TOGAF Framework For an AI-enabled Software House
DOI:
10.33395/sinkron.v8i2.12390Keywords:
Artificial Intelligence, TOGAF, Enterprise Architecture, AI-Enabled, Software HouseAbstract
The integration of artificial intelligence (AI) in software development has revolutionized the industry, leading to faster and more accurate results. However, the implementation of AI requires a robust framework to ensure effective planning, design, implementation, and maintenance of AI-enabled software systems. The Open Group Architecture Framework (TOGAF) provides such a framework, enabling organizations to develop a structured and integrated approach to AI-enabled software development. In this journal, we present a case study of how a software house utilized the TOGAF framework to integrate AI in their software development processes. We discuss the challenges faced by the organization in the integration process and how the TOGAF framework provided a structured approach to overcome these challenges. We also highlight the benefits that the organization realized through the implementation of AI-enabled software systems. The case study presented in this journal demonstrates the applicability of the TOGAF framework in AI-enabled software development, and its potential to enhance the capabilities and competitiveness of software houses. The TOGAF framework provides a structured approach to the integration of AI in software development, ensuring that organizations can effectively leverage the benefits of AI while minimizing the associated risks and challenges.
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References
Haren, V. (2011). TOGAF Version 9.1. In Van Haren Publishing eBooks. Van Haren Publishing. https://dl.acm.org/citation.cfm?id=2208005
Wamba-Taguimdje, S., Wamba, S. F., Kamdjoug, J. R. K., & Wanko, C. E. T. (2020). Influence of artificial intelligence (AI) on firm performance: the business value of AI-based transformation projects. Business Process Management Journal, 26(7), 1893–1924. https://doi.org/10.1108/bpmj-10-2019-0411
Davenport, T. H. (2018). From analytics to artificial intelligence. Journal of Business Analytics, 1(2), 73–80. https://doi.org/10.1080/2573234x.2018.1543535
Cukier, K. N. (2021). Commentary: How AI Shapes Consumer Experiences and Expectations. Journal of Marketing, 85(1), 152–155. https://doi.org/10.1177/0022242920972932
Walia. (2023. Guest editorial for special issue – AI facets and industrial applications (Part 2). Guest Editorial for Special Issue – AI Facets and Industrial Applications (Part 2).
Balocco, R., Cavallo, A., Ghezzi, A., & Berbegal-Mirabent, J. (2019). Lean business models change process in digital entrepreneurship. Business Process Management Journal, 25(7), 1520–1542. https://doi.org/10.1108/bpmj-07-2018-0194
Muhammad, S. A., Indrajit, R. E., & Dazki, E. (2022). Kajian Pengembangan Enterprise Architecture Pada Industri Software House. Jutisi : Jurnal Ilmiah Teknik Informatika Dan Sistem Informasi, 11(2), 403. https://doi.org/10.35889/jutisi.v11i2.929
Michael, D., Indrajit, R. E., & Dazki, E. (2022). Implementation of Enterprise Architecture in Cloud Computing Companies. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 7(2), 549–559. https://doi.org/10.33395/sinkron.v7i2.11407
Bernaert, M., Poels, G., Snoeck, M., De Backer, M. (2013). Enterprise architecture for small and medium-sized enterprises: A starting point for bringing EA to smes, based on adoption models. Progress in IS, 67–96. https://doi.org/10.1007/978-3-642-38244-4_4
Mishra, S., & Tripathi, A. K. (2021). AI business model: an integrative business approach. Journal of Innovation and Entrepreneurship, 10(1). https://doi.org/10.1186/s13731-021-00157-5
Gong, Y., & Janssen, M. (2021). Roles and Capabilities of Enterprise Architecture in Big Data Analytics Technology Adoption and Implementation. Journal of Theoretical and Applied Electronic Commerce Research, 16(1), 37–51. https://doi.org/10.4067/s0718-18762021000100104
Schkarin, T., & Dobhan, A. (2022). Prerequisites for Applying Artificial Intelligence for Scheduling in Small- and Medium-sized Enterprises. Prerequisites for Applying Artificial Intelligence for Scheduling in Small- and Medium-sized Enterprises.
Kerzel, U. (2021). Enterprise AI Canvas Integrating Artificial Intelligence into Business. Applied Artificial Intelligence, 35(1), 1–12. https://doi.org/10.1080/08839514.2020.1826146
Mucha, T., & Seppälä, T. (2020). Artificial Intelligence Platforms – A New Research Agenda for Digital Platform Economy. Social Science Research Network. https://doi.org/10.2139/ssrn.3532937
Pereira, S. L., Medina, F. a. D. S., Gonçalves, R. F., & Da Silva, M. V. (2016). System Thinking and Business Model Canvas for Collaborative Business Models Design. In IFIP advances in information and communication technology (pp. 461–468). Springer Science+Business Media. https://doi.org/10.1007/978-3-319-51133-7_55
Elliott, D., & Soifer, E. (2022). AI Technologies, Privacy, and Security. Frontiers in Artificial Intelligence, 5. https://doi.org/10.3389/frai.2022.826737
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Copyright (c) 2023 Nathaniel Crosley, Richardus Eko Indrajit, Erick Dazki

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