Paper Number
2181
Paper Type
Complete Research Paper
Abstract
Artificial intelligence (AI) provides immense opportunities for an efficient and lean public administration. However, since AI is a general-purpose technology, there is a need for conducting AI fitness assessments against organisational-specific problem(s). This requires a pilot stage before an adoption decision is made. However, despite several promising AI pilot projects underway within the Canadian public administration, few have transitioned into production solutions. Through a qualitative study based on in-depth semi-structured interviews (n=37) within Canadian public administration, this paper explores the AI adoption process. The results enumerate two pathways to AI initiation: problem-driven and solution-problem pairing. The paper identifies the existence of a significant AI operationalisation chasm as a major barrier to operationalising AI pilots. This chasm results from technical debt, silos, and a lack of processes for managing AI tensions. The paper contributes to the AI adoption and diffusion literature and provides practitioner recommendations for crossing the AI chasm.
Recommended Citation
Madan, Rohit and Ashok, Mona, "AI Operationalisation Chasm: Evidence from Canadian Public Administration" (2024). ECIS 2024 Proceedings. 11.
https://aisel.aisnet.org/ecis2024/track20_adoption/track20_adoption/11
AI Operationalisation Chasm: Evidence from Canadian Public Administration
Artificial intelligence (AI) provides immense opportunities for an efficient and lean public administration. However, since AI is a general-purpose technology, there is a need for conducting AI fitness assessments against organisational-specific problem(s). This requires a pilot stage before an adoption decision is made. However, despite several promising AI pilot projects underway within the Canadian public administration, few have transitioned into production solutions. Through a qualitative study based on in-depth semi-structured interviews (n=37) within Canadian public administration, this paper explores the AI adoption process. The results enumerate two pathways to AI initiation: problem-driven and solution-problem pairing. The paper identifies the existence of a significant AI operationalisation chasm as a major barrier to operationalising AI pilots. This chasm results from technical debt, silos, and a lack of processes for managing AI tensions. The paper contributes to the AI adoption and diffusion literature and provides practitioner recommendations for crossing the AI chasm.
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