Towards an AI-driven business development framework: A multi-case study
Artikel i vetenskaplig tidskrift, 2023

Artificial intelligence (AI) and the use of machine learning (ML) and deep learning (DL) technologies are becoming increasingly popular in companies. These technologies enable companies to leverage big quantities of data to improve system performance and accelerate business development. However, despite the appeal of ML/DL, there is a lack of systematic and structured methods and processes to help data scientists and other company roles and functions to develop, deploy and evolve models. In this paper, based on multi-case study research in six companies, we explore practices and challenges practitioners experience in developing ML/DL models as part of large software-intensive embedded systems. Based on our empirical findings, we derive a conceptual framework in which we identify three high-level activities that companies perform in parallel with the development, deployment and evolution of models. Within this framework, we outline activities, iterations and triggers that optimize model design as well as roles and company functions. In this way, we provide practitioners with a blueprint for effectively integrating ML/DL model development into the business to achieve better results than other (algorithmic) approaches. In addition, we show how this framework helps companies solve the challenges we have identified and discuss checkpoints for terminating the business case.

AI-driven business development framework

machine learning

challenges

deep learning

artificial intelligence

iterations and triggers

Författare

Meenu Mary John

Malmö universitet

Helena Holmstrom Olsson

Malmö universitet

Jan Bosch

Chalmers, Data- och informationsteknik, Interaktionsdesign och Software Engineering

Journal of Software: Evolution and Process

2047-7481 (eISSN)

Vol. 35 6 e2432

Ämneskategorier

Annan data- och informationsvetenskap

Programvaruteknik

Systemvetenskap

DOI

10.1002/smr.2432

Mer information

Senast uppdaterat

2023-07-05