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Enterprise Architecture-Based Project Model for AI Service System Development

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Handbook on Artificial Intelligence-Empowered Applied Software Engineering

Part of the book series: Artificial Intelligence-Enhanced Software and Systems Engineering ((AISSE,volume 2))

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Abstract

In this chapter, we consider projects in which enterprise service systems are developed using artificial intelligence (AI) technologies. When developing a system using AI technologies to support a business task in a company, all project members from both business and IT divisions must have a common understanding of the project to ensure success. Therefore, we propose an enterprise architecture-based business–IT alignment model for AI service systems as a generic business–AI alignment model and a business analysis method for constructing project specific models from the generic model. We evaluated the proposed model and business analysis method through a practice.

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Acknowledgements

This work was supported by the JSPS Grant-in-Aid for Scientific Research (KAKENHI) Grant Number JP19K20416, and JST-Mirai Project (Engineerable AI Techniques for Practical Applications of High-Quality Machine Learning-based Systems) Grant Number JPMJMI20B8.

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Authors and Affiliations

  1. Musashi University, 1-26-1, Toyotama-kami, Nerima-ku, Tokyo, 176-8534, Japan

    Hironori Takeuchi

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  1. Hironori Takeuchi
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Correspondence to Hironori Takeuchi .

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Editors and Affiliations

  1. Department of Informatics, University of Piraeus, Piraeus, Greece

    Maria Virvou

  2. Department of Informatics, University of Piraeus, Piraeus, Greece

    George A. Tsihrintzis

  3. College of Engineering and Computer Science, Wright State University, Joshi Research, Dayton, OH, USA

    Nikolaos G. Bourbakis

  4. KES International, Shoreham-by-Sea, UK

    Lakhmi C. Jain

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Takeuchi, H. (2022). Enterprise Architecture-Based Project Model for AI Service System Development. In: Virvou, M., Tsihrintzis, G.A., Bourbakis, N.G., Jain, L.C. (eds) Handbook on Artificial Intelligence-Empowered Applied Software Engineering. Artificial Intelligence-Enhanced Software and Systems Engineering, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-031-08202-3_7

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