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Titlebook: Embedding Artificial Intelligence into ERP Software ; A Conceptual View on Siar Sarferaz Book 2024 The Editor(s) (if applicable) and The Au

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Solution Architecturelities, ERP reference processes, ERP reference architecture, and ERP application patterns for artificial intelligence build the foundation for the solution architecture that we propose in this chapter. There are simple use cases like trending and predictions, which can be served with classic algorit
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Life Cycle Managementgence, new artifacts and processes are introduced that must be considered from the life cycle management perspective. For example, artificial intelligence models must be trained, deployed, activated, and monitored. Those aspects are not covered by classic life cycle management tools and concepts. ER
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Data Protection and Data Privacylegal requirements. Thus, processing of artificial intelligence must be compliant with data protection and data privacy legislations. For example, the training job must only consider personal data for which consent is given. Compliance must be ensured for all aspects of General Data Protection Regul
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Model Degradationpower of artificial intelligence models decreases due to changes in the data environment. Determining this time point and triggering retraining is the objective of model degradation. However, this is a challenging task as in addition to statistical techniques, feedback of the users is required and a
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