Thema4548
Abschlussarbeitstyp: Bachelor, Master
Betreuer: Sebastian Lins
Forschungsgruppe: unbekannt
Partner: Yale University
Archivierungsnummer: 4548
Abschlussarbeitsstatus: Offen
Beginn:
27. Januar 2020
Abgabe: unbekannt
Motivation
Artificial Intelligence (AI) is a topic of ever-increasing relevance in today’s technologies. With the possible application scenarios of AI in companies being as diverse as imaginable, it creates value in every industrial sector where large amounts of data accumulate. However, companies face numerous considerable barriers adopting AI, such as the high cost of computing power or the limited expertise in this domain. Combining the benefits of a cloud environment with the application scenarios of AI has created a powerful new way to adopt AI provided by a third-party provider as a cloud service – so called AI as a Service (AIaaS). However, a holistic view of the determinant factors motivating companies to adopt AI in the form of AIaaS is virtually absent in the literature.
Objectives
The study aims to close this gap by characterizing AIaaS and elaborating the drivers and barriers in its adoption.
Method
Interviews and discussions with experts, such as AIaaS-Providers, companies willing to use these services, consultants...
Literature
- Hesamifard, E., Takabi, H., Ghasemi, M., & Jones, C. (2017). Privacy-preserving Machine Learning in Cloud. In Proceedings of the 2017 on Cloud Computing Security Workshop, Dallas, TX, USA.
- https://www.heise.de/brandworlds/cloud-innovationen/chancen-innovationen/megatrend-ai-as-a-service-was-ist-dran/
- Schneider, Stephan; Sunyaev, Ali (2016): Determinant Factors of Cloud-Sourcing Decisions. https://publikationen.bibliothek.kit.edu/1000091294