TY - GEN
T1 - AI Transformation in the Public Sector
T2 - 33rd Annual Workshop of the Swedish Artificial Intelligence Society, SAIS 2021
AU - Peretz-Andersson, Einav
AU - Lavesson, Niklas
AU - Bifet, Albert
AU - Mikalef, Patrick
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/6/14
Y1 - 2021/6/14
N2 - Real-world application of data-driven and intelligent systems (AI) is increasing in the private and public sector as well as in society at large. Many organizations transform as a consequence of increased AI implementation. The consequences of such transformations may include new recruitment plans, procurement of additional IT, changes in existing positions and roles, new business models, as well as new policies and regulations. However, it is unclear how this transformation varies across different types of organizations. We study the effects of bottom-up approaches, such as pilot projects and mentoring to specific groups within organizations, and aim to explore how such approaches can complement the top-down approach of strategic AI implementation. Our context is the public sector. Our goal is to acquire an improved understanding of how and when AI transformation occurs in the public sector, which are the consequences, and which strategies are fruitful or detrimental to the organization. We aim to study public sector organizations in Sweden, Norway, New Zealand, Germany, and The Netherlands to learn about potential similarities and differences with regard to AI transformation.
AB - Real-world application of data-driven and intelligent systems (AI) is increasing in the private and public sector as well as in society at large. Many organizations transform as a consequence of increased AI implementation. The consequences of such transformations may include new recruitment plans, procurement of additional IT, changes in existing positions and roles, new business models, as well as new policies and regulations. However, it is unclear how this transformation varies across different types of organizations. We study the effects of bottom-up approaches, such as pilot projects and mentoring to specific groups within organizations, and aim to explore how such approaches can complement the top-down approach of strategic AI implementation. Our context is the public sector. Our goal is to acquire an improved understanding of how and when AI transformation occurs in the public sector, which are the consequences, and which strategies are fruitful or detrimental to the organization. We aim to study public sector organizations in Sweden, Norway, New Zealand, Germany, and The Netherlands to learn about potential similarities and differences with regard to AI transformation.
U2 - 10.1109/SAIS53221.2021.9483960
DO - 10.1109/SAIS53221.2021.9483960
M3 - Conference contribution
AN - SCOPUS:85111588622
T3 - 33rd Workshop of the Swedish Artificial Intelligence Society, SAIS 2021
BT - 33rd Workshop of the Swedish Artificial Intelligence Society, SAIS 2021
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 14 June 2021 through 15 June 2021
ER -