English
Bibtex
Cite as text
@Select Types{,
Journal = "Band-1",
Title= "Developing Purposeful AI Use Cases – A Structured Method and Its Application in Project Management",
Author= "Peter Hofmann, Jan Jöhnk, Dominik Protschky, and Nils Urbach",
Doi= "https://doi.org/10.30844/wi_2020_a3-hofmann",
Abstract= "An appropriate problem-solution-fit is essential to develop purposeful artificial intelligence (AI) applications. However, in domains with an unintuitive problem-solution-fit, such as project management (PM), organizations require methodological guidance. Hence, we propose a five-step method to develop organization-specific AI use cases: First, companies must consider the context factors technology, organization (in particular data and application domain), and environment. Second, companies must identify existing domain problems and AI solutions. Third, our method facilitates abstraction to understand the underlying nature of the identified problems and AI solutions. Fourth, our problem-solution-matrix assists companies to match AI functions with the domain context. Fifth, companies derive necessary implications for the subsequent use case implementation. To construct and evaluate our method, we followed the design science research paradigm complemented by situational method engineering and based on 14 interviews. Our method addresses a relevant practical problem and contributes to identifying purposeful AI use cases in unintuitive application domains.",
Keywords= "Artificial Intelligence, Project Management, Use Case Development, Design Science Research, Situational Method Engineering.
",
}
Peter Hofmann, Jan Jöhnk, Dominik Protschky, and Nils Urbach: Developing Purposeful AI Use Cases – A Structured Method and Its Application in Project Management. Online: https://doi.org/10.30844/wi_2020_a3-hofmann (Abgerufen 25.12.24)
Open Access
Abstract
Abstract
An appropriate problem-solution-fit is essential to develop purposeful artificial intelligence (AI) applications. However, in domains with an unintuitive problem-solution-fit, such as project management (PM), organizations require methodological guidance. Hence, we propose a five-step method to develop organization-specific AI use cases: First, companies must consider the context factors technology, organization (in particular data and application domain), and environment. Second, companies must identify existing domain problems and AI solutions. Third, our method facilitates abstraction to understand the underlying nature of the identified problems and AI solutions. Fourth, our problem-solution-matrix assists companies to match AI functions with the domain context. Fifth, companies derive necessary implications for the subsequent use case implementation. To construct and evaluate our method, we followed the design science research paradigm complemented by situational method engineering and based on 14 interviews. Our method addresses a relevant practical problem and contributes to identifying purposeful AI use cases in unintuitive application domains.
Keywords
Schlüsselwörter
Artificial Intelligence, Project Management, Use Case Development, Design Science Research, Situational Method Engineering.
References
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