Newest papers

When Better Opportunities Backfire: Service Worker Responses to Parallel AI Deployment in Customer Acquisition

Xinyu Fu, Shulong Luo, Narayan Ramasubbu, Peng Shen, Xincheng Wang, Yucheng Wang · 2026 · SSRN Electronic Journal

DOI: 10.2139/ssrn.7631480 · cited by 0 works (OpenAlex) · open-access PDF

Arabic

عندما يتم توزيع آلات صوتي AI في مراكز الاتصال عالية الدقة، يمكن للشركات توزيع الأهداف المنخفضة إلى الذكاء الاصطناعي وتوزيع الأهداف المنخفضة إلى العمال البشريين. استناداً إلى نظرية البحث السريع، نحن نعتقد أن توزيع المهام التي تسببها الذكاء الاصطناعي يغير العمل، مما يزيد من فرص العمل التي تواجهها العمال البشريين، ولكن أيضا يزيد من قيمة احتياجاتهم من أجل الاستمرار مع الأهداف في يدهم، مما يجعلهم أقل عرضة للتوقف.

Machine translation (Meta M2M100); the English original follows.

Abstract

As AI voice agents get deployed in high-volume contact centers, firms can route low-intent leads to AI and allocate high-intent leads to human workers. Drawing on sequential search theory, we posit that AI-induced task allocation reshapes work, enriching opportunities facing human workers but also raising their reservation value for continuing with the lead in hand, making them less willing to persist. We study the effects of an AI voice-agent deployment at a Chinese online health-insurance brokerage using more than a half million customer outreach records surrounding the rollout. Adopting a r

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Topics: Software deployment, Reservation, Business, Workload, Marketing, Service (business)

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