AI tools and hotel innovation outcomes: The mediating role of data-driven culture

during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (see The Effect of Open Access).

Background ChatGPT is an open-source large language model that uses deep learning techniques to generate human-like texts. ChatGPT has the potential to revolutionize medical education as it acts as an interactive virtual tutor and personalized learning assistant. We assessed the use of ChatGPT and other Artificial Intelligence (AI) tools among medical faculty in Uganda. Methods We conducted a descriptive cross-sectional study among medical faculty at four public universities in Uganda from November to December 2023. Participants were recruited consecutively. We used a semi-structured questionnaire to collect data on participants’ socio-demographics and the use of AI tools such as ChatGPT. Our outcome variable was the use of ChatGPT and other AI tools. Data were analyzed in Stata version 17.0. Results We recruited 224 medical faculty, majority [75% (167/224)] were male. The median age (interquartile range) was 41 years (34–50). Almost all medical faculty [90% (202/224)] had ever heard of AI tools such as ChatGPT. Over 63% (120/224) of faculty had ever used AI tools. The most commonly used AI tools were ChatGPT (56.3%) and Quill Bot (7.1%). Fifty-six faculty use AI tools for research writing, 37 for summarizing information, 28 for proofreading work, and 28 for setting exams or assignments. Forty faculty use AI tools for non-academic purposes like recreation and learning new skills. Faculty older than 50 years were 40% less likely to use AI tools compared to those aged 24 to 35 years (Adjusted Prevalence Ratio (aPR):0.60; 95% Confidence Interval (CI): [0.45, 0.80]). Conclusion The use of ChatGPT and other AI tools was high among medical faculty in Uganda. Older faculty (>50 years) were less likely to use AI tools compared to younger faculty. Training on AI use in education, formal policies, and guidelines are needed to adequately prepare medical faculty for the integration of AI in medical education.

Background ChatGPT is a large language model that uses deep learning techniques to generate human-like texts. ChatGPT has the potential to revolutionize medical education as it acts as an interactive virtual tutor and personalized learning assistant. We assessed the use of ChatGPT and other Artificial Intelligence (AI) tools among medical faculty in Uganda. Methods We conducted a descriptive cross-sectional study among medical faculty at four public universities in Uganda from November to December 2023. Participants were recruited consecutively. We used a semi-structured questionnaire to collect data on participants’ socio-demographics and the use of AI tools such as ChatGPT. Our outcome variable was the use of ChatGPT and other AI tools. Data were analyzed in Stata version 17.0. Results We recruited 224 medical faculty, majority [75% (167/224)] were male. The median age (interquartile range) was 41 years (34–50). Almost all medical faculty [90% (202/224)] had ever heard of AI tools such as ChatGPT. Over 63% (120/224) of faculty had ever used AI tools. The most commonly used AI tools were ChatGPT (56.3%) and Quill Bot (7.1%). Fifty-six faculty use AI tools for research writing, 37 for summarizing information, 28 for proofreading work, and 28 for setting exams or assignments. Forty faculty use AI tools for non-academic purposes like recreation and learning new skills. Faculty older than 50 years were 40% less likely to use AI tools compared to those aged 24 to 35 years (Adjusted Prevalence Ratio (aPR):0.60; 95% Confidence Interval (CI): [0.45, 0.80]). Conclusion The use of ChatGPT and other AI tools was high among medical faculty in Uganda. Older faculty (>50 years) were less likely to use AI tools compared to younger faculty. Training on AI use in education, formal policies, and guidelines are needed to adequately prepare medical faculty for the integration of AI in medical education.

ChatGPT is a large language model that uses deep learning techniques to generate human-like texts. ChatGPT has the potential to revolutionize medical education as it acts as an interactive virtual tutor and personalized learning assistant. We assessed the use of ChatGPT and other Artificial Intelligence (AI) tools among medical faculty in Uganda. We conducted a descriptive cross-sectional study among medical faculty at four public universities in Uganda from November to December 2023. Participants were recruited consecutively. We used a semi-structured questionnaire to collect data on participants' socio-demographics and the use of AI tools such as ChatGPT. Our outcome variable was the use of ChatGPT and other AI tools. Data were analyzed in Stata version 17.0. We recruited 224 medical faculty, majority [75% (167/224)] were male. The median age (interquartile range) was 41 years (34-50). Almost all medical faculty [90% (202/224)] had ever heard of AI tools such as ChatGPT. Over 63% (120/224) of faculty had ever used AI tools. The most commonly used AI tools were ChatGPT (56.3%) and Quill Bot (7.1%). Fifty-six faculty use AI tools for research writing, 37 for summarizing information, 28 for proofreading work, and 28 for setting exams or assignments. Forty faculty use AI tools for non-academic purposes like recreation and learning new skills. Faculty older than 50 years were 40% less likely to use AI tools compared to those aged 24 to 35 years (Adjusted Prevalence Ratio (aPR):0.60; 95% Confidence Interval (CI): [0.45, 0.80]). The use of ChatGPT and other AI tools was high among medical faculty in Uganda. Older faculty (>50 years) were less likely to use AI tools compared to younger faculty. Training on AI use in education, formal policies, and guidelines are needed to adequately prepare medical faculty for the integration of AI in medical education.

Systematic literature reviews (SLRs) are essential for synthesising research evidence and guiding informed decision-making. However, SLRs require significant resources and substantial efforts in terms of workload. The introduction of artificial intelligence (AI) tools can reduce this workload. This study aims to investigate the preferences in SLR screening, focusing on trade-offs related to tool attributes. A discrete choice experiment (DCE) was performed in which participants completed 13 or 14 choice tasks featuring AI tools with varying attributes. Data were collected via an online survey, where participants provided background on their education and experience. Professionals who have published SLRs registered on Pubmed, or who were affiliated with a recent Health Economics and Outcomes Research conference were included as participants. The use of a hypothetical AI tool in SLRs with different attributes was considered by the participants. Key attributes for AI tools were identified through a literature review and expert consultations. These attributes included the AI tool's role in screening, required user proficiency, sensitivity, workload reduction and the investment needed for training. The participants' adoption of the AI tool, that is, the likelihood of preferring the AI tool in the choice experiment, considering different configurations of attribute levels, as captured through the DCE choice tasks. Statistical analysis was performed using conditional multinomial logit. An additional analysis was performed by including the demographic characteristics (such as education, experience with SLR publication and familiarity with AI) as interaction variables. The study received responses from 187 participants with diverse experience in performing SLRs and AI use. The familiarity with AI was generally low, with 55.6% of participants being (very) unfamiliar with AI. In contrast, intermediate proficiency in AI tools is positively associated with adoption (p=0.030). Similarly, workload reduction is also strongly linked to adoption (p<0.001). Interestingly, if expert proficiency is needed for the AI, authors with more scientific experience in their profession are less likely to adopt AI (p=0.009). However, more experience specifically with SLR publications increases AI adoption likelihood (p=0.001). The findings suggest that workload reduction is not the only consideration for SLR reviewers when using AI tools. The key to AI adoption in SLRs is creating reliable, workload-reducing tools that assist rather than replace human reviewers, with moderate proficiency requirements and high sensitivity.

Higher education institutions throughout the world are challenged by the influx of Artificial Intelligence (AI) tools into education. Hence, the awareness and use of AI tools in education among the educators and students in higher education and their perspectives about AI are crucial and essential. This chapter comprised of a study exploring the awareness, use and perspectives on AI among educators and students in some government and private sectors of higher education. An average number of educators and a vast number of students are aware and use emerging AI tools like ChatGPT or a similar application. Educators are divided on the views that AI tools are well known in the University. Students consider that AI tools are an essential tool for undergraduate students' success. Professional discussion on AI tools in education are suggested for educators in higher education and students' insights are important in planning teaching and learning activities

This study investigates the relationship between undergraduates’ technological readiness, self-efficacy, attitude, and usage of artificial intelligence (AI) tools. The study leverages the technology acceptance model (TAM) to explore the relationships among the study’s variables. The study’s participants are 176 undergraduate students from a public university in southwestern Nigeria. The Partial Least Square Structural Equation Modeling (PLS-SEM) was used to analyze the responses from the participants. The questionnaire has six constructs measured on a 5-point Likert scale. The results show that undergraduates’ technological self-efficacy determines their usage of AI tools and perception of AI tools’ ease of use, but this does not determine their perception of the AI tools’ usefulness and attitude towards AI tools usage. Also, technological readiness was found to determine the perception of the AI tools’ usefulness, perception of AI tools’ ease of use, and technological self-efficacy among undergraduates but does not determine their usage of AI tools and attitude towards AI tools usage. In addition, undergraduates’ attitude towards AI tools was considered the primary determinant of the usage of AI tools. It was concluded that some factors determine the adoption of AI tools, which are interrelated. Educators can play a pivotal role in empowering students to harness the power of AI tools by encouraging their usage under well-coordinated guidance rather than imposing outright restrictions. By fostering AI literacy and equipping students with the knowledge and skills to navigate these innovative technologies, educators can instil the confidence and competency needed to integrate AI tools into various academic activities seamlessly.

PurposeThe purpose of the paper is to explore the rapidly evolving landscape of artificial intelligence (AI) tools in academic research, highlighting their potential to transform various stages of the research process. AI tools are transforming academic research, offering numerous benefits and challenges.Design/methodology/approachAcademic research is undergoing a significant transformation with the emergence of (AI) tools. These tools have the potential to revolutionize various aspects of research, from literature review to writing and proofreading. An overview of AI applications in literature review, data analysis, writing and proofreading, discussing their benefits and limitations is given. A comprehensive review of existing literature on AI applications in academic research was conducted, focusing on tools and platforms used in various stages of the research process. AI was used in some of the searches for AI applications in use.FindingsThe analysis reveals that AI tools can enhance research efficiency, accuracy and quality, but also raise important ethical and methodological considerations. AI tools have the potential to significantly enhance academic research, but their adoption requires careful consideration of methodological and ethical implications. The integration of AI tools also raises questions about authorship, accountability and the role of human researchers. The authors conclude by outlining future directions for AI integration in academic research and emphasizing the need for responsible adoption.Originality/valueAs AI continues to evolve, it is essential for researchers, institutions and policymakers to address the ethical and methodological implications of AI adoption, ensuring responsible integration and harnessing the full potential of AI tools to advance academic research. This is the contribution of the paper to knowledge.

Marketing scientists as well as practitioners believe that artificial intelligence (AI) holds the promise of productivity gains for organizations. However, there has been little scientific research into these theories. This study investigates the role of AI in enhancing marketing productivity, deriving insights from a case study conducted with the marketing team of an industrial software start-up. Drawing upon Case Study Analysis by Yin (2018) and Participatory Action Research by Kemmis and McTaggart (2007), the study employs a combination of survey interviews, AI tool research and AI tool testings. Key findings indicate that productivity gains are more likely than productivity impairments with the use of marketing AI tools. This effect is even stronger when knowledge workers possess high levels of AI skills and utilize AI tools with suitable capabilities. Having closely analyzed six marketing disciplines, particularly SEO / content and design demonstrated significant productivity gains including generative AI (GAI) tools the team already subscribed to like ChatGPT 4 and Canva, but also new AI solutions. While an AI tool’s level of integration only showed a weak positive productivity impact, future studies are suggested to further investigate this variable by comparing the effects of less advanced but more accessible tools like generative AI versus highly advanced, but less accessible business AI. Having navigated the vast and dynamic landscape of AI tools, insights further emphasize the importance of AI experience sharing and informed decision-making, implying knowledge of own user rights and always staying updated on AI advancements. Zooming out from process level, the work's literature review further highlights the role of environmental and organizational AI enablers, like budget allocation, fostering AI trust and mindset, but also implementing AI routines and responsibilities. Overall, this research underscores the imperative for companies, especially startups and SMEs, to explore AI technology as a means to enhance productivity and gain a competitive edge.

Performance of an artificial intelligence tool with real-time clinical workflow integration - Detection of intracranial hemorrhage and pulmonary embolism.

The expansion of artificial intelligence (AI) tools has brought about new opportunities and challenges for teachers and students. These tools have the potential to reshape teaching and stimulate both students’ and teachers’ creativity. In 21st-century education, creativity emerges as a key skill that encompasses problem-solving, innovation, adaptability, critical thinking, and cognitive development. AI tools also provide personalized assistance and feedback as well as customized study materials. Moreover, they have proven beneficial in cultivating critical thinking and enhancing students’ research skills. Instead of questioning teachers’ preparedness for AI technologies, the focus should be on discovering ways to effectively and creatively integrate these tools into the classroom. This paper explores the possibilities of implementing generative AI tools to promote students’ creativity, thus enhancing the overall quality of teaching. In the Croatian educational system, similarly to Poland, school pedagogues should encourage positive changes within the school culture. Therefore, this paper also underscores the role of school pedagogues in bridging the gap between teachers and AI tools as an educational innovation. School pedagogues should be instrumental in supporting teachers during the integration of AI tools into their teaching by showcasing practical applications and emphasizing potential benefits for student engagement and learning outcomes. In this capacity, school pedagogues bear the responsibility of fostering a reflective and critical approach towards AI tools, advocating creative yet responsible use of technology in the classroom.

Cross-sectional survey study BACKGROUND: Artificial intelligence (AI) tools are increasingly integrated into various aspects of medicine, including medical research. However, the scope and manner in which early-career surgeons utilize AI tools in their research remain inadequately understood. This study aimed to investigate the frequency and specific applications of AI tools in medical research among early-career surgeons, including their perceptions, concerns, and outlook regarding AI in research. A survey comprising 25 questions was distributed among members of an international club of early-career spine surgeons (<10 years of experience). The survey assessed demographics, AI tool utilization, access to AI training resources, and perceptions of AI benefits and concerns in research. Sixty early-career surgeons participated, with 86.7% reporting AI tool use in their research. ChatGPT was the most frequently utilized tool, with a usage rate of 93.1%. AI tools were primarily used for grammatical proofreading (69.6%) and rephrasing (64.3%), while 26.8% of participants used AI for statistical analysis. While 80.4% perceived improved efficiency as a key benefit, 70.0% expressed concerns about reliability. None of the participants had received formal AI training, and only 15.0% had access to AI mentors. Despite these challenges, 91.6% anticipated a positive long-term impact of AI on research. AI tools are widely adopted among early-career surgeons for various research tasks, extending from text generation to data analysis. However, the absence of formal training and concerns regarding the reliability of AI tools underscore the necessity of training for AI integration in medical research. This study provides timely insights into AI adoption patterns among early-career surgeons, highlighting the urgent need for formal AI training programs to ensure responsible research practices.

This study explores the lived experiences of English as a Foreign Language (EFL) learners engaging with Artificial Intelligence (AI) tools to support their academic writing development. Using a narrative inquiry approach, the research investigates how learners describe their interactions with AI technologies such as ChatGPT and Grammarly, and what challenges and opportunities they perceive. Eighteen university-level EFL students participated in in-depth interviews, revealing that AI tools are widely appreciated for enhancing linguistic accuracy, improving efficiency, boosting writing confidence, and supporting idea generation. These benefits align with the Technology Acceptance Model and Sociocultural Theory, suggesting that AI acts as both a facilitator of ease and a scaffold within learners’ Zones of Proximal Development. However, the findings also highlight substantial concerns related to academic integrity, over-reliance, and AI’s limitations in generating culturally nuanced or critically engaging content. This duality reflects the "Paradox of Assistance," where the same features that make AI valuable can also inhibit deeper learning if uncritically used. The study emphasizes the need for intentional, pedagogically guided integration of AI in EFL writing instruction, promoting a balanced Human-AI collaboration that empowers learners as autonomous and reflective writers.

Background Histological remission is an important target for Ulcerative Colitis (UC) treatment; however, scoring of histological images is time-consuming and prone to inter and intra-observer variability. Thus, a need exists for an accurate, reproducible, and reliable automated method. Previously, we demonstrated an Artificial Intelligence (AI) Tool using image processing and machine learning algorithms to measure histological disease activity using the Nancy index consistently and accurately.1 Here, we aim to enhance the capabilities of the AI Tool, by adding substantially more population-diversified training data while maintaining accuracy and robustness of results. Methods Eight global sites submitted 600 UC histological images. These were added to the 200 images previously used to train and validate the AI Tool. The 800-image dataset was divided into 2 groups: 90% used for training, 10% for testing. The novel AI algorithms were trained using state-of-the-art image processing and machine learning techniques based on deep learning and feature extraction. Cell and tissue regions of each training image were manually annotated, measured, and assigned a Nancy Index independently by 3 histopathologists, and used to further train the AI using over 43,000 characterisations. The AI Tool fully characterises histological images, identifying tissue types, cell types, cell numbers and locations, and automatically measures the Nancy Index for each image. Intra Class Correlation (ICC) and Confusion Matrix analyses were performed to evaluate the AI Tool and assess accuracy. Results The average ICC was 92.1% among the histopathologists and 91.1% between histopathologists and AI Tool, compared with 88.3% and 87.2% in the previous study.1 Confusion matrix analysis (Table 1) demonstrated the strongest correlation at the extremes of the Nancy Index, with 80% correlation between predicted and true labels for Nancy Scores of 0 or 4. When 2 adjacent scores were combined, correlations were stronger: 96% for a true Nancy score of 0 being predicted as 0 or 1, and 100% for a true Nancy score of 2 being predicted as 2 or 3. Conclusion By adding a larger number of images to the AI Tool training data, the robustness of the AI Tool was substantially improved while maintaining accuracy. The continued high correlation of AI Tool performance with the histopathologists reinforces the potential role for the AI Tool for IBD clinical applications. Fully characterising whole slides could standardise and validate an AI-driven scoring system for histology slides in IBD, eliminating the subjectivity of the human pathologist in assessment of disease activity.

The integration of new technologies in professional contexts has emerged as a critical determinant of organizational efficiency and competitiveness. In this regard, the application of Artificial Intelligence (AI) in recruitment processes facilitates faster and more accurate decision-making by processing large volumes of data, minimizing human bias, and offering personalized recommendations to enhance talent development and candidate selection. The Technology Acceptance Model (TAM) provides a valuable framework for understanding recruiters’ perceptions of innovative technologies, such as AI tools and GenAI. Drawing on the TAM, a model was developed to explain the intention to use AI tools, proposing that perceived ease of use and perceived usefulness influence attitudes toward AI, which subsequently affect the intention to use AI tools in recruitment and selection processes. Two studies were conducted in Portugal to address this research objective. The first was a qualitative exploratory study involving 100 interviews with recruiters who regularly utilize AI tools in their professional activities. The second study employed a quantitative confirmatory approach, utilizing an online questionnaire completed by 355 recruiters. The qualitative findings underscored the transformative role of AI in recruitment, emphasizing its potential to enhance efficiency and optimize resource management. However, recruiters also highlighted concerns regarding the potential loss of personal interaction and the need to adapt roles within this domain. The results also supported the indirect effect of perceived ease of use and perceived usefulness on the use of AI tools in recruitment and selection processes via positive attitudes toward the use of these tools. This suggests that AI is best positioned as a complementary tool rather than a replacement for human decision-making. The insights gathered from recruiters’ perspectives provide actionable recommendations for organizations seeking to leverage AI in recruitment processes. Specifically, the findings show the importance of ethical considerations and maintaining human involvement to ensure a balanced and effective integration of AI tools.