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  4. Rethinking AI Design Practices: A Reference Architecture for Generative AI Systems
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Rethinking AI Design Practices: A Reference Architecture for Generative AI Systems

Journal
European Conference on Information Systems (ECIS)
Type
conference paper
Date Issued
2025
Author(s)
Marc Christopher Grau  
;
Reinhard, Philipp
;
Ingrid Bauer-Hänsel  
;
Ivo Blohm  
Research Team
IWI6
Abstract
Generative AI (GenAI) holds the potential to transform various facets of society. While research and practice increasingly explore its diverse use cases and assess its impact, many companies continue to face significant challenges in designing and developing advanced GenAI systems, hindering their ability to derive value from these technologies. To address these challenges and offer guidance on emerging GenAI development practices, we propose a reference architecture that highlights key design decisions. Using a design science research approach, we developed the reference architecture informed by consortium workshops, literature reviews, and expert interviews. The reference architecture is grounded in eight key design requirements and serves as a strategic guide to streamline system design and assist organisational decision-making and communication. Additionally, the architecture contributes to the academic discourse by offering a structured framework for future research on the design peculiarities of GenAI systems, helping bridge the gap between practical implementations and theoretical insights.
Language
English
Keywords
Generative Artificial Intelligence
Large Language Models
Foundation Models
Reference Architecture
Design Science Research
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
Aisel
Pages
17
Event Title
European Conference on Information Systems (ECIS)
Event Location
Amman, Jordan
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/122882
Subject(s)

information managemen...

Division(s)

IWI - Institute of In...

File(s)
Thumbnail Image

open.access

Name

JML_1032.pdf

Size

618.04 KB

Format

Adobe PDF

Checksum (MD5)

f787be7a7d882d5413be4667688c9e46

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