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人工智能系统在企业绩效考核中的应用

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随着信息技术的不断发展和普及,企业面临着越来越复杂和多样化的市场环境与业务挑战.在这样的背景下,企业需要对员工和部门的绩效进行科学、准确的评估和预测,以制定更有效的管理策略、决策方针与激励机制,增加员工积极性,提高企业的竞争力与生产效率.然而,传统的绩效考核方式往往存在主观性、局限性等问题,难以满足企业对于绩效考核的精细化和智能化需求.人工智能系统在企业绩效考核中的应用已经成为了越来越多企业的选择,基于此,通过对人工智能技术、企业绩效考核及其应用现状的分析,探讨了人工智能系统在企业绩效考核中的具体应用,以及其在提升企业绩效方面的作用.结果显示,人工智能技术能够快速高效地对企业绩效进行测量和分析,为企业决策提供支持,并在提高企业绩效、优化资源配置和提高员工绩效方面发挥重要的作用.
Application of Artificial Intelligence Systems in Corporate Performance Appraisal
As information technology continues to develop and spread,companies are faced with increasingly complex and diverse market environments and business challenges.In such a context,enterprises need to conduct scientific and accurate assessment and prediction of employee and departmental performance in order to formulate more effective management strategies,decision-making guidelines and incentive mechanisms,increase employee motivation and improve the competitiveness and productivity of enterprises.However,traditional performance ap-praisal methods often suffer from subjectivity and limitations,making it difficult to meet the refined and intelligent needs of enterprises for performance appraisal.The application of artificial intelligence systems in enterprise per-formance appraisal has become the choice of more and more enterprises.Through the analysis of artificial intelli-gence technology,enterprise performance appraisal and its application status,this paper discusses the specific ap-plication of artificial intelligence systems in enterprise performance appraisal and its role in improving enterprise performance.The results show that AI technology can quickly and efficiently measure and analyze corporate per-formance,provide support for corporate decision-making,and play an important role in improving corporate per-formance,optimising resource allocation and improving employee performance.

artificial intelligencecorporate performance appraisalresource allocationemployee performance

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山西省信息产业技术研究院有限公司,山西 太原 030012

人工智能 企业绩效考核 资源配置 员工绩效

2024

山西电子技术
山西省电子工业科学研究院 山西省电子学会

山西电子技术

影响因子:0.197
ISSN:1674-4578
年,卷(期):2024.(3)