AI-based Technologies for Conversational Agent Design– Development Tools and Architectures for Intelligent Interactions
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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29th Annual Americas Conference on Information Systems, AMCIS 2023. The Association for Information Systems (AIS), 2023. (29th Annual Americas Conference on Information Systems, AMCIS 2023).
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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RIS
TY - CHAP
T1 - AI-based Technologies for Conversational Agent Design– Development Tools and Architectures for Intelligent Interactions
AU - Strohmann, Timo
AU - Khosrawi-Rad, Bijan
AU - Schmidt, Lukas
AU - Hiske, Patrick
N1 - Publisher Copyright: © 2023 29th Annual Americas Conference on Information Systems, AMCIS 2023. All rights reserved.
PY - 2023
Y1 - 2023
N2 - Conversational agents are becoming increasingly intelligent due to artificial intelligence (AI) advances, improving human-machine interaction. As conversational agents are already being used in various real-world applications, research shows the enormous potential of exploring advanced areas such as companionship or learning support. Particularly, those intelligent and future-oriented application areas rely on using AI-based technologies. However, implementations are often prototypical without comprehensive technological information. Moreover, the possibilities for practical implementation of conversational agents are growing, making the choice of architecture and tools for implementation complex. We address this problem by developing a taxonomy that helps characterize AI-based tools and services for intelligent interactions. We then derive archetypes for AI-based tools using cluster analysis and give meta-architectures that exemplify how to integrate AI-based services into typical technical conversational agent architectures. With our research, we aim to expand the knowledge base for developing conversational agents and support developers in their implementation.
AB - Conversational agents are becoming increasingly intelligent due to artificial intelligence (AI) advances, improving human-machine interaction. As conversational agents are already being used in various real-world applications, research shows the enormous potential of exploring advanced areas such as companionship or learning support. Particularly, those intelligent and future-oriented application areas rely on using AI-based technologies. However, implementations are often prototypical without comprehensive technological information. Moreover, the possibilities for practical implementation of conversational agents are growing, making the choice of architecture and tools for implementation complex. We address this problem by developing a taxonomy that helps characterize AI-based tools and services for intelligent interactions. We then derive archetypes for AI-based tools using cluster analysis and give meta-architectures that exemplify how to integrate AI-based services into typical technical conversational agent architectures. With our research, we aim to expand the knowledge base for developing conversational agents and support developers in their implementation.
KW - Architecture
KW - Chatbot
KW - Conversational Agents
KW - Taxonomy
UR - http://www.scopus.com/inward/record.url?scp=85184806434&partnerID=8YFLogxK
M3 - Article in conference proceedings
AN - SCOPUS:85184806434
T3 - 29th Annual Americas Conference on Information Systems, AMCIS 2023
BT - 29th Annual Americas Conference on Information Systems, AMCIS 2023
PB - The Association for Information Systems (AIS)
T2 - 29th Annual Americas Conference on Information Systems: Diving into Uncharted Waters, AMCIS 2023
Y2 - 10 August 2023 through 12 August 2023
ER -