The impact of transformational leadership style on the intention to use AI technology in Lebanese banks: The role of perceived usefulness and ease of use

Objective: This study investigates the contribution of Artificial Intelligence (AI) technology to the learning process of accounting students in Surakarta, focusing on its adoption and associated learning ethics in the digital era.Methods: A quantitative approach was employed using a questionnaire distributed via Google Forms, targeting accounting students from private and state universities. The analysis utilized SmartPLS 3 for Partial Least Squares Structural Equation Modeling (PLS-SEM).Findings: The results indicate that Perceived Ease of Use significantly influences AI Technology Adoption, while Technology Readiness positively impacts both Perceived Usefulness and Perceived Ease of Use. However, Technology Readiness shows no significant effect on AI Technology Adoption. This highlights the critical role of ease of use over perceived usefulness in driving technology adoption among students.Novelty: This research contributes to the existing literature by demonstrating the nuanced relationships between technology readiness, perceived ease of use, and the adoption of AI technologies in accounting education, specifically in a developing context.Theory and Policy Implications: The findings suggest that educational institutions should focus on enhancing students' technological readiness and simplifying AI interfaces to promote adoption. This has implications for curriculum design and policy formulation aimed at effectively integrating AI technologies into accounting education.

Recent rapid advances in artificial intelligence (AI) technologies have brought to the agenda how to encourage the use of these technologies in education. Teachers' acceptance of artificial intelligence technologies has an important place in this context. This study, based on the Technology Acceptance Model (TAM), investigates the factors affecting teachers' acceptance of artificial intelligence technologies. For this purpose, a five-structure structural model for AI technology was proposed by adding Self-Efficacy and Anxiety to TAM. Data were obtained from teachers working in Turkey. A trial form consisting of 21 items was prepared for EFA. 18 items were confirmed by CFA. Structural Equation Modeling (SEM) was used to analyze the data. In the proposed model, 7 hypotheses related to Self-Efficacy (SE), Artificial Intelligence Anxiety (AIA), Perceived Ease of Use (PEU), Perceived Utility (PU) and Behavioral Intention (BI) were tested. Six of the seven proposed hypotheses were confirmed while one was not. There was a significant negative effect of teachers' SE on their AIA, AIA on their PEU, and AIA on their BI (H1, H2, H7). In addition, a significant positive effect of teachers' PEU on their PU, SE on their BI and PU on their BI was found (H3, H4, H6). However, the hypothesis (H5) that teachers' PEU has a significant positive effect on their BI was not supported. In the study, it was found that teachers' acceptance of using AI technologies in teaching is predictable by teachers' self-efficacy towards AI, AI anxiety and perceived usefulness. The results of this study contributed to the extension of TAM. In addition, the results of the study can help future educational planning in the use of educational technologies.

This study examines the role of different factors in supporting the sustainable use of Artificial Intelligence (AI) technologies in higher education, particularly in the context of student interactions with intelligent and human-centered learning tools. Using Structural Equation Modeling (SEM) and Artificial Neural Networks (ANN) within the Technology Acceptance Model (TAM), the research provides a detailed look at how trust influences students’ attitudes and behaviors toward AI-based learning platforms. Data were gathered from 200 students at Occidental Mindoro State College to analyze the effects of social influence, self-efficacy, perceived ease of use, perceived risk, attitude toward use, behavioral intention, acceptance, and actual use. Results from SEM indicate that perceived risk and ease of use have a stronger impact on AI adoption than perceived usefulness and trust. The ANN analysis further shows that acceptance is the most important factor influencing actual AI use, reflecting the complex, non-linear relationships between trust, risk, and adoption. These findings highlight the need for AI systems that are adaptive, transparent, and designed with the user experience in mind. By building interfaces that are more intuitive and reliable, educators and designers can strengthen human–AI interaction and promote responsible and lasting integration of AI in education.

Purpose: The purpose of this paper is to assess the impact of dimensions of technology readiness (TR) on accounting office staffʼs intention to use artificial intelligence (AI), using the mediating factors of the technologyʼs perceived usefulness (PU) and perceived ease of use (PEOU). Methodology/research approach: The study was based on a purposive sample of 200 staff members of accounting offices in Poland. Structural equation modelling (SEM) was used to test the relationships between the TR personality dimensions and the cognitive dimensions (PU and PEOU) of the technology acceptance model (TAM). Findings: The findings indicate that respondentsʼ optimism affected the perceived usefulness of technology, while innovativeness affected the perceived ease of use of AI technologies. In addition, the cognitive dimensions of the TAM were confirmed to in-fluence respondents' intention to use AI tools; thus, PU and PEOU mediate the relationship between TR dimensions and the intention to use technology. Research limitations/implications: The study focuses on a limited number of accounting practitioners. Moreover, the basis for the analysis was only two TR modera-tors: PU and PEOU. Originality/value: The articleʼs integration of knowledge from psychology, manage-ment and technology fosters a holistic approach to the issue of adopting technological innovations such as AI. The adopted research perspective enriches the theoretical contribution to the literature by identifying factors in AI technology adoption among Polish accountants. It also facilitates the application of the research results in practice as it takes into account the organisational and individual context of this process. Furthermore, the content of the article and the analysis contained therein can provide valuable support to organisations planning to use AI technologies, allowing them to improve their implementation strategies by considering both technical and human aspects.

Purpose: This study aimed to analyze the influence of trust on the acceptance of artificial intelligence (AI) technologies among small and medium-sized enterprises (SMEs). Based on the modified Technology Acceptance Model (TAM), the relationships between trust and perceived usefulness, ease of use, attitude, and implementation intention were examined. Need for the study: In dynamic digital transformation, SMEs face limited resources, low technological competence, and uncertainty about AI's ethical and functional aspects. Previous studies have rarely considered trust as a central factor in AI adoption models in the SME sector. Filling this research gap became the main motivator of this project. Methodology: A quantitative research method based on structural equation modeling (SEM) was used, using a five-point Likert scale questionnaire. Data were collected from the management staff of SMEs in Poland. The relationships between constructs were analyzed using confirmatory factor analysis (CFA) and model fit indices. Findings: The results confirmed the significant influence of trust on perceived ease of use, usefulness, and attitude towards AI and indirectly on implementation intention. Trust was a key factor supporting the positive perception and acceptance of AI technologies in the SME environment. The model achieved high construct validity and a good fit to empirical data. Practical Implications: The study suggests strengthening trust in AI – through algorithm transparency, user education, certification, and ethical frameworks – should be essential to SMEs' digital transformation strategies. The results provide practical guidance for decision-makers, policymakers, and technology providers on effectively supporting AI adoption in the SME sector.

IntroductionMedia students' acceptance and use of intelligent technology requires not only external environmental support but also the stimulation of internal driving forces. This study incorporates mindfulness into the classical Technology Acceptance Model (TAM) to investigate its role in shaping students' perceptions and behavioral intentions toward artificial intelligence (AI) tools. Specifically, the research examines: (1) the impact of mindfulness on media students' perceptions of AI technology; (2) the influence of mindfulness on their continuous intention to use AI technology; and (3) the moderating effect of perceived risk on the intention to adopt AI tools.MethodsBased on a conceptual model integrating mindfulness with TAM, this study conducted an offline questionnaire survey among 588 media students. The data were analyzed using SmartPLS and SPSS to test the structural equation modeling and moderating effects.ResultsThe findings revealed three key outcomes. First, mindfulness exerts a significant, direct, and positive influence on personal innovativeness (PI), perceived usefulness (PU), and perceived ease of use (PEU). Second, PI functions as a mediating variable in the relationship between mindfulness and AI-based behavioral intention (AIBI). Third, perceived risk (PR) significantly weakens the relationships between PI, PU, and AIBI.DiscussionThis study demonstrates that mindfulness enhances media students' intention to adopt AI tools by strengthening their perceptions of usefulness, ease of use, and personal innovativeness. However, perceived risk undermines these positive effects. By integrating mindfulness into the Technology Acceptance Model (TAM), this research extends the theoretical understanding of AI technology acceptance and provides practical insights for media education. The findings highlight that embedding mindfulness training and reducing perceived risks can effectively foster rational acceptance and the innovative application of AI tools, thereby contributing to the cultivation of intelligent media talent.

The acceptance of technology at the higher educational level has been a significant discussion, with little attention on the gender dynamics on the acceptance of artificial intelligence (AI ) tools by senior lecturers. This study delved into a detailed analysis of the gender dynamics in the discussion of technology acceptance mainly AI tools, in foreign language (FL) education. Quantitative study approach was adopted in the process, and survey design was implemented. Data was collected using structured digital questionnaire, based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model. A total of ninety-five (95) male senior lecturers and one hundred and three (103) female senior lecturers participated in the study. Analysis was conducted using relevant statistical measures. The results showed disparities in the attitudes and views of senior lecturers towards artificial intelligence (AI) technologies in the context of FL education, greatly influenced by gender. In relation to usage, male senior lecturers have higher positive reactions (61.06%) in comparison to their female counterparts (46.6%). However, in relation to the assumption that AI technologies improve the performance of learners, 69% of male senior lecturers agree with this notion, but a substantially greater percentage of 72.81% of female senior lecturers hold the same perspective. Moreover, there exists a little disparity in the level of proficiency in using AI technologies across genders. Specifically, 56.84% of male senior lecturers see it as uncomplicated, while 61.16% of their female counterparts share the same sentiment. The gender discrepancy that is most notable pertains to the perceived level of ease in using artificial intelligence (AI) technologies during foreign language (FL) lessons. The data reveals that a majority of male senior lecturers, calculated as 69.48%, see the use of these tools very easy. In contrast, a much higher proportion of female senior lecturers, 86.41%, share the same perception. This discrepancy highlights a notable disparity in confidence levels between the two genders. These results together emphasise the changing gender dynamics in the acceptance of technology, interrogating conventional assumptions and underscoring the need for customised support systems to guarantee fair and efficient integration of artificial intelligence (AI) technologies in foreign language instruction among senior lecturers.

Background: The integration of Artificial Intelligence(AI) in dental care presents numerous benefits. However, fostering a proactive attitude is essential to ensure that these advancements lead to positive developments within dental practices. This study primarily focuses on examining the acceptance of AI technologies among dental professionals. Objective: The present study aims to explore the perceptions and acceptance of dentists towards the integration of AI in dentistry through Technology Acceptance Model (TAM) as a theoretical framework. Methods: By adopting descriptive research design, the study involved systematic collection of primary data from dental professionals to gain insights into their perceptions, attitudes, and acceptance of AI technologies in their professional environment. Using judgmental sampling, the researcher selected participants with first-hand experience relevant to the study’s topic. Consequently, a sample of 200 dental professionals who are actively using or planning to use AI technologies have been considered as prospective respondents. Results: The findings of the study reveal that dental professionals are aware about the usage of AI in dentistry and AI implementation is most notable in Orthodontics at 34%, followed by a significant use in Endodontics and Prosthodontics at 18.5% and 17.5% respectively. The results based on Structural Equation Modelling (SEM) indicate that the variable “perceived ease of use” positively influences dental professionals' attitudes towards its use in dentistry. Furthermore, the positive attitude has significantly influenced their behavioural intention to use, which in turn positively affected the actual usage of AI in dental practices. Conclusion: Though the overall impact of AI in dentistry is largely positive, it is notable that perceived usefulness did not significantly influence dentists' attitudes. This discrepancy indicates that the majority of dentists are aware of the benefits of integrating AI in dentistry, conflicting with expectations, the variable perceived usefulness did not have a significant impact on the attitudes of dental professionals towards AI. Keywords: artificial intelligence; dentistry; diagnostics; technology acceptance model (TAM)

Masters or Slaves? AI and the Future of Humanity

In this digital environment, Artificial Intelligence describes the technology that is considered to have changed the global economy the most. It is estimated that by 2030, AI will contribute approximately $15.7 trillion to the global economy due to its steady expansion in scope, application, and environmental protection. Achieving sustainable development goals depends on sustainable customer loyalty, as it significantly impacts the circular economy and social responsibility. The research aims to examine satisfaction as a mediator to understand how the modified Artificial Intelligence (AI) technology acceptance dimensions relate to customer loyalty in digital banking services. This study collected valid responses from 380 respondents through a cross-sectional survey in Hyderabad, India. A measurement model, developed using a survey questionnaire and partial least squares path modeling, was used to verify the measured items, test hypotheses, and evaluate the correlations among various constructs. Regarding digital banking services, satisfaction fully mediates the relationship between the modified AI Technology Acceptance Model (TAM) factors, perceived usefulness, perceived ease of use, perceived risk, perceived trust, and perceived benefit and customer loyalty. However, the results indicate that AI acceptance factors and customer loyalty are partly mediated by satisfaction. The relationship between AI acceptance factors, customer loyalty, and satisfaction is not moderated by gender. Conversely, age acts as a mediating factor in the relationship between satisfaction, loyalty, and AI acceptance factors. According to the study's findings, deploying AI technology in sustainable financial services is essential for providing clients with positive experiences, which influence customer satisfaction and loyalty, thereby attracting customers to use these services. The study demonstrates how marketing managers can leverage modified AI acceptance factors to promote digital banking services and foster favorable customer loyalty.

This study examines in depth the factors influencing the sustainable intention to use Artificial Intelligence (AI) technology among professionals in Indonesia. By integrating the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), this study aims to identify and analyze the key determinants driving the continued use of AI in the workplace. Using a quantitative approach, data were collected through an online survey involving 113 respondents actively using AI across various industry sectors and analyzed using structural equation modeling (SEM). The results indicate that perceived usefulness, perceived ease of use, and subjective norms have a significant positive effect on the intention to continue using AI. Notably, perceived usefulness emerged as the strongest predictor, highlighting the critical role of AI's practical value in encouraging sustained use. In addition, perceived behavioral control significantly influences sustainable intention, underscoring the importance of organizational support and skill development in facilitating long-term AI adoption. These findings contribute to the theoretical development of technology acceptance in professional settings and offer practical insights for organizations aiming to enhance AI integration strategies.

The rapid development of digital technology and artificial intelligence (AI) has brought significant changes in many areas of life, including business, healthcare, education, and entertainment. The great potential of AI technologies to provide positive benefits to society is balanced with concerns about their negative impact on quality of life. This study aims to explore the influence of digital AI technology on the overall quality of life around the world, focusing on the Performance Expectancy, Effort Expectancy, and Use Behavior aspects of digital AI technology. This research method utilizes the UTAUT (Unified Theory of Acceptance and Use of Technology) approach and collects data quantitatively through a questionnaire covering 3 variables related to digital AI technology and its influence on quality of life. Data analysis was conducted using PLS-SEM (Partial Least Squares - Structural Equation Modeling) to identify important aspects related to the advantages and disadvantages of AI technology. The results from the 70 respondents indicated that digital AI technologies have the potential to improve quality of life by meeting performance expectations and providing ease of use, and a balanced approach is needed in the development and implementation of AI technologies to maximize their positive impact while minimizing their negative impact.

Skin cancers, including melanoma and keratinocyte cancers, are among the most common cancers worldwide, and their incidence is rising in most populations. Earlier detection of skin cancer leads to better outcomes for patients. Artificial intelligence (AI) technologies have been applied to skin cancer diagnosis, but many technologies lack clinical evidence and/or the appropriate regulatory approvals. There are few qualitative studies examining the views of relevant stakeholders or evidence about the implementation and positioning of AI technologies in the skin cancer diagnostic pathway. This study aimed to understand the views of several stakeholder groups on the use of AI technologies to facilitate the early diagnosis of skin cancer, including patients, members of the public, general practitioners, primary care nurse practitioners, dermatologists, and AI researchers. This was a qualitative, semistructured interview study with 29 stakeholders. Participants were purposively sampled based on age, sex, and geographical location. We conducted the interviews via Zoom between September 2022 and May 2023. Transcribed recordings were analyzed using thematic framework analysis. The framework for the Nonadoption, Abandonment, and Challenges to Scale-Up, Spread, and Sustainability was used to guide the analysis to help understand the complexity of implementing diagnostic technologies in clinical settings. Major themes were "the position of AI in the skin cancer diagnostic pathway" and "the aim of the AI technology"; cross-cutting themes included trust, usability and acceptability, generalizability, evaluation and regulation, implementation, and long-term use. There was no clear consensus on where AI should be placed along the skin cancer diagnostic pathway, but most participants saw the technology in the hands of either patients or primary care practitioners. Participants were concerned about the quality of the data used to develop and test AI technologies and the impact this could have on their accuracy in clinical use with patients from a range of demographics and the risk of missing skin cancers. Ease of use and not increasing the workload of already strained health care services were important considerations for participants. Health care professionals and AI researchers reported a lack of established methods of evaluating and regulating AI technologies. This study is one of the first to examine the views of a wide range of stakeholders on the use of AI technologies to facilitate early diagnosis of skin cancer. The optimal approach and position in the diagnostic pathway for these technologies have not yet been determined. AI technologies need to be developed and implemented carefully and thoughtfully, with attention paid to the quality and representativeness of the data used for development, to achieve their potential.

The use of artificial intelligence (AI) technology in the beauty industry continues to increase as a means of helping consumers in product choices. The research aims to test the influence of perceived ease of use, perceved usefulness and subjective norms on the intention to use AI technology on the selection of beauty products. Young adult women became the subject focus on this study as the most targeted market based of the beauty industry. A total of 105 respondents were sampled in quantitative research using purposive sampling method. Data processing by Smart-PLS applications results in the perceptual ease of use, perceived usefulness and subjective norms having a significant influence on the intention to use AI technology. On the other hand, subjective norms do not influence perceived usefulness. Keywords: artificial intelligence; perceived ease of use, perceived usefulness, subjective norm

Purpose This paper aims to explore the factors influencing auditors’ willingness to learn and use artificial intelligence (AI) technologies in auditing. This study extended the Unified Theory of Acceptance and Use of Technology by incorporating the willingness to learn as a key factor for AI adoption in auditing. Design/methodology/approach Data were collected through validated questionnaires form 150 auditors selected via simple random sampling from a population of 300 statutory auditors. Partial least squares structural equation modeling was used to analyze the relationships between variables. Findings This study finds that performance expectancy and effort expectancy significantly and positively influence auditors’ willingness to learn AI technologies. However, social influence does not significantly impact their willingness. A positive relationship is observed between willingness to learn and the actual use of AI in auditing process. Practical implications The findings suggest the need for government, professional associations and universities seeking to develop AI-focused training programs and incorporate AI into curricula, ensuring accounting students are equipped to meet future demands. Originality/value This study contributes new insights into the factors influencing auditors’ willingness to adopt AI technologies, focusing on Jordanian auditors and addressing the gap in literature related to AI adoption in auditing within developing economies.