Mapping AI Literacy Expectations in Technical and Professional Communication: Evidence From 137 AI-Referenced Job Postings

Abstract

Background: This exploratory study examines the emerging requirements of artificial-intelligence (AI) literacies reflected in technical and professional communication (TPC) job postings and provides empirical insights into how employers articulate these literacies in hiring practices. Literature review: We situate this study within the existing scholarship regarding job postings analysis in TPC, AI in TPC, and AI literacy. Research questions: How do employers reference AI literacy in TPC job postings? How are AI literacy dimensions distributed across the TPC job description domains? Methodology: We collected job postings published between March 1 and June 10, 2025, across ten major online recruitment platforms, focusing on US-based positions that fall into six TPC job categories that explicitly referenced AI. This process yielded 137 eligible postings for analysis. Employing a multistage and mixed-method design for data analysis, we coded AI literacies using the AI literacy framework and coded the job descriptions using the four TPC job description domains. Results: Our quantitative findings show growing integration of AI literacy into TPC roles, with uneven emphasis on specific AI literacy dimensions across TPC positions. Employers prioritize practical applications of AI tools, while ethical considerations receive little attention. Our topical modeling analysis also indicates that AI literacy is an integrative skill and functions as an embedded capability in TPC jobs. Conclusion: This study has significant implications for TPC educators. AI literacy should be taught as an integrative skill that augments human expertise. TPC programs should embed AI instruction across the curriculum while continuing to emphasize the core competencies essential to professional communication.