Artificial Intelligence Chatbot Perception and Use Across Campus

Purpose This study aims to investigate the key factors influencing students’ adoption of artificial intelligence (AI) chatbot applications in higher education. It further examines the mediating and moderating role of AI chatbots and tech readiness in determining the effect of perceived usefulness, subjective norms, tech simplicity and tech literacy on the intention to use AI chatbot applications. Design/methodology/approach A survey was conducted at Malaysian universities whereby 430 students participated and 426 responses were deemed valid for analysis. The data was carefully examined to ensure the accuracy of the proposed model. To comprehend the intricate relationships in the model, the authors used the partial least squares structural equation modeling (PLS-SEM) technique. Findings The results revealed that perceived usefulness (PU), subjective norm (SN), tech literacy (TL) and tech simplicity (TS) have a significant impact on students’ intention to use AI applications. The intention to use AI chatbot applications significantly influences the adoption of AI chatbots in higher education. The findings indicated that the intention to use AI chatbots mediates the effect of PU, SN, TL and TS on the adoption of AI chatbots. Tech readiness (TR) moderates the effect of PU and TS on the intention to use AI chatbot applications. Originality/value This research addresses a new insight into AI chatbot adoption within higher education, particularly demonstrating how AI chatbots and tech readiness act as mediators and moderators in shaping students’ perceptions and adoption of AI chatbot applications.

IntroductionThis study explores the effects of Artificial Intelligence (AI) chatbots, with a particular focus on OpenAI’s ChatGPT, on Higher Education Institutions (HEIs). With the rapid advancement of AI, understanding its implications in the educational sector becomes paramount.MethodsUtilizing databases like PubMed, IEEE Xplore, and Google Scholar, we systematically searched for literature on AI chatbots’ impact on HEIs. Our criteria prioritized peer-reviewed articles, prominent media outlets, and English publications, excluding tangential AI chatbot mentions. After selection, data extraction focused on authors, study design, and primary findings. The analysis combined descriptive and thematic approaches, emphasizing patterns and applications of AI chatbots in HEIs.ResultsThe literature review revealed diverse perspectives on ChatGPT’s potential in education. Notable benefits include research support, automated grading, and enhanced human-computer interaction. However, concerns such as online testing security, plagiarism, and broader societal and economic impacts like job displacement, the digital literacy gap, and AI-induced anxiety were identified. The study also underscored the transformative architecture of ChatGPT and its versatile applications in the educational sector. Furthermore, potential advantages like streamlined enrollment, improved student services, teaching enhancements, research aid, and increased student retention were highlighted. Conversely, risks such as privacy breaches, misuse, bias, misinformation, decreased human interaction, and accessibility issues were identified.DiscussionWhile AI’s global expansion is undeniable, there is a pressing need for balanced regulation in its application within HEIs. Faculty members are encouraged to utilize AI tools like ChatGPT proactively and ethically to mitigate risks, especially academic fraud. Despite the study’s limitations, including an incomplete representation of AI’s overall effect on education and the absence of concrete integration guidelines, it is evident that AI technologies like ChatGPT present both significant benefits and risks. The study advocates for a thoughtful and responsible integration of such technologies within HEIs.

Artificial Intelligence (AI) chatbots have emerged as tools with the potential to enrich the learning experience. This research aims to analyze the perceptions of professors and students regarding the utilization of AI chatbots in the context of higher education. The primary objective of this study is to comprehend how teachers and students view the use of AI chatbots in higher education. This research adopts a qualitative approach employing semi-structured interviews and content analysis of relevant written documents. Data are collected and analyzed using descriptive statistics. The findings of this research reveal that most respondents, both professors and students, hold a positive attitude toward using AI chatbots in higher education. The critical benefits acknowledged include accessibility, assistance answering questions, and enhanced learning efficiency. Some challenges related to data security and the quality of interaction with chatbots are also identified. This research demonstrates that AI chatbots have significant potential to enhance the learning experience in higher education. However, attention must be given to existing technical challenges and privacy concerns to ensure broader acceptance. This study provides valuable insights into the perceptions of professors and students regarding AI chatbots, which can serve as a guide for educational institutions in developing effective implementation strategies. Furthermore, these results may stimulate further research into the use of AI technology in higher education.

BackgroundMalaysia, an upper middle-income country in the Asia-Pacific region, has an HIV epidemic that has transitioned from needle sharing to sexual transmission, mainly in men who have sex with men (MSM). MSM are the most vulnerable population for HIV in Malaysia. In 2022, our team developed a web-based artificial intelligence (AI) chatbot and tested its feasibility and acceptability among MSM in Malaysia to promote HIV testing. To enhance the usability of the AI chatbot, we made it accessible to the public through the website called MYHIV365 and tested it in an observational study.ObjectiveThis study aimed to test the usability of an AI chatbot in promoting HIV testing among MSM living in Malaysia.MethodsThis observational study was conducted from August 2023 to March 2024 among 334 MSM. Participants were recruited through community outreach and social-networking apps using flyers. The interactions between participants and the AI chatbot were documented and retrieved from the chatbot developer’s platform. Data were analyzed following a predefined metrics using R software (Posit Software, PBC).ResultsThe AI chatbot interacted with 334 participants, assisting them in receiving free HIV self-testing kits, offering information on HIV, pre-exposure prophylaxis (PrEP), and mental health, and providing details of 220 MSM-friendly clinics, including their addresses, phone numbers, and operating hours. After the study, 393 human-chatbot interactions were documented on the chatbot developer’s platform. Most participants (304/334, 91.0%) interacted with the AI chatbot once, 30 (9.0%) engaged 2 or more times at different intervals. Participants’ interaction time with the chatbot varied, ranging from 1 to 31 minutes. The AI chatbot properly addressed most participants’ questions (362/393, 92.1%) about HIV and PrEP. However, in 31 interactions, participants posed additional questions to the chatbot that were not programmed into the chatbot algorithms, resulting in unanswered interactions.ConclusionsThe web-based AI chatbot demonstrated high usability in delivering HIV self-testing kits and providing clinical information on HIV testing, PrEP, and mental health services. To enhance its usability in community and clinical settings, the chatbot must offer personalized health information and precise interaction, powered by sophisticated machine learning algorithms. In addition, establishing an effective connection between the AI chatbot and health care systems to eliminate stigma and discrimination toward MSM is crucial for the future implementation of AI chatbots.

How Well Do Artificial Intelligence Chatbots Respond to the Top Search Queries About Urological Malignancies?

The adoption of artificial intelligence (AI) chatbots in higher education promises improved student support and administrative efficiency. Our objective is to offer insights to institutions in effectively adopting AI chatbots, tailored to the needs of both students and faculty. Using secondary survey data from United States higher education, we conducted a moderated mediation analysis to examine the mediation effect of perceived resources/support on the relationship between user role and perceived efficiency of AI chatbots, moderated by technological tool usage. The results revealed that perceived resources/support availability plays a mediating role in shaping how both students and faculty perceive the efficiency of AI chatbots, with students reporting greater efficiency when resources and support are more readily available. This mediation effect becomes marginally stronger as the usage of technological tools increases. While both student and faculty groups demonstrate openness to using AI chatbots, their perceptions of benefits and challenges towards AI chatbots differ significantly.

This editorial discusses the role of artificial intelligence (AI) chatbots in the healthcare sector, emphasizing their potential as supplements rather than substitutes for medical professionals. While AI chatbots have demonstrated significant potential in managing routine tasks, processing vast amounts of data, and aiding in patient education, they still lack the empathy, intuition, and experience intrinsic to human healthcare providers. Furthermore, the deployment of AI in medicine brings forth ethical and legal considerations that require robust regulatory measures. As we move towards the future, the editorial underscores the importance of a collaborative model, wherein AI chatbots and medical professionals work together to optimize patient outcomes. Despite the potential for AI advancements, the likelihood of chatbots completely replacing medical professionals remains low, as the complexity of healthcare necessitates human involvement. The ultimate aim should be to use technology like AI chatbots to enhance patient care and outcomes, not to replace the irreplaceable human elements of healthcare.

PurposeThis study aims to explore the antecedent factors affecting consumers’ intention to continue using artificial intelligence (AI) chatbots in pharmaceutical e-commerce. This study aims to provide a comprehensive understanding of how technical characteristics and user satisfaction influence continuance intention, offering insights for enhancing AI chatbot systems and customer service strategies.Design/methodology/approachThis study adopts both online and offline data collection methods and uses structural equation modelling with AMOS 26.0 to investigate the factors influencing consumers’ continuance intention to use AI chatbots in the pharmaceutical e-commerce context. The research model integrates technical characteristics of AI chatbots, service expectation confirmation, emotional satisfaction, cognitive satisfaction and e-health literacy.FindingsThe results of this study indicate that perceived flexibility, accuracy, reliability and convenience of AI chatbots positively influence service expectation confirmation, while anthropomorphism does not have a significant impact. Both emotional and cognitive satisfaction positively influence consumers’ continuance intention. This study highlights the importance of optimizing AI chatbot systems to improve service efficiency and consumer satisfaction.Originality/valueThis study uniquely integrates the pharmaceutical e-commerce context into AI chatbots research, addressing an existing gap in context-specific studies. This study introduces a dual-dimensional satisfaction framework encompassing cognitive and emotional satisfaction, offering theoretical support for more holistic satisfaction enhancement strategies. The findings of this study also provide practical implications for companies seeking to establish and sustain long-term, stable customer relationships through advanced AI chatbot systems.

Background: The use of artificial intelligence (AI) chatbot can be fundamental to supporting the establishment and maintenance of smart digital government for Society 5.0 across all national government departments in South Africa. In this way, the AI chatbot can ensure that government services are incorporated and provide quality services to smart citizens. As such, smart citizens can use an AI chatbot to access government services, regardless of the place and time. Objectives: The purpose of this study is to investigate the use of an AI chatbot to establish smart digital government for Society 5.0. Method: This qualitative study adopts content analysis as its research methodology, which is grounded in a literature review that integrates insights from the researchers’ experiences with the use of an AI chatbot to support smart digital government in Society 5.0. Results: The findings of the study reveal that an AI chatbot has the potential to provide government information and services around the clock, regardless of where they are and the time they want to access these services. This can allow citizens to access and retrieve government services timeously. Through an AI chatbot, citizens can access and retrieve information and services from various government databases and websites, promptly. Conclusion: This study provides a framework to map how an AI chatbot can be utilised to support smart digital government for Society 5.0. Contribution: The framework of this study would help the government including national government departments to integrate an AI chatbot in their databases, to ensure that smart digital services are provided to citizens.

Purpose This study aims to explore global entrepreneurship through the lens of artificial intelligence (AI) chatbots as text-generation tools and human entrepreneurs to examine the motivations, challenges and opportunities faced by entrepreneurs across four income levels (as defined by the World Bank’s Gross National Income per capita classification). Later, it compares the results of both outcomes and identifies potential patterns and variations. Design/methodology/approach This study uses AI chatbots as analytical tools to identify themes in global entrepreneurship, using them to analyze existing literature on motivations, challenges and opportunities across income levels. It involves (n = 5) AI chatbots – ChatGPT, Microsoft Copilot, Google Gemini, ChatSonic and Quora Poe – as text generation tools. To verify the AI-generated insights, human participants (n = 20) from diverse economies (5 per income level) were interviewed. Data analysis combines AI-driven thematic coding (ATLAS.ti) with human validation, addressing model biases and limitations such as outdated training data, to provide a comprehensive, accurate view of global entrepreneurship. Findings The study reveals key differences and commonalities in entrepreneurial motivations, challenges and opportunities across income levels. AI chatbots effectively identified broad trends (opportunity versus necessity and market gaps), but human entrepreneurs highlighted context-specific nuances, including the importance of community-driven motivations and cultural preservation in low- and middle-income settings and sustainability concerns, innovation and ethical value creation in high-income economies. The research demonstrates the potential of AI for initial exploratory analysis while emphasizing the necessity of human validation to ensure accuracy and depth (AI–human data hybridization). This approach offers a novel framework for future inquiry in international entrepreneurship. Originality/value This study is a unique, bold and brave attempt to use AI chatbots as an exploratory method validated by human intervention to understand the motivations, opportunities and challenges of entrepreneurs across income levels. It challenges traditional models, emphasizing the importance of contextual richness, social impact and purpose-driven innovation in entrepreneurship research and practice.

This chapter examines the critical role of artificial intelligence (AI) chatbots in luxury fashion retail, focussing on how these technologies are transforming the customer experience by offering personalised, real-time interactions that could potentially replicate in-store experiences. The importance of this issue lies in the unique challenges luxury brands face in integrating technology without losing their core values of exclusivity and emotional engagement. As the luxury market increasingly shifts to online platforms, AI chatbots have become essential tools for maintaining high-touch, personalised customer interactions, but the body of research on this subject, especially in a luxury context, remains limited. The chapter underscores the need for further exploration into how AI chatbots can deepen emotional engagement, adapt to diverse cultural contexts, and address growing concerns around sustainability and ethical AI in terms of privacy. By synthesising existing literature, this chapter emphasises the urgency for luxury brands to innovate through AI while preserving their heritage, ultimately suggesting that AI chatbots can bridge the gap between digital efficiency and the emotional resonance required in luxury brand experience. Followed by a proposed future research agenda, this chapter makes a valuable foundation for academics and practitioners seeking to navigate the complexities of digital transformation in the luxury sector.

Artificial intelligence (AI) chatbots like ChatGPT and Google Bard are computer programs that use AI and natural language processing to understand customer questions and generate natural, fluid, dialogue-like responses to their inputs. ChatGPT, an AI chatbot created by OpenAI, has rapidly become a widely used tool on the internet. AI chatbots have the potential to improve patient care and public health. However, they are trained on massive amounts of people’s data, which may include sensitive patient data and business information. The increased use of chatbots introduces data security issues, which should be handled yet remain understudied. This paper aims to identify the most important security problems of AI chatbots and propose guidelines for protecting sensitive health information. It explores the impact of using ChatGPT in health care. It also identifies the principal security risks of ChatGPT and suggests key considerations for security risk mitigation. It concludes by discussing the policy implications of using AI chatbots in health care.

Artificial intelligence (AI) chatbots have gained popularity as a source of information that is easily accessed by patients. The best treatment of acute Achilles tendon ruptures (AATR) remains controversial due to varying surgical repair techniques, postoperative protocols, nonoperative treatment options, and surgeon and patient factors. Given that patients will continue to turn towards AI for answers to medical questions, the purpose of this study is to evaluate whether popular AI engines can provide adequate responses to frequently asked questions regarding AATR. Three AI engines (ChatGPT, Google Gemini, and Microsoft Copilot) were prompted for a concise response to ten common questions regarding AATR management. Four board-certified orthopaedic surgeons were asked to assess the responses using a four-point scale. A Kruskal-Wallis test was used to compare the responses between the three AI systems using the scores assigned by the surgeons. All three engines provided comparable answers to 7 of 10 questions (70%). Significant differences were noted between the AI systems for three of the ten questions (Question 4, overall p = .027; Question 7, overall p = .043; and Question 10, overall p = .033). post-hoc analyses revealed that Copilot received significantly poorer scores (higher mean ratings) compared to Gemini for Question 4 (adjusted p = .028) and Question 7 (adjusted p = .036), and poorer score compared to ChatGPT for Question 10 (adjusted p = .033). AI chatbots can appropriately answer concise prompts about diagnosis and management of AATR. The responses provided by the three AI chatbots analyzed in our study were largely uniform and satisfactory, with only one of the engines scoring lower on three of the ten questions. As AI engines advance, they will become an important tool for patient education in orthopaedics.

Type 2 diabetes is a significant global health concern. It often causes diabetic foot ulcers (DFUs), which affect millions of people and increase amputation and mortality rates. Despite existing guidelines, the complexity of DFU treatment makes clinical decisions challenging. Large language models such as chat generative pretrained transformer (ChatGPT), which are adept at natural language processing, have emerged as valuable resources in the medical field. However, concerns about the accuracy and reliability of the information they provide remain. We aimed to assess the accuracy of various artificial intelligence (AI) chatbots, including ChatGPT, in providing information on DFUs based on established guidelines. Seven AI chatbots were asked clinical questions (CQs) based on the DFU guidelines. Their responses were analyzed for accuracy in terms of answers to CQs, grade of recommendation, level of evidence, and agreement with the reference, including verification of the authenticity of the references provided by the chatbots. The AI chatbots showed a mean accuracy of 91.2% in answers to CQs, with discrepancies noted in grade of recommendation and level of evidence. Claude-2 outperformed other chatbots in the number of verified references (99.6%), whereas ChatGPT had the lowest rate of reference authenticity (66.3%). This study highlights the potential of AI chatbots as tools for disseminating medical information and demonstrates their high degree of accuracy in answering CQs related to DFUs. However, the variability in the accuracy of these chatbots and problems like AI hallucinations necessitate cautious use and further optimization for medical applications. This study underscores the evolving role of AI in healthcare and the importance of refining these technologies for effective use in clinical decision-making and patient education.

PurposeThe purpose of this study is twofold: first, to identify the categories of artificial intelligence (AI) chatbot service failures in frontline, and second, to examine the effect of the intensity of AI emotion exhibited on the effectiveness of the chatbots’ autonomous service recovery process.Design/methodology/approachWe adopt a mixed-methods research approach, starting with a qualitative research, the purpose of which is to identify specific categories of AI chatbot service failures. In the second stage, we conduct experiments to investigate the impact of AI chatbot service failures on consumers’ psychological perceptions, with a focus on the moderating influence of chatbot’s emotional expression. This sequential approach enabled us to incorporate both qualitative and quantitative aspects for a comprehensive research perspective.FindingsThe results suggest that, from the analysis of interview data, AI chatbot service failures mainly include four categories: failure to understand, failure to personalize, lack of competence, and lack of assurance. The results also reveal that AI chatbot service failures positively affect dehumanization and increase customers’ perceptions of service failure severity. However, AI chatbots can autonomously remedy service failures through moderate AI emotion. An interesting golden zone of AI’s emotional expression in chatbot service failures was discovered, indicating that extremely weak or strong intensity of AI’s emotional expression can be counterproductive.Originality/valueThis study contributes to the burgeoning AI literature by identifying four types of AI service failure, developing dehumanization theory in the context of smart services, and demonstrating the nonlinear effects of AI emotion. The findings also offer valuable insights for organizations that rely on AI chatbots in terms of designing chatbots that effectively address and remediate service failures.