Health information system deployment has been driven by the transformation and digitalization currently confronting healthcare. The need and potential of these systems within healthcare have been tremendously driven by the global instability that has affected several interrelated sectors. Accordingly, many research studies have reported on the inadequacies of these systems within the healthcare arena, which have distorted their potential and offerings to revolutionize healthcare. Thus, through a comprehensive review of the extant literature, this study presents a critique of the health information system for healthcare to supplement the gap created as a result of the lack of an in-depth outlook of the current health information system from a holistic slant. From the studies, the health information system was ascertained to be crucial and fundament in the drive of information and knowledge management for healthcare. Additionally, it was asserted to have transformed and shaped healthcare from its conception despite its flaws. Moreover, research has envisioned that the appraisal of the current health information system would influence its adoption and solidify its enactment within the global healthcare space, which is highly demanded.

Artificial intelligence (AI) has emerged as a transformative force across various sectors, including academic libraries, offering potential paradigm shifts in operations and patron services. The imperative need for AI in educational library services stems from its myriad advantages in enhancing efficiency and service quality. Despite its promise, the integration of AI within academic libraries faces hurdles such as expertise shortages, infrastructure limitations, financial constraints, and employment concerns. This paper critically seeks to assess AI implementation in academic library services. The aim is to uncover adoption drivers and challenges in AI implementation in academic libraries. This paper conducts a comprehensive literature review to explore implementation of AI in academic libraries. The findings of the study indicate that AI implementation heralds an era of enhanced service delivery, albeit accompanied by challenges, notably in developing countries like South Africa. It also indicates that success hinges on meticulous planning, collaborative teamwork, adequate funding, and proactive promotion. Furthermore, the paper’s findings offer librarians and top management insights into navigating the adoption of AI projects within academic library settings efficiently.

Artificial intelligence (AI) has become a prevalent part of many businesses, including higher education. AI is progressively gaining traction as an instrumental engagement tool in higher education institutions (HEIs). The premise underlying this trend is the potential of robots to foster enhanced student engagement and, consequently, elevate academic performance. Considering this development, HEI’s must probe deeper into the possible adoption of robotics in educational practices. This paper aims to conduct a comprehensive exploration into the adoption of robotics in teaching and learning in the higher education space. To provide a holistic perspective, this study poses three questions: what factors influence robotics uptake in HEIs, how can robots be integrated to improve teaching and learning in HEIs, and what are the perceived benefits of robotics implementation in teaching and learning. A bibliometric analysis and comprehensive review methodology were employed in this study to provide an in-depth assessment of the development, significance, and implications of robotics in HEIs. The dual approach offers a robust evaluation of robotics as a pivotal element needed for the enhancement of teaching and learning practices. The study’s findings uncover the increasing adoption of robotics within the higher education sphere. It also identifies the challenges encountered during adoption, ranging from technical hurdles to educational adjustments. Furthermore, this paper offers guidelines for various stakeholders for the effective integration of robotics into higher education.

There have been several studies centred on health information systems with many insights provided to enhance health care applications globally. These studies have provided theoretical schemes for fortifying the enactment and utilisation of the Health Information System (HIS). In addition, these research studies contribute greatly to the development of HIS in alignment with major stakeholders such as health practitioners and recipients of health care. Conversely, there has been trepidation about HIS’ sustainability and resilience for healthcare applications in the era of digitalization and globalization. Hence, this paper investigates research on HIS with a primary focus on health care applications to ascertain its sustainability and resilience amidst the transformation of the global healthcare space. Therefore, using a bibliometric approach, this paper measures the performance of health information systems and healthcare for health care applications using bibliometric data from the web of science database. The findings reveal solid evidence of the constructive transformation of health information systems and health care applications in the healthcare arena, providing ample evidence of the adaptation of HIS and health care applications within the healthcare arena to the fourth industrial revolution and, additionally, revealing the resilient alignment of health care applications and health information systems.

Background: The adoption of artificial intelligence (AI) in manufacturing has the potential to considerably improve productivity, efficiency and sustainability. Artificial intelligence aids with tasks such as data processing and process monitoring, process modelling and optimisation, live fault detection, and process quality assessment in manufacturing processes. Aim: This study sought to obtain a full understanding of the influence of AI on the South African manufacturing industry by exploring how AI technology is impacting productivity, reshaping the workforce, affecting quality control practices and optimising supply chain management among other issues. Setting: Data in this study were obtained from 23 qualitative research publications that address the influence of AI on the manufacturing industry in South Africa published on ScienceDirect, Scopus, Springer, Web of Science and Google Scholar. Method: Multiple correspondence analysis was utilised to analyse associations among quality, productivity, supply chain and workforce transformation in the presence of AI in the South African manufacturing industry. Results: The findings demonstrate a substantial association between the usage of AI and a range of performance measures, suggesting that those organisations embracing AI technology can benefit from greater productivity, quality control and supply chain management. Additionally, findings emphasised the necessity of workforce transformation because of AI adoption. Conclusion: The adoption of AI technology positively influenced the South African manufacturing industry, contributing to increased productivity and quality, and optimising the supply chain. Contribution: This study makes a valuable contribution to the existing body of knowledge as AI adoption in the manufacturing industry in developing countries is only emerging.

Introduction: Many transformations and uncertainties, such as the fourth industrial revolution and pandemics, have propelled healthcare acceptance and deployment of health information systems (HIS). External and internal determinants aligning with the global course influence their deployments. At the epic is digitalization, which generates endless data that has permeated healthcare. The continuous proliferation of complex and dynamic healthcare data is the digitalization frontier in healthcare that necessitates attention. Objective: This study explores the existing body of information on HIS for healthcare through the data lens to present a data-driven paradigm for healthcare augmentation paramount to attaining a sustainable and resilient HIS. Method: Preferred Reporting Items for Systematic Reviews and Meta-Analyses: PRISMA-compliant in-depth literature review was conducted systematically to synthesize and analyze the literature content to ascertain the value disposition of HIS data in healthcare delivery. Results: This study details the aspects of a data-driven paradigm for robust and sustainable HIS for health care applications. Data source, data action and decisions, data sciences techniques, serialization of data sciences techniques in the HIS, and data insight implementation and application are data-driven features expounded. These are essential data-driven paradigm building blocks that need iteration to succeed. Discussions: Existing literature considers insurgent data in healthcare challenging, disruptive, and potentially revolutionary. This view echoes the current healthcare quandary of good and bad data availability. Thus, data-driven insights are essential for building a resilient and sustainable HIS. People, technology, and tasks dominated prior HIS frameworks, with few data-centric facets. Improving healthcare and the HIS requires identifying and integrating crucial data elements. Conclusion: The paper presented a data-driven paradigm for a resilient and sustainable HIS. The findings show that data-driven track and components are essential to improve healthcare using data analytics insights. It provides an integrated footing for data analytics to support and effectively assist health care delivery.