{"title":"Leadership in AI Terminology Governance: From Anomia to Agency","authors":"Christine Haskell, Suzanne Joy Clark","doi":"10.1002/jls.70002","DOIUrl":null,"url":null,"abstract":"<p>The current article examines the evolving relationship between leadership, artificial intelligence (AI), and language through the lens of structuration theory and critical discourse analysis's sensemaking theory. Through a content analysis of terminology governance practices across industries, we identify key leadership practices and opportunities to shape how organizations name, understand, and implement AI technologies. The study addresses the current state of “AI anomia”—the collective inability to name AI-related tools, including in ethical ways—and presents a practical framework for leaders to govern AI terminology while maintaining human agency in technological adoption. Findings suggest that effective AI terminology governance requires that leaders balance standardization with cultural integration, technical precision with public understanding, and innovation with ethical considerations.</p>","PeriodicalId":45503,"journal":{"name":"Journal of Leadership Studies","volume":"18 4","pages":"55-66"},"PeriodicalIF":0.5000,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jls.70002","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Leadership Studies","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/jls.70002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 0
Abstract
The current article examines the evolving relationship between leadership, artificial intelligence (AI), and language through the lens of structuration theory and critical discourse analysis's sensemaking theory. Through a content analysis of terminology governance practices across industries, we identify key leadership practices and opportunities to shape how organizations name, understand, and implement AI technologies. The study addresses the current state of “AI anomia”—the collective inability to name AI-related tools, including in ethical ways—and presents a practical framework for leaders to govern AI terminology while maintaining human agency in technological adoption. Findings suggest that effective AI terminology governance requires that leaders balance standardization with cultural integration, technical precision with public understanding, and innovation with ethical considerations.