AI Integration Methodology: Does One Size Fit All?

The rapid evolution of Generative AI is reshaping the Information Systems (IS) landscape, transforming how organizations retrieve knowledge, support decision-making, and co-create value. Yet for many educators and practitioners, a clear, actionable methodology for integrating this powerful technology into enterprise or academic environments remains elusive. This Professional Development Symposium introduces and discusses a structured, human-centered approach to AI deployment that emphasizes mutual trust and coordinated action in complex, dynamic contexts. This session will appeal to a broad AMCIS audience, including researchers, educators, and practitioners engaged in digital transformation, IS curriculum development, AI ethics, and socio-technical systems. It is particularly relevant to multiple SIGs, such as SIGOSRA, SIGED, SIGAI, and SIGGreen, and seeks to foster interdisciplinary dialogue on how best to prepare both learners and organizations for the AI era. Through a combination of conceptual framing, real-world case studies, and interactive activities, participants will explore the flexibility and relevance of this methodology across diverse educational and organizational settings. By encouraging an open exchange of experiences and perspectives, this PDS aims to deliver immediate pedagogical value and cultivate long-term collaboration. The session culminates in a critical conversation on the provocative question: Does one size fit all in AI integration?

Institutions

Publication Details

Journal
Journal of the Association for Information Systems
Published
2025-08-16
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI Integration Methodology: Does One Size Fit All?

Journal of the Association for Information Systems
Ethics and Social Impacts of AI
article

AI Integration Methodology: Does One Size Fit All?

article en

Abstract

The rapid evolution of Generative AI is reshaping the Information Systems (IS) landscape, transforming how organizations retrieve knowledge, support decision-making, and co-create value. Yet for many educators and practitioners, a clear, actionable methodology for integrating this powerful technology into enterprise or academic environments remains elusive. This Professional Development Symposium introduces and discusses a structured, human-centered approach to AI deployment that emphasizes mutual trust and coordinated action in complex, dynamic contexts. This session will appeal to a broad AMCIS audience, including researchers, educators, and practitioners engaged in digital transformation, IS curriculum development, AI ethics, and socio-technical systems. It is particularly relevant to multiple SIGs, such as SIGOSRA, SIGED, SIGAI, and SIGGreen, and seeks to foster interdisciplinary dialogue on how best to prepare both learners and organizations for the AI era. Through a combination of conceptual framing, real-world case studies, and interactive activities, participants will explore the flexibility and relevance of this methodology across diverse educational and organizational settings. By encouraging an open exchange of experiences and perspectives, this PDS aims to deliver immediate pedagogical value and cultivate long-term collaboration. The session culminates in a critical conversation on the provocative question: Does one size fit all in AI integration?

Journal of the Association for Information Systems
Université de Sherbrooke (CA)
Peace, Justice and strong institutions
Openalex Percentile: Top 44%
Ethics and Social Impacts of AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.