This study explores pandemic impact on internships during the Spring 2020 semester when Covid lockdowns began. Using anonymized data from a Spring 2020 Business Internship course, this study details the breadth of the impact and uses employer exit survey data from intern performance reviews to assess how effectively business interns were able to pivot to successfully complete the internship and to meet employer expectations around key soft skills performance areas. Included in the conclusion are implications and practical suggestions for preparing students for success in the ever-changing landscape of internships.

LinkedIn has emerged as a dominant platform for professional networking and career development, yet bibliometric analyses on its scholarly landscape remain scarce. This study systematically maps LinkedIn research using 1,273 peer-reviewed publications from Web of Science (WoS), following the SPAR-4-SLR protocol. To address four core research questions, we analyze (1) thematic structures and evolution, (2) collaboration and citation networks, (3) publication venues and citation metrics, and (4) emerging trends. Key bibliometric indicators—total citations (25,461), h- index (38), and publication trends—were analyzed, while co-citation and bibliographic coupling (WoS) and keyword co-occurrence (Scopus) network analyses were conducted using VOSviewer. Results reveal a sharp publication increase, peaking at 204 in 2023, with Computers in Human Behavior (19 papers, 898 citations) and PLOS One (10 papers, 897 citations) as leading outlets. Research clusters focus on recruitment, professional branding, and LinkedIn’s role in organizations, though empirical validation remains limited, particularly regarding career outcome predictions. Findings offer a structured knowledge base for academia and industry. Limitations include reliance on WoS for citations and Scopus for keywords, potentially introducing data set inconsistencies. Future research should integrate cross-database approaches and explore LinkedIn’s role in AI-driven recruitment.

In the globalized labor market, skills gaps between industry expectations and university preparation are becoming more prevalent. English communication skills (ECS) are vital soft skills in all workplaces, particularly in international business, where English is commonly used as a lingua franca. This case study examined the nexus between academia and industry regarding the instruction of ECS and their applicability to meet the requirements of the globalized business landscape by collecting data from 43 personnel in the international ready-made garment (RMG) industry in Bangladesh. The research reveals that English courses in higher education do not adequately address the communication needs of the international RMG business, which requires practical experience in the workplace, trade-specific vocabulary, intelligibility, and clarity rather than a high level of fluency. The study recommends promoting the teaching of English for general business purposes in Bangladesh by integrating theoretical and practical learning in the classroom and workplace as part of the curriculum.

Data-driven decision making has now moved beyond its traditional domains—operations research, business economics, computer sciences, and business statistics—to “softer subjects,” such as human resource management, organization behavior, and business communication. In this context, teaching with technology encourages students to systematically apply domain knowledge to communicate across a wide variety of stakeholders. In the era of multimodal forms of communication and multiple data sources, management students must be analytical when writing compelling reports and giving persuasive presentations. They should be well versed in using both quantitative and qualitative techniques for report writing and presentation. Drawing on authentic user-generated comments on social media, this article presents two case studies on (a) crisis communication by 30 CEOs and (b) culture shock experienced by foreign tourists sojourning in India, China, and the United Arab Emirates, to demonstrate how master’s in business administration (MBA) students could derive insights from the online comments to make strategic decisions for organizational benefit and make reports based on those findings. The article asserts that this could help to cultivate a data-analytic mindset among the students by preparing them to communicate small (and big) data-driven analysis to relevant stakeholders. It attempts to suggest ways to develop MBA students’ ability to analyze their potential audiences as well as to generate meaningful insights from the available information on social media websites. Finally, it hopes to nudge business communication instructors to embrace multidisciplinary perspectives for planning a technology-based business communication assignment involving the social media landscape. Instructors can not only use the two case studies to illustrate ways to integrate technology with teaching but also create their own mini cases to improve the decision-making, report-writing, and business report presentation skills of their students.

The rapid, widespread implementation of artificial intelligence technologies in workplaces has implications for business communication. In this article, the authors describe current capabilities, challenges, and concepts related to the adoption and use of artificial intelligence (AI) technologies in business communication. Understanding the abilities and inabilities of AI technologies is critical to using these technologies ethically. The authors offer a proposed research agenda for researchers in business communication concerning topics of implementation, lexicography and grammar, collaboration, design, trust, bias, managerial concerns, tool assessment, and demographics. The authors conclude with some ideas regarding how to teach about AI in the business communication classroom.