Breaking the Vicious Circle: Why AI for software analytics and business intelligence does not take off in practice
Paper in proceedings, 2020

In recent years, the application of artificial intelligence (AI) has become an integral part of a wide range of areas, including software engineering. By analyzing various data sources generated in software engineering, it can provide valuable insights into customer behavior, product performance, bugs and errors, and many more. In practice, however, AI for software analytics and business intelligence often gets stuck in a prototypical stage and the results are rarely used to make decisions based on data. To understand the underlying root causes of this phenomenon, we conduct both an explanatory case study and a survey on the challenges of realizing and utilizing artificial intelligence in the context of software-intensive businesses. As a result, we identify a vicious circle that prevents practitioners from moving from prototypical analytics to continuous and productively usable software analytics and business intelligence based on AI.

Data-driven software engineering

business intelligence

software analytics

Author

Iris Figalist

Siemens

Christoph Elsner

Siemens

Jan Bosch

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers), Software Engineering for Testing, Requirements, Innovation and Psychology

Helena Holmström Olsson

Malmö university

Proceedings - 46th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2020

5-12 9226335

46th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2020
Kranj, Slovenia,

Subject Categories

Other Mechanical Engineering

Other Engineering and Technologies not elsewhere specified

Software Engineering

DOI

10.1109/SEAA51224.2020.00013

More information

Latest update

12/16/2020