{"title":"人工智能强化培训、教育与发展:生成式人工智能在领导力学习中的作用的探索与洞察","authors":"Daniel Jenkins, Gaurav Khanna","doi":"10.1002/jls.70004","DOIUrl":null,"url":null,"abstract":"<p>The current article examines artificial intelligence's (AI) role in leadership training, education, and development across higher education and industry contexts. We analyze current implementations and explore how AI technologies reshape leadership preparation while investigating the essential balance between task-oriented and relationship-oriented approaches. Our analysis reveals that successful AI integration depends on human-in-the-loop processes, pedagogical design that preserves relationship-building, and comprehensive AI literacy development. The study introduces the concept of ‘taxonomical leapfrogging’ and demonstrates how AI can enhance traditional leadership development through sophisticated content sequencing, personalized learning pathways, and intelligent feedback systems. We provide a practical framework for implementing AI tools while identifying key challenges, including quality assurance at scale and ethical considerations. Our findings suggest that effective leadership development requires integrated approaches that leverage AI's capabilities while preserving essential human elements, with specific recommendations for both academic programs and industry initiatives.</p>","PeriodicalId":45503,"journal":{"name":"Journal of Leadership Studies","volume":"18 4","pages":"81-97"},"PeriodicalIF":0.5000,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AI-Enhanced Training, Education, & Development: Exploration and Insights Into Generative AI's Role in Leadership Learning\",\"authors\":\"Daniel Jenkins, Gaurav Khanna\",\"doi\":\"10.1002/jls.70004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The current article examines artificial intelligence's (AI) role in leadership training, education, and development across higher education and industry contexts. We analyze current implementations and explore how AI technologies reshape leadership preparation while investigating the essential balance between task-oriented and relationship-oriented approaches. Our analysis reveals that successful AI integration depends on human-in-the-loop processes, pedagogical design that preserves relationship-building, and comprehensive AI literacy development. The study introduces the concept of ‘taxonomical leapfrogging’ and demonstrates how AI can enhance traditional leadership development through sophisticated content sequencing, personalized learning pathways, and intelligent feedback systems. We provide a practical framework for implementing AI tools while identifying key challenges, including quality assurance at scale and ethical considerations. Our findings suggest that effective leadership development requires integrated approaches that leverage AI's capabilities while preserving essential human elements, with specific recommendations for both academic programs and industry initiatives.</p>\",\"PeriodicalId\":45503,\"journal\":{\"name\":\"Journal of Leadership Studies\",\"volume\":\"18 4\",\"pages\":\"81-97\"},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2025-03-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Leadership Studies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/jls.70004\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Leadership Studies","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/jls.70004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MANAGEMENT","Score":null,"Total":0}
AI-Enhanced Training, Education, & Development: Exploration and Insights Into Generative AI's Role in Leadership Learning
The current article examines artificial intelligence's (AI) role in leadership training, education, and development across higher education and industry contexts. We analyze current implementations and explore how AI technologies reshape leadership preparation while investigating the essential balance between task-oriented and relationship-oriented approaches. Our analysis reveals that successful AI integration depends on human-in-the-loop processes, pedagogical design that preserves relationship-building, and comprehensive AI literacy development. The study introduces the concept of ‘taxonomical leapfrogging’ and demonstrates how AI can enhance traditional leadership development through sophisticated content sequencing, personalized learning pathways, and intelligent feedback systems. We provide a practical framework for implementing AI tools while identifying key challenges, including quality assurance at scale and ethical considerations. Our findings suggest that effective leadership development requires integrated approaches that leverage AI's capabilities while preserving essential human elements, with specific recommendations for both academic programs and industry initiatives.