| 1. |
- Griesch, L., et al.
(författare)
-
Towards AI as a Service for Small and Medium-Sized Enterprises (SME)
- 2024
-
Ingår i: The Practice of Enterprise Modeling. - : Springer. - 9783031485824 - 9783031485831 ; , s. 37-53
-
Konferensbidrag (refereegranskat)abstract
- AI-as-a-Service (AIaaS) combines Artificial Intelligence (AI) and cloud computing to make AI accessible to enterprises without implementing complex solutions or technologies on-premise. Many small and medium-sized enterprises (SME) that lack competencies in the AI and technology sector consider AIaaS as a promising option to implement AI solutions. However, the differences between AIaaS and AI on-premise have not attracted much research. The intention of this paper is to contribute to this area by analysing the literature in the field and investigating a concrete example in more detail. Exploring AIaaS is crucial to better understand the opportunities and limitations of AI services. The contributions of the paper are (a) an analysis of the literature on AIaaS to identify factors affecting AI implementation and how AIaaS solutions differ from on-premise solutions when introducing AI in a company, (b) a case study of an SME that compares AIaaS and AI on-premise in practice, and (c) the application potential of a morphological box to compare AIaaS and AI on-premise.
|
|
| 2. |
- Rittelmeyer, J. D., et al.
(författare)
-
A Morphological Box for AI Solutions : Evaluation, Refinement and Application Potentials
- 2023
-
Ingår i: Advanced Information Systems Engineering Workshops. - : Springer. - 9783031349843 - 9783031349850 ; , s. 5-16
-
Konferensbidrag (refereegranskat)abstract
- The understanding of the concepts of AI is still one of the major problems for companies that want to implement AI solutions, from our own experience. Because of that, we presented an initial version of a morphological box that supports the understanding of AI solutions in previous work [1]. We now evaluated the morphological box with expert interviews from different domains and a short literature search. We present the planning, conduction and analysis of the interviews as well as a refined version of the morphological box for AI solutions. For the analysis we used the approach of qualitative content analysis by Mayring & Fenzl [2]. The interviews helped to identify several new features and values and they offered interesting insights into important aspects for AI introduction and into the introduction process itself from practitioners’ perspectives. Furthermore, we illustrate some of the boxes application potential along the information system development process and future improvement and application potentials.
|
|
| 3. |
- Rittelmeyer, J. D., et al.
(författare)
-
A Survey to Evaluate the Completeness and Correctness of a Morphological Box for AI Solutions
- 2024
-
Ingår i: Advanced Information Systems Engineering Workshops. - : Springer. - 9783031610028 - 9783031610035 ; , s. 115-129
-
Konferensbidrag (refereegranskat)abstract
- Artificial Intelligence (AI) is a key technology driving digital transformation in enterprises worldwide. However, the implementation of AI projects often faces hurdles, primarily due to misconceptions about AI’s capabilities and suitable applications. This research represents a step in a broader research process aimed at creating an artifact to help companies, particularly those outside the IT sector, navigate these challenges. We present an evaluation of a morphological box that outlines critical factors for successful AI integration. The evaluation was carried out by conducting and analyzing a survey in which participants rated the individual features and values, as well as their structure. We also conducted the Kaiser-Meyer-Olkin and Bartlett tests and created a correlation matrix as statistical measures to identify overlap between the elements of the box. After analyzing the data, we found some further room for improvement but that the box seems to include the generally most important aspects. Overall, the participants’ ratings for the individual elements were also satisfactory.
|
|
| 4. |
- Rittelmeyer, J. D., et al.
(författare)
-
Morphological Box for AI Solutions : Evaluation and Refinement with a Taxonomy Development Method
- 2023
-
Ingår i: Perspectives in Business Informatics Research. - : Springer. - 9783031431258 - 9783031431265 ; , s. 145-157
-
Konferensbidrag (refereegranskat)abstract
- Investigations into the organisational uptake of artificial intelligence (AI) solutions confirm that there is a growing interest in enterprises and public authorities to use AI. In this context, the lack of understanding of AI concepts in organisations is a significant challenge. As a contribution to addressing this issue, we previously developed and evaluated a morphological box for AI solutions. To further refine this morphological box, the paper follows a well-established scientific method for this purpose: This paper presents the application of a taxonomy development method to our morphological box. We use this method to determine a meta-characteristic, identify the target audience, project the use of the morphological box, and define both subjective and objective ending conditions. We describe several iterations of the development and evaluation loops and present our final results. Our analysis demonstrates the effectiveness of the taxonomy development method in refining and enhancing the morphological box for AI solutions. We further present the application of the morphological box for classifying AI projects with four initial case studies, discuss the results as well as further development directions and potentials of the box.
|
|
| 5. |
- Sandkuhl, Kurt, 1963-, et al.
(författare)
-
Use of EA Models in Organizational AI Solution Development
- 2022
-
Ingår i: Advances in Enterprise Engineering XV. - Cham : Springer. - 9783031115196 - 9783031115202 ; , s. 149-166
-
Konferensbidrag (refereegranskat)abstract
- Digital transformation in combination with service ecosystems exploit and incorporate innovative technologies, such as artificial intelligence, Internet of things or data analytics. For most enterprises, new digital business models and participation in service eco-systems lead to severe changes of the enterprise architecture (EA) and the need for methodical support to systematically perform the resulting change process. The focus of this paper is on the implementation of AI applications in organizations. Based on the analysis of industrial case studies, our observation is that different kinds of AI applications require different prerequisites in an organizational IT landscape, some of which can be found in an EA model, and some enterprises intend to use AI but are not prepared for it. The work investigates, what information can be harvested from EA models to support requirements engineering and the evaluation of organizational readiness for AI planning and implementation. The main contributions of our work are (a) an enhanced and updated literature analysis on EA use for AI introduction, (b) an analysis of differences in requirements of different kinds of AI applications, and (c) an improved AI context analysis method prepared for addressing these differences. The improved method exploits insights gained in our work on what information regarding the requirements can be extracted from EA models.
|
|
