From HAL to GenAI: Optimizing chatbot impacts with CARE

Feng, Cai (Mitsu), Elsamari Botha and Leyland Pitt

Business Horizons, 2024, vol. 67, issue 5, 537-548

Abstract: This article explores the evolution and prospects of conversational chatbots, specifically the latest generation referred to as generative artificial intelligence (GenAI) chatbots. This article comprehensively examines GenAI chatbots’ business applications and impact across macro, meso, and micro levels of organizations. At the macro level, this article explores how GenAI chatbots reshape industry dynamics. The meso perspective delves into organizational changes, while the micro lens focuses on enhancing individual productivity, learning, and creativity. GenAI chatbots’ immense potential is accompanied by risks in four areas: matching, ethics, technology, and adaptability (META). In response to these challenges, the article introduces a human-centric CARE framework—standing for collaboration, accountability, responsiveness, and empowerment—to mitigate the risks and to optimize the effects of GenAI chatbots. This work provides practical guidelines for navigating the complex landscape of GenAI implementation.

Keywords: Generative AI; Chatbots; AI adoption; AI risks; AI ethics; Large language models (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:bushor:v:67:y:2024:i:5:p:537-548

DOI: 10.1016/j.bushor.2024.04.012

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