The study highlights the crucial role of professional social media and LinkedIn instruction for students seeking employment. An analysis of 20 business and technical communication textbooks identifies significant gaps between textbook guidance and real-world expectations. Some textbooks in both fields fall short in offering actionable strategies for creating and maintaining a professional social media presence. While many textbooks emphasize the importance of social media or LinkedIn, most fail to provide concrete examples or best practices, such as keyword optimization for AI, effective networking strategies, and best practices for posting content. Grounded in digital literacy theory and professional identity formation, the study provides teaching recommendations, including the identification and adoption of supplemental materials to teach professional social media usage.

Businesses increasingly use Artificial Intelligence (AI) Applicant Tracking Systems (ATS) to screen job applicants’ résumés. A summative content analysis auditing how 18 business communication, business English, and technical communication textbooks cover résumés and AI ATS found a lack of consensus. The study identified the challenge of offering specific advice on emerging AI technology in textbooks. The article recommends writing and teaching practice changes when discussing emerging technology and creating or using textbook content.

In a cross-institutional study, this article shares research findings about business student perceptions and experiences using an automated writing assistant program based on traditional artificial intelligence. Using a mixed-methods approach, we share student responses to Grammarly’s suggested revisions and provide insight into students’ confidence levels and correctness in workplace written communication. Finally, this study concludes with a discussion of the implications of this work related to business communication education and research, as well as possibilities for the future.

This article presents the ongoing conversation about generative AI guidance and policy in higher education. The article examines syllabus policies, including analyzing sentiment, emotion, and common themes in GenAI policies. Findings show that policies should be audience-focused, clearly written, and grounded in strategies to promote ethical AI use in academia and the workforce. Practical tips for policy writing and sample policies are provided.