Journal: Economics DOI: 10.32629/ej.v9i9.3639
Abstract
生成式人工智能进入企业工作场景以后,不一定会带来工作效率的提升。当技术成熟 度不够或者任务匹配程度不足的时候,员工可能在原有工作之外又增加了学习、检查 和修改等任务,这样就形成了新的工作负荷。基于此,本文根据工作要求与资源理论 、技术压力理论还有任务与技术匹配理论,结合一些企业实践和实证研究,分析人工 智能早期导入中的员工工作强化问题。研究发现,人工智能对绩效的影响要看技术、 任务与组织流程的匹配程度,所以企业应该从关注人工智能使用率转到关注实际工作 价值,通过试点应用、负荷评估和流程优化来提高人工智能应用成效。
Keywords
人工智能;组织行为;工作强化;技术压力;任务与技术匹配
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[1] Microsoft.The 2025 Annual Work Trend Index:The Frontier Firm is Born[R].Microsoft,2025.
[2] Demerouti E, Bakker A B,Nachreiner F,Schaufeli W B. The Job Demands- Resources Model of Burnout[J].Journal of Applied Psychology,2001,86(3):499- 512.
[3] Bakker A B,Demerouti E.The Job Demands-Resources Model:State of the Art[J].Journal of Managerial Psychology,2007,22(3):309-328.
[4] Tarafdar M, Pullins E B,Ragu-Nathan T S.Technostress: Negative Effect on Performance and Possible Mitigations[J].Information Systems Journal,2015,25(2):103-132.
[5] Goodhue D L,Thompson R L.Task-Technology Fit and Individual Performance[J].MIS Quarterly,1995,19(2):213-236.
[6] Business Insider.Microsoft Pushes Staff to Use Internal AI Tools More, and May Consider This in Reviews. Using AI Is No Longer Optional[N/OL].Business Insider,2025-06.
[7] Becker J,Rush N,Barnes B,Rein D.Measuring the Impact of Early 2025 AI on Experienced Open Source Developer Productivity[R].METR,2025.
[8] Brynjolfsson E,Li D,Raymond L R.Generative AI at Work[R].NBER Working Paper 31161,2023.
[9] Raisch S,Krakowski S.Artificial Intelligence and Management:The Automation-Augmentation Paradox[J].Academy of Management Review,2021,46(1):192-210.
[10] Jarrahi M H.Artificial Intelligence and the Future of Work:Human-AI Symbiosis in Organizational Decision Making[J].Business Horizons,2018,61(4):577-586.
[11] Kellogg K C,Valentine M A,Christin A.Algorithms at Work:The New Contested Terrain of Control[J].Academy of Management Annals,2020,14(1):366- 410.
[12] Autor D H.Why Are There Still So Many Jobs? The History and Future of Workplace Automation[J].Journal of Economic Perspectives,2015,29(3):3-30.
[2] Demerouti E, Bakker A B,Nachreiner F,Schaufeli W B. The Job Demands- Resources Model of Burnout[J].Journal of Applied Psychology,2001,86(3):499- 512.
[3] Bakker A B,Demerouti E.The Job Demands-Resources Model:State of the Art[J].Journal of Managerial Psychology,2007,22(3):309-328.
[4] Tarafdar M, Pullins E B,Ragu-Nathan T S.Technostress: Negative Effect on Performance and Possible Mitigations[J].Information Systems Journal,2015,25(2):103-132.
[5] Goodhue D L,Thompson R L.Task-Technology Fit and Individual Performance[J].MIS Quarterly,1995,19(2):213-236.
[6] Business Insider.Microsoft Pushes Staff to Use Internal AI Tools More, and May Consider This in Reviews. Using AI Is No Longer Optional[N/OL].Business Insider,2025-06.
[7] Becker J,Rush N,Barnes B,Rein D.Measuring the Impact of Early 2025 AI on Experienced Open Source Developer Productivity[R].METR,2025.
[8] Brynjolfsson E,Li D,Raymond L R.Generative AI at Work[R].NBER Working Paper 31161,2023.
[9] Raisch S,Krakowski S.Artificial Intelligence and Management:The Automation-Augmentation Paradox[J].Academy of Management Review,2021,46(1):192-210.
[10] Jarrahi M H.Artificial Intelligence and the Future of Work:Human-AI Symbiosis in Organizational Decision Making[J].Business Horizons,2018,61(4):577-586.
[11] Kellogg K C,Valentine M A,Christin A.Algorithms at Work:The New Contested Terrain of Control[J].Academy of Management Annals,2020,14(1):366- 410.
[12] Autor D H.Why Are There Still So Many Jobs? The History and Future of Workplace Automation[J].Journal of Economic Perspectives,2015,29(3):3-30.
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