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How Organizations Can Integrate AI-Generated Positive Communication Into Recruitment Efforts for Gen Z Employees

Stephanie A. Smith & Michael G. Strawser

Business and Professional Communication Quarterly2026https://doi.org/10.1177/23294906251406942article
ABDC C
Weight
0.50

What the paper says

This study examines the role of positive communication in AI-generated recruitment messaging and its influence on Generation Z job seekers. Drawing on positive communication scholarship (Mirivel & Fuller, 2024) and the Human Needs Approach (Socha & Beck, 2015), we explore how AI-generated job descriptions shape anticipatory socialization and perceptions of workplace culture. Using qualitative focus groups, we identify key themes related to authenticity, engagement, and the fulfillment of fundamental psychological needs. Findings indicate that although positive communication enhances job attractiveness, job seekers remain skeptical of AI-generated content unless it aligns with real-world workplace values. Organizations must balance AI efficiency with human oversight to maintain trust and ensure transparency in recruitment messaging. This study contributes to business communication research by offering practical and pedagogical implications for AI-integrated hiring strategies and ethical recruitment communication.

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Cite this paper

https://doi.org/https://doi.org/10.1177/23294906251406942

Or copy a formatted citation

@article{stephanie2026,
  title        = {{How Organizations Can Integrate AI-Generated Positive Communication Into Recruitment Efforts for Gen Z Employees}},
  author       = {Stephanie A. Smith & Michael G. Strawser},
  journal      = {Business and Professional Communication Quarterly},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/23294906251406942},
}

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How Organizations Can Integrate AI-Generated Positive Communication Into Recruitment Efforts for Gen Z Employees

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.