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arXiv · 2012.11976

A Maturity Assessment Framework for Conversational AI Development Platforms

Johan Aronsson·Philip Lu·Daniel Strüber·Thorsten Berger
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Abstract

Conversational Artificial Intelligence (AI) systems have recently sky-rocketed in popularity and are now used in many applications, from car assistants to customer support. The development of conversational AI systems is supported by a large variety of software platforms, all with similar goals, but different focus points and functionalities. A systematic foundation for classifying conversational AI platforms is currently lacking. We propose a framework for assessing the maturity level of conversational AI development platforms. Our framework is based on a systematic literature review, in which we extracted common and distinguishing features of various open-source and commercial (or in-house) platforms. Inspired by language reference frameworks, we identify different maturity levels that a conversational AI development platform may exhibit in understanding and responding to user inputs. Our framework can guide organizations in selecting a conversational AI development platform according to their needs, as well as helping researchers and platform developers improving the maturity of their platforms.

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Johan Aronsson, Philip Lu, Daniel Strüber, Thorsten Berger. 2020-12-22. A Maturity Assessment Framework for Conversational AI Development Platforms. https://doi.org/10.1145/3412841.3442046

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