Creational and conversational AI affordances: How the new breed of chatbots is revolutionizing knowledge industries

Laavanya Ramaul, Paavo Ritala and Mika Ruokonen

Business Horizons, 2024, vol. 67, issue 5, 615-627

Abstract: The new generative AI (GenAI) paradigm offers unprecedented opportunities for users to tap into. AI capabilities are increasingly helpful in creative and knowledge-intensive domains that have long been considered a territory of human expertise. The new breed of chatbots is based on large language models (LLMs), and they have overcome many constraints that plague the everyday use of previous AI technologies. This article employs the theory of affordances to understand how ChatGPT facilitates (i.e., affords) and constrains (i.e., disaffords) the usefulness of a new breed of chatbots. We further divide two distinct yet interrelated dimensions of new AI affordances: creational and conversational. Via 29 interviews with professionals using ChatGPT in various creative and knowledge-intensive sectors, we identify three creational affordances (content creation and enhancement, knowledge acquisition and creativity augmentation, and task automation) and three conversational affordances (contextual sensitivity, interactive accessibility, and human-AI workflow synergy). Creational affordances refer to the system’s ability to produce novel outputs and automate routine work, whereas conversational affordances encompass the variety of interaction possibilities with an AI system. Both affordances also involve disaffordances that limit the usefulness of the new types of AI systems. Furthermore, we introduce an integrated framework that shows how creational and conversational affordances reinforce each other via meta-affordances of accessibility, accumulation, and adaptability. We illustrate our findings with practical examples and offer guidelines for using these emerging capabilities in company settings.

Keywords: Conversational AI; Generative AI; ChatGPT; Technology affordances; Chatbots (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:615-627

DOI: 10.1016/j.bushor.2024.05.006

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