Riding a bicycle while building its wheels: The process of machine learning-based capability development and IT-business alignment practices
Mucha,Tomasz Ma,Sijia Abhari,Kaveh
Mucha,Tomasz
Ma,Sijia
Abhari,Kaveh
Abstract
Purpose Recent advancements in Artificial Intelligence (AI) and, at its core, Machine Learning (ML) offer opportunities for organizations to develop new or enhance existing capabilities. Despite the endless possibilities, organizations face operational challenges in harvesting the value of ML-based capabilities (MLbC), and current research has yet to explicate these challenges and theorize their remedies. To bridge the gap, this study explored the current practices to propose a systematic way of orchestrating MLbC development, which is an extension of ongoing digitalization of organizations. Design/methodology/approach Data were collected from Finland's Artificial Intelligence Accelerator (FAIA) and complemented by follow-up interviews with experts outside FAIA in Europe, China and the United States over four years. Data were analyzed through open coding, thematic analysis and cross-comparison to develop a comprehensive understanding of the MLbC development process. Findings The analysis identified the main components of MLbC development, its three phases (development, release and operation) and two major MLbC development challenges: Temporal Complexity and Context Sensitivity. The study then introduced Fostering Temporal Congruence and Cultivating Organizational Meta-learning as strategic practices addressing these challenges. Originality/value This study offers a better theoretical explanation for the MLbC development process beyond MLOps (Machine Learning Operations) and its hindrances. It also proposes a practical way to align ML-based applications with business needs while accounting for their structural limitations. Beyond the MLbC context, this study offers a strategic framework that can be adapted for different cases of digital transformation that include automation and augmentation of work.
Description
Publisher Copyright: © 2023, Tomasz Mucha, Sijia Ma and Kaveh Abhari.
Date
2023-07
Journal Title
Journal ISSN
Volume Title
Publisher
Research Projects
Organizational Units
Journal Issue
Keywords
Machine learning, machine learning operations (MLOps), IT capabilities, IT-business alignment, process model, artificial intelligence (AI), development operations (DevOps), temporality, context sensitivity, capability development, digitalization, digital transformation
Citation
Mucha, T, Ma, S & Abhari, K 2023, 'Riding a bicycle while building its wheels: The process of machine learning-based capability development and IT-business alignment practices', Internet Research, vol. 33, no. 7, pp. 168-205. https://doi.org/10.1108/INTR-10-2022-0769