AI governance: the IPA case : A Bosch Home Comfort case study
Manoukian, Guillaume (2023-06-15)
AI governance: the IPA case : A Bosch Home Comfort case study
(15.06.2023)
Julkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty.
avoin
Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2023073192049
https://urn.fi/URN:NBN:fi-fe2023073192049
Tiivistelmä
This thesis examines the crucial issue of AI governance in companies and addresses the lack of clear governance frameworks that facilitate adopting and maximizing AI benefits.
Through a qualitative approach involving ten participants from the Bosch environment (Belgium, Netherlands, Germany, and Portugal), this study investigates the implementation of AI-driven tools and proposes insights for effective governance.
Companies should prioritize implementing Intelligent Process Automation by leveraging precise analyses and establishing clear internal guidelines. Moreover, creating dedicated teams, such as a data team, can significantly contribute to automating processes across different departments.
This research is built upon existing literature and knowledge in the field while providing unique insights by incorporating an internal perspective within Bosch. In practice, the recommendations from this study can be applied by creating specific teams within the company and emphasizing comprehensive documentation of AI processes and guidelines.
Further research could explore developing tailored approaches to suit specific company requirements. It is essential to acknowledge that a limitation of this study is the perpetual evolution of IPA.
Through a qualitative approach involving ten participants from the Bosch environment (Belgium, Netherlands, Germany, and Portugal), this study investigates the implementation of AI-driven tools and proposes insights for effective governance.
Companies should prioritize implementing Intelligent Process Automation by leveraging precise analyses and establishing clear internal guidelines. Moreover, creating dedicated teams, such as a data team, can significantly contribute to automating processes across different departments.
This research is built upon existing literature and knowledge in the field while providing unique insights by incorporating an internal perspective within Bosch. In practice, the recommendations from this study can be applied by creating specific teams within the company and emphasizing comprehensive documentation of AI processes and guidelines.
Further research could explore developing tailored approaches to suit specific company requirements. It is essential to acknowledge that a limitation of this study is the perpetual evolution of IPA.