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

Shijie Liu Shanghai Maritime University ; Jianfen Chen Towson University

Abstract

<bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>Background:</i></b> 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. <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>Literature review:</i></b> We situate this study within the existing scholarship regarding job postings analysis in TPC, AI in TPC, and AI literacy. <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>Research questions:</i></b> How do employers reference AI literacy in TPC job postings? How are AI literacy dimensions distributed across the TPC job description domains? <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>Methodology:</i></b> 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. <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>Results:</i></b> 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. <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>Conclusion:</i></b> 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.

Journal
IEEE Transactions on Professional Communication
Published
2026-06-01
DOI
10.1109/tpc.2026.3685842
CompPile
Open Access
Closed
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