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
AI 음성 에이전트가 대량 접촉 센터에 배치될 때, 기업은 AI로 낮은 의도를 가진 리드들을 리드할 수 있고 인간 노동자들에게 높은 의도를 가진 리드들을 할당할 수 있습니다. 연속 검색 이론을 기반으로, 우리는 AI가 유도한 작업 할당이 작업을 재구성하여 인간 노동자들에 직면한 기회를 풍부하게 만들지만, 리드와 함께 계속할 수 있도록 예약 가치를 높일 수 있도록 하여 AI 음성 에이전트 배포의 효과를 연구합니다.
Machine translation (Meta M2M100); the English original follows.
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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