Nthubu, Boineelo R and Raza, Hassan (2025) Deciphering And Evolution of AI Practices. In: UK Academy for Information Systems (UKAIS) International Conference, 2025-04-23 - 2025-04-24, Newcastle Business School.
Full text not available from this repository.Abstract
There is a rapid increase in AI-based systems using NLP-based conversational assistants and AI agents for task augmentation and automation. However, despite the advancements in AI technology, challenges persist regarding the different interpretations of Responsible, Trustworthy and Explainable AI, as well as understanding the evolution of their practices. Using a systematic literature review, we will explore the relationships between responsible, trustworthy, and explainable AI in the organisational context. Furthermore, we will use a practice-based approach to identify the best practices for AI implementations and investigate how these practices evolve when they are situated in different organisational contexts. We will use a qualitative multiple case study design with semi-structured interviews in two organisations: a recruitment company with an AI platform for customers and a telecommunications company using AI for customer services. This research will contribute to IS literature by identifying the different types of responsible, trustworthy, and explainable AI best practices and how they evolve.