From HAL to GenAI: Optimizing chatbot impacts with CARE
Cai Feng, Elsamari Botha, Leyland Pitt
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 reshapes industry dynamics. The Meso perspective delves into organizational changes, while the Micro lens focuses on enhancing individual productivity, learning, and creativity. However, GenAI chatbots’ immense potential is accompanied by risks in four META areas – Matching, Ethics, Technology, and Adaptability. In response to these challenges, the article introduces a human-centric CARE framework – Collaboration, Accountability, Responsiveness, and Empowerment – to mitigate the risks and optimize the impacts brought by GenAI chatbots. This work provides practical guidelines to navigate the complex landscape of GenAI implementation.