{"title":"影响人工智能准备程度的因素:系统文献综述","authors":"Wajid Ali, Abdul Zahid Khan","doi":"10.1016/j.dsm.2024.09.005","DOIUrl":null,"url":null,"abstract":"<div><div>Public-and private-sector organizations have adopted artificial intelligence (AI) to meet the challenges of the Fourth Industrial Revolution. The successful implementation of AI is a challenging task, and previous research has advocated the need to explore key readiness before AI implementation. The objective of this study is to identify the AI readiness factors explored by different authors in past research. To achieve this, we conducted a rigorous literature review. The approach used in the systematic literature review is also discussed. A rigorous review of 52 studies from various journals and databases (Science Direct, Springer Link, Institute of Electrical and Electronics Engineers, Emerald, and Google Scholar) identified 23 AI readiness factors. The key factors identified were mainly related to organizational information technology infrastructure, top management support, resource availability, collaborative culture, organizational size, organizational capability, compatibility, data quality, and financial budget, whereas the other 15 were potential factors in AI readiness. All of these factors should be considered before the implementation of AI in any organization. The findings also reflect a high failure rate, including AI readiness factors, which are intended to facilitate AI adoption in organizations and reduce the frequency of failures. These factors will aid management in developing an effective strategy for AI implementation in organizations.</div></div>","PeriodicalId":100353,"journal":{"name":"Data Science and Management","volume":"8 2","pages":"Pages 224-236"},"PeriodicalIF":0.0000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Factors influencing readiness for artificial intelligence: a systematic literature review\",\"authors\":\"Wajid Ali, Abdul Zahid Khan\",\"doi\":\"10.1016/j.dsm.2024.09.005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Public-and private-sector organizations have adopted artificial intelligence (AI) to meet the challenges of the Fourth Industrial Revolution. The successful implementation of AI is a challenging task, and previous research has advocated the need to explore key readiness before AI implementation. The objective of this study is to identify the AI readiness factors explored by different authors in past research. To achieve this, we conducted a rigorous literature review. The approach used in the systematic literature review is also discussed. A rigorous review of 52 studies from various journals and databases (Science Direct, Springer Link, Institute of Electrical and Electronics Engineers, Emerald, and Google Scholar) identified 23 AI readiness factors. The key factors identified were mainly related to organizational information technology infrastructure, top management support, resource availability, collaborative culture, organizational size, organizational capability, compatibility, data quality, and financial budget, whereas the other 15 were potential factors in AI readiness. All of these factors should be considered before the implementation of AI in any organization. The findings also reflect a high failure rate, including AI readiness factors, which are intended to facilitate AI adoption in organizations and reduce the frequency of failures. These factors will aid management in developing an effective strategy for AI implementation in organizations.</div></div>\",\"PeriodicalId\":100353,\"journal\":{\"name\":\"Data Science and Management\",\"volume\":\"8 2\",\"pages\":\"Pages 224-236\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Data Science and Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666764924000511\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data Science and Management","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666764924000511","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
公共和私营部门组织已经采用人工智能(AI)来应对第四次工业革命的挑战。成功实施人工智能是一项具有挑战性的任务,之前的研究主张在实施人工智能之前需要探索关键准备情况。本研究的目的是确定不同作者在过去的研究中探索的人工智能就绪因素。为此,我们进行了严格的文献综述。本文还讨论了系统文献综述所采用的方法。对来自不同期刊和数据库(Science Direct, b施普林格Link, Institute of Electrical and Electronics Engineers, Emerald和谷歌Scholar)的52项研究进行了严格审查,确定了23个人工智能就绪因素。确定的关键因素主要与组织信息技术基础设施、高层管理支持、资源可用性、协作文化、组织规模、组织能力、兼容性、数据质量和财务预算有关,而其他15个因素是人工智能准备就绪的潜在因素。在任何组织实施人工智能之前,都应该考虑所有这些因素。调查结果还反映了高故障率,包括人工智能准备因素,旨在促进组织中人工智能的采用并减少故障的频率。这些因素将有助于管理层制定有效的人工智能实施战略。
Factors influencing readiness for artificial intelligence: a systematic literature review
Public-and private-sector organizations have adopted artificial intelligence (AI) to meet the challenges of the Fourth Industrial Revolution. The successful implementation of AI is a challenging task, and previous research has advocated the need to explore key readiness before AI implementation. The objective of this study is to identify the AI readiness factors explored by different authors in past research. To achieve this, we conducted a rigorous literature review. The approach used in the systematic literature review is also discussed. A rigorous review of 52 studies from various journals and databases (Science Direct, Springer Link, Institute of Electrical and Electronics Engineers, Emerald, and Google Scholar) identified 23 AI readiness factors. The key factors identified were mainly related to organizational information technology infrastructure, top management support, resource availability, collaborative culture, organizational size, organizational capability, compatibility, data quality, and financial budget, whereas the other 15 were potential factors in AI readiness. All of these factors should be considered before the implementation of AI in any organization. The findings also reflect a high failure rate, including AI readiness factors, which are intended to facilitate AI adoption in organizations and reduce the frequency of failures. These factors will aid management in developing an effective strategy for AI implementation in organizations.