CYMar 12
The Landscape of Generative AI in Information Systems: A Synthesis of Secondary Reviews and Research AgendasAleksander Jarzębowicz, Adam Przybyłek, Jacinto Estima et al.
As organizations grapple with the rapid adoption of Generative AI (GenAI), this study synthesizes the state of knowledge through a systematic literature review of secondary studies and research agendas. Analyzing 28 papers published since 2023, we find that while GenAI offers transformative potential for productivity and innovation, its adoption is constrained by multiple interrelated challenges, including technical unreliability (hallucinations, performance drift), societal-ethical risks (bias, misuse, skill erosion), and a systemic governance vacuum (privacy, accountability, intellectual property). Interpreted through a socio-technical lens, these findings reveal a persistent misalignment between GenAI's fast-evolving technical subsystem and the slower-adapting social subsystem, positioning IS research as critical for achieving joint optimization. To bridge this gap, we discuss a research agenda that reorients IS scholarship from analyzing impacts toward actively shaping the co-evolution of technical capabilities with organizational procedures, societal values, and regulatory institutions--emphasizing hybrid human--AI ensembles, situated validation, design principles for probabilistic systems, and adaptive governance.
SEApr 22, 2020
Applying Normalization Process Theory to Explain Large-Scale Agile TransformationsNoel Carroll, Kieran Conboy
Given the prevalence and effectiveness of agile methods at a team level, large organizations are now attempting to mimic this success at large scale by adopting large-scale methods such as Scaled Agile Framework (SAFe), Spotify, and Large Scale Scrum (LeSS). However, compared to insights on traditionally small scale methods, the extant literature provides sparse coverage on theories to examine large-scale agile transformations. In this article, we focus on the challenge of normalizing large scale agile transformations and apply Normalization Process Theory (NPT) to support theorize about this process. We present our initial case study findings and outline future research on the application of NPT for large-scale transformations. From a research and practice perspective, we explain how NPT can be adopted to focus on the processes of embedding and sustaining practices, activities which are very often ignored, yet central to the success or failure of transformations.
SEJan 23, 2019
Implementing Large-Scale Agile Frameworks: Challenges and RecommendationsKieran Conboy, Noel Carroll
Based on 13 agile transformation cases over 15 years, this article identifies nine challenges associated with implementing SAFe, Scrum-at-Scale, Spotify, LeSS, Nexus, and other mixed or customised large-scale agile frameworks. These challenges should be considered by organizations aspiring to pursue a large-scale agile strategy. This article also provides recommendations for practitioners and agile researchers.