Context: In traditional software systems, Requirements Engineering (RE) activities are well-
established and researched. However, building Artificial Intelligence (AI) based software …

In traditional approaches to building software systems (that do not include an Artificial
Intelligent (AI) or Machine Learning (ML) component), Requirements Engineering (RE) …

Abstract Context: Engineering Artificial Intelligence (AI) software is a relatively new area with
many challenges, unknowns, and limited proven best practices. Big companies such as …

Context: Artificial intelligence (AI) components used in building software solutions have
substantially increased in recent years. However, many of these solutions focus on technical …

Good data quality is crucial for any data-driven system's effective and safe operation. For
critical safety systems, the significance of data quality is even higher since incorrect or low …

Becoming a data-driven organization is a vision for several organizations. It has been
frequently mentioned in the literature that data-driven organizations are likely to be more …

Artificial Intelligence (AI) provides organizations with vast opportunities of deploying AI for
competitive advantage such as improving processes, and creating new or enriched products …

Artificial Intelligence (AI) is one of the key drivers of digital transformation and challenges
enterprises to adapt to its various requirements. Many companies fail to implement AI …

The inductive nature of artificial neural models makes dataset quality a key factor of their
proper functionality. For this reason, multiple research studies proposed metrics to assess …

Investigations into the organisational uptake of artificial intelligence (AI) solutions confirm
that there is a growing interest in enterprises and public authorities to use AI. In this context …