of DepEd Personnel

The rapid integration of Artificial Intelligence (AI) in education has introduced new opportunities and challenges to teaching and school management. AI tools such as Chat GPT, Grammarly, and AI-based lesson planners are transforming how educators deliver lessons and manage administrative tasks (de Jong, 2020; Takona, 2024). This study explored the perceptions, usage patterns, and attitudes of DepEd personnel in Tandag City toward AI tools, highlighting both the potential benefits and concerns associated with AI adoption. A descriptive quantitative research design was employed, involving 174 DepEd personnel from various roles, including teachers (82.2%), master teachers (5.7%), principals (2.9%), and administrative staff (1.7%). Data were gathered through an online survey and analyzed using statistical methods to determine the respondents’ demographic profiles, level of AI usage, perceptions, and attitudes toward AI integration in education. The findings revealed that most respondents (87.4%) were familiar with AI tools, with Chat GPT being the most commonly used application (60.9%), consistent with trends noted by Zhang et al. (2021). Although AI usage frequency varied, 24.7% of respondents reported using AI tools weekly, while 20.1% used them daily, and 37.4% used them rarely. Despite the widespread use of AI, formal training on AI tools remained limited, with 86.2% of respondents reporting no attendance at related seminars or training, reflecting the gaps identified by Anwar and Gupta (2021). This gap highlights the need for professional development initiatives to build AI literacy and confidence among educators. The study also revealed a generally positive perception of AI, with a mean perception score of 3.71 (SD = 0.33), recognizing its potential to enhance creativity, innovation, and productivity (Davenport et al., 2020). However, respondents expressed concerns about data privacy (64.9%) and job displacement (58.6%), as well as skepticism regarding the reliability of AI-generated content (54.0%) (Frey & Osborne, 2017; Taddeo & Floridi, 2018). While there was cautious optimism regarding the future use of AI in education, many respondents (60.4%) preferred human interaction over AI-powered assistants (Chen et al., 2020). To address these challenges, the study recommends targeted training programs that emphasize practical applications, data security, and ethical considerations. Enhancing AI literacy will enable educators to maximize the benefits of AI while mitigating potential risks. Further research on the long-term impacts of AI adoption in education is essential to ensure effective and responsible integration that fosters inclusive and adaptive learning environments (Brynjolfsson & McAfee, 2017).

The Evolving Role of Human Translators in the Age of Artificial Intelligence: Perceptions, Challenges, and Adaptation Strategies

The rise of artificial intelligence (AI) in translation has drastically altered the profession, with machine translation (MT) and neural machine translation (NMT) introducing automation and efficiency. While AI brings benefits such as increased productivity and cost reduction, it raises significant concerns among translators regarding job displacement, ethical risks, and the devaluation of human translation. This study aims to explore the perceptions of translators, educators, and students about the impact of AI on their translation profession, addressing concerns and suggesting strategies for adapting to the AI-driven landscape. Using a qualitative method (semi-structured interviews), the research gathered insights into how translators perceive the evolving nature of their roles, the challenges they face, and their recommendations for skill development and adaptation. Findings indicate that AI has enhanced efficiency in translation work, particularly in technical, legal, and research-based translations, shifting translators’ roles toward editing and post-editing AI-generated drafts. Tools like MemoQWeb help maintain consistency through translation memories and term bases. However, AI struggles with literary and cultural translations due to figurative language and cultural nuances, and ethical concerns such as data privacy and translator deskilling remain pressing. Translators emphasize the need for skill development in AI-assisted workflows to balance automation with human expertise. This study contributes to the growing discourse on AI in translation by providing empirical insights into how translators navigate AI-driven changes, the skills required for adaptation, and the ethical challenges they face. It highlights the importance of integrating AI literacy into translator education and professional development, offering strategies for leveraging AI while preserving human creativity and linguistic accuracy.

AI and inclusion in simulation education and leadership: a global cross-sectional evaluation of diversity.

Simulation-based medical education (SBME) is a critical training tool in healthcare, shaping learners' skills, professional identities, and inclusivity. Leadership demographics in SBME, including age, gender, race/ethnicity, and medical specialties, influence program design and learner outcomes. Artificial intelligence (AI) platforms increasingly generate demographic data, but their biases may perpetuate inequities in representation. This study evaluated the demographic profiles of simulation instructors and heads of simulation labs generated by three AI platforms-ChatGPT, Gemini, and Claude-across nine global locations. A global cross-sectional study was conducted over 5days (November 2024). Standardized English prompts were used to generate demographic profiles of simulation instructors and heads of simulation labs from ChatGPT, Gemini, and Claude. Outputs included age, gender, race/ethnicity, and medical specialty data for 2014 instructors and 1880 lab heads. Statistical analyses included ANOVA for continuous variables and chi-square tests for categorical data, with Bonferroni corrections for multiple comparisons: P significant < 0.05. Significant demographic differences were observed among AI platforms. Claude profiles depicted older heads of simulation labs (mean: 57years) compared to instructors (mean: 41years), while ChatGPT and Gemini showed smaller age gaps. Gender representation varied, with ChatGPT and Gemini generating balanced profiles, while Claude showed a male predominance (63.5%) among lab heads. ChatGPT and Gemini outputs reflected greater racial diversity, with up to 24.4% Black and 20.6% Hispanic/Latin representation, while Claude predominantly featured White profiles (47.8%). Specialty preferences also differed, with Claude favoring anesthesiology and surgery, whereas ChatGPT and Gemini offered broader interdisciplinary representation. AI-generated demographic profiles of SBME leadership reveal biases that may reinforce inequities in healthcare education. ChatGPT and Gemini demonstrated broader diversity in age, gender, and race, while Claude skewed towards older, White, and male profiles, particularly for leadership roles. Addressing these biases through ethical AI development, enhanced AI literacy, and promoting diverse leadership in SBME are essential to fostering equitable and inclusive training environments. Not applicable. This study exclusively used AI-generated synthetic data.

Artificial Intelligence in the Curriculum: Development and Implementation of a Professional Training Program to Promote Literacy Among Health Education College Majors

Artificial intelligence (AI) is rapidly reshaping many sectors of society, including healthcare and health education. While AI has long been embedded in engineering, computer science, and mathematics curricula, it has not yet been intentionally integrated in a meaningful way in other curricula like health education. The employment of health education specialists continues to increase rapidly, driven primarily to contain healthcare costs and improve health outcomes. Thus, the next generation of health education specialists must possess AI literacy as a minimum learning outcome and a level of competency that enables them to work effectively in the rapidly evolving AI-driven healthcare workforce. This paper discusses the design and implementation of an AI professional training course, “AI in Health Education and Health Promotion,” for health education majors at a major southeastern university in the United States that mandates integration of AI across the curriculum for all college majors. It also presents the course content, teaching methods, implementation strategies, student feedback, and lessons learned. At the end of the 2023 to 2024 academic year, 528 students completed the training. Pre-training qualitative responses suggested a basic understanding of AI but a limited understanding of its core principles and applications. Post-training responses showed excitement about AI’s potential to enhance health education practices, particularly in creating tailored messages. However, their responses also revealed concerns about the potential misuse of AI. This curriculum presents a model for other health education programs that seek to design their own AI training programs.

Emerging Trends in AI for Academic Law Libraries: Global Insights with a Caribbean Lens

Abstract Artificial Intelligence (AI) is rapidly transforming the landscape of academic law libraries worldwide, offering new opportunities for enhancing legal research, information management, and user engagement. This article examines emerging trends in AI applications within academic law libraries, focusing on global developments alongside the unique challenges and opportunities faced in the Caribbean context. Key areas of exploration include AI-powered legal research tools, natural language processing (NLP) applications, and the ethical considerations surrounding AI integration. Drawing from insights presented at the CARALL Conference in July 2024, this article provides a comparative analysis of global best practices and proposes strategic recommendations for Caribbean academic law libraries to harness the potential of AI while addressing regional gaps in technological infrastructure and AI literacy.

Student’s Perception of Syllabus Adoption in Higher Education; Redesigning for the Age of AI

This research investigates the incorporation of artificial intelligence (AI) within higher education curricula, concentrating on students’ views regarding necessary syllabus modifications to adequately prepare for a future influenced by AI. The study delineates three primary objectives: to determine what elements should be included in the syllabus, to identify key AI tools for academic growth, and to understand the challenges associated with embedding AI into current educational frameworks. A qualitative research study was adopted, employing semi-structured interviews with ten students selected through purposive sampling. A thematic analysis was performed to uncover recurring themes and insights. The results reveal a significant demand for AI literacy, project-based learning, and practical applications as vital components of a restructured syllabus. Students identified tools such as Grammarly, ChatGPT, and specialized AI platforms for various disciplines as essential for academic achievement. Nonetheless, the challenges of over-reliance on AI, diminished creativity, and complacency were also noted. This investigation highlights the necessity for a syllabus that effectively balances technological integration with the maintenance of creativity and critical thinking. By considering student perspectives, higher education institutions can enhance readiness for graduates poised to enter an AI-influenced job market. The implications of this study suggest that educators should emphasize the inclusion of project-based learning modules that motivate students to leverage AI tools for addressing real-world challenges. Faculty development programs should aim at providing educators with the competencies required to assist students in the ethical and productive application of AI. Future inquiries should examine faculty opinions and the long-term effects of AI-enhanced syllabi.

What Is in There for Artificial Intelligence to Support Mental Health Care for Persons with Serious Mental Illness? Opportunities and Challenges.

Artificial intelligence (AI) holds potential to support persons with serious mental illness, but evidence remains limited. To explore opportunities and challenges there, we conducted qualitative interviews with multiple Norwegian mental health stakeholders. Data was analyzed using thematic analysis and sentiment analysis. Twenty-two informants shared their opinions, with half expressing moderately negative sentiments. Findings suggest AI can optimize mental health service delivery and encourage a flexible approach to recovery. However, AI's ability to provide emotional support may inadvertently worsen isolation, highlighting the need for a more holistic approach to human oversight and personal adaptation. Enhancing AI literacy and gathering more evidence from both persons and service providers is essential for future development.

Principles for enhancing trust in artificial intelligence systems among medical imaging professionals in Ghana: A nationwide cross-sectional study.

Principles for enhancing trust in artificial intelligence systems among medical imaging professionals in Ghana: A nationwide cross-sectional study.

Engaging English language learners in AI literacy practices: A conceptual framework and practical strategies for educators

As artificial intelligence (AI), and especially generative AI, are increasingly impacting daily life, it is becoming essential for learners to acquire AI literacy — the capability to interact with AI at the interface of technology and the target language. Without AI literacy, they may struggle to navigate AI-driven systems and access benefits of this new technology. Questions of how to define and operationalise AI literacy loom large across the educational sector, but existing approaches generally do not consider the specific needs of language learners. In this conceptual paper, we focus on AI literacy for English language learners — we critically review existing research on AI literacy, provide an overview of a conceptual model of AI literacy that we have developed for language learning contexts, explain its pedagogical implications, and illustrate the theory in action through two detailed examples of learning units to help English teachers to operationalise the model in their practice.

Adoption challenges to artificial intelligence literacy in public healthcare: an evidence based study in Saudi Arabia

In recent years, Artificial Intelligence (AI) is transforming healthcare systems globally and improved the efficiency of its delivery. Countries like Saudi Arabia are facing unique adoption challenges in their public healthcare, these challenges are specific to AI literacy, understanding and effective usage of AI technologies. In addition, cultural, regulatory and operational barriers increase the complication of integrating AI literacy into public healthcare operations. In spite of its critical contribution in enabling sustainable healthcare development, limited studies have addressed these adoption challenges. Our study explores the AI literacy adoption barriers in context to Saudi Arabian public healthcare sector, focusing on its relevance for advancing healthcare operations and achieving Sustainable Development Goals (SDGs). The research aims to identifying and addressing the adoption challenges of Artificial Intelligence literacy within the public healthcare in Saudi Arabia. The research aims to enhance the understanding of AI literacy, its necessity for enhancing healthcare operations, and the specific hurdles that impede its successful AI adoption in Saudi Arabia’s public healthcare ecosystem. The research employs a qualitative analysis using the T-O-E framework to explore the adoption challenges of AI literacy. Additionally, the Best-Worse Method (BWM) is applied to evaluate the adoption challenges to AI literacy adoption across various operational levels within Saudi Arabia’s public healthcare supply chain. The study uncovers substantial adoption challenges at operational, tactical, and strategic level, including institutional readiness, data privacy, and compliance with regulatory frameworks. These challenges complicate the adoption of AI literacy in the Saudi public healthcare supply chains. The research offers critical insights into the various issues affecting the promotion of AI literacy in Saudi Arabia’s public healthcare sector. This evidence-based study provides essential commendations for healthcare professionals and policymakers to effectively address the identified challenges, nurturing an environment beneficial to the integration of AI literacy and advancing the goals of sustainable healthcare development.

Mediating effect of AI attitudes and AI literacy on the relationship between career self-efficacy and job-seeking anxiety

As artificial intelligence (AI) technology quickly grows, college students have new worries and fears. Using Marx’s theory of labour alienation, this study explores the complex relationship between college students’ job-seeking anxiety (JSA) and career self-efficacy (CSE) in the context of the AI era. A structural equation modeling (SEM) study of data from 455 Chinese students indicates that CSE adversely affects JSA. Moreover, AI attitudes (AIA) and AI literacy (AIL) play significant mediating roles in the relationship between career self-efficacy (CSE) and job-specific anxiety (JSA). Specifically, these factors help explain how CSE influences JSA by fostering positive perceptions of AI and improving students’ understanding of AI technologies. The findings underscore the importance of cultivating positive attitudes toward AI, enhancing AI literacy, and strengthening career self-efficacy to reduce job-seeking anxiety and better prepare students for the challenges of an AI-driven job market. These observations provide significant implications for educators and policymakers in developing interventions to enhance students’ career preparedness and protect their mental health during technological changes.

Building Indonesia’s Golden Generation 2045: Fostering Financial Literacy and Information Technology Competencies in SMAN 1 Indralaya

Currently digital economy, proficiency in artificial intelligence (AI), digital technologies, and personal finance is essential. This community engagement initiative at SMAN 1 Indralaya integrated AI, digital, and financial literacy training through a four-stage framework: needs assessment, instructional delivery, technical mentoring, and evaluation. The programme significantly improved students’ ethical digital awareness, practical use of AI tools for budgeting, and basic financial reporting skills. The spontaneous formation of peer-learning groups indicated a shift toward autonomous, sustainable learning. These outcomes affirm the effectiveness of AI-integrated pedagogies in cultivating future-ready competencies in under-resourced educational settings.

Analysis of college students' attitude towards using AI in their academic works

This study looks the attitudes of college students at Isabela State University towards the use of Artificial Intelligence (AI) tools in academic work. Using a descriptive quantitative approach, survey data were collected via an online questionnaire that assessed AI familiarity, usage frequency, perceived benefits, ethical concerns, and openness to institutional support. The results indicate that most students are familiar with and actively use AI tools for assignments, research, and projects, with a majority rating their experience as beneficial. However, concerns such as misinformation, accuracy, and privacy in monitored environments were also noted. Despite these challenges, students showed a strong willingness to participate in ethical and responsible AI training programs. These findings underscore the need for universities to implement AI literacy initiatives that equip students with both the technical and ethical knowledge necessary for responsible usage of AI in academic settings.

Artificial intelligence literacy education in primary schools: a review

Abstract Artificial intelligence (AI) has become an important part of 21st-century life and this requires that students understand how to adapt to this change. Despite calls to extend AI literacy education from university to young students, there remains a lack of evidence-based research informing educators and researchers on the content of AI literacy education at the primary school level. This study aims to offer a comprehensive overview of what constitutes AI literacy education in primary schools, including its theoretical frameworks, pedagogical strategies, learning tools, assessment methods, educational outcomes, and challenges. The study presents a systematic review mapping process using Scopus and the Web of Science. Twenty-five empirical studies focusing on the primary school context were selected. The review revealed that (1) AI literacy encompasses a fluid conceptual understanding of digital literacy in terms of interacting and collaborating with AI, computational thinking, critical data literacy, and AI ethics; (2) constructionism, the constructivist theoretical framework, and the ARCS (Attention, Relevance, Confidence, and Satisfaction) model of instructional design were the dominant means of constructing the research design of the selected studies; (3) constructivist methodologies, project-based learning, programming, and human-agent interaction were commonly used by the selected studies, and AI learning tools, particularly intelligent agents, were often adopted in AI literacy teaching and learning research; (4) mixed-research methods were the most common, with surveys, interviews, and artifacts being employed to evaluate students’ learning outcomes; and (5) there were positive academic, affective, and behavioral educational outcomes, as well as course satisfaction. To our knowledge, this is the first systematic review to offer a detailed perspective on AI literacy at the primary school level, providing valuable insights for researchers, policymakers, and educators designing future educational frameworks, curricula, and assessment. Future research directions are also discussed.

The Role of Artificial Intelligence and Digital Literacy in Enhancing Employee Effectiveness and Efficiency in the Economic Sector

The advancement of technology, particularly artificial intelligence (AI) and digital literacy, has brought significant changes to the workforce, including the economic sector. This study aims to analyze the role of AI and digital literacy in enhancing employee effectiveness and efficiency. AI enables the automation of routine tasks, optimization of decision-making, and increased productivity through faster and more accurate data analysis. Meanwhile, digital literacy is a crucial factor for employees to adapt to new technologies and utilize digital tools optimally. This research employs a qualitative method with a literature review approach to examine the impact of AI implementation and digital literacy levels on employee performance. The findings indicate that a combination of AI and digital literacy can improve work efficiency, reduce administrative burdens, and support innovation in business processes. However, challenges such as human resource readiness and adaptation to technological changes remain significant barriers. Therefore, strategies to enhance digital competencies for employees and policies supporting AI integration in the workplace are needed.

Artificial Intelligence use cases adopted by people and their impact on achieving sustainable development goals: a systematic review

Individuals are increasingly integrating Artificial Intelligence (AI) into their lives, adopting various use cases in healthcare, education, urban mobility, and more. AI has the potential to enhance efficiency, well-being, and societal progress, but it also has negative potential associated with ethical challenges, privacy concerns, and social inequality. A significant research gap remains in understanding the impacts of AI use cases adopted by people on SDG achievement. This study addresses that gap through a systematic analysis of whether AI adoption by people supports or hinders progress toward the SDGs. Using the PRISMA framework, we conducted a systematic review of 131 studies. The results show that the overall impact of AI use cases adopted by individuals on the SDGs is moderately positive. These use cases significantly contribute to areas such as healthcare, innovation, and sustainable urban development, yet their effects remain complex and context dependent. While individually adopted AI fosters efficiency and well-being in many domains, concerns about job displacement, biased decision-making, and misinformation highlight the need for responsible deployment. The study emphasizes the importance of ethical AI governance, equitable access, and AI literacy to ensure its positive contribution to sustainable development. Future research should not only empirically evaluate the real-world impacts of AI applications adopted by people from a sustainability perspective but also explore and develop strategies to mitigate negative impacts on progress toward the SDGs while maximizing their positive contributions. This research contributes to the evolving discourse on AI adoption by people and its implications for sustainable development.