A multi-criteria decision-making approach applied to Responsible Artificial Intelligence Digital Cloud Transformation Strategy of Organisations. Case study in the health sector
Organisations are committed to understanding both the needs of their customers and the capabilities and plans of their competitors and partners, through the processes of acquiring and evaluating market information in a systematic and anticipatory manner. On the other hand, most organisations in the...
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| Format: | Doctoral thesis |
| Publication date: | 2023 |
| Country: | España |
| Institution: | Universidad Complutense de Madrid (UCM) |
| Repository: | Docta Complutense |
| Language: | English |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/4171 |
| Online Access: | https://hdl.handle.net/20.500.14352/4171 |
| Access Level: | Open access |
| Keyword: | 65.012.123(043.2) Decision making Toma de decisiones Estadística 1209 Estadística |
| Summary: | Organisations are committed to understanding both the needs of their customers and the capabilities and plans of their competitors and partners, through the processes of acquiring and evaluating market information in a systematic and anticipatory manner. On the other hand, most organisations in the last few years have defined that one of their main strategic objectives for the next few years is to become a truly data-driven organisation in the current Big Data and Artificial Intelligence (AI) context (Moreno et al., 2019). They are willing to invest heavily in Data and AI Strategy and build enterprise data and AI platforms that will enable this Market-Oriented vision (Moreno et al., 2019). In this thesis, it is presented a Multicriteria Decision Making (MCDM) model (Saaty, 1988), an AI Digital Cloud Transformation Strategy and a cloud conceptual architecture to help AI leaders and organisations with their Responsible AI journey, capable of helping global organisations to move from the use of data from descriptive to prescriptive and leveraging existing cloud services to deliver true Market-Oriented in a much shorter time (compared with traditional approaches)... |
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