The emerging information revolution makes it necessary to manage vast amounts of unstructured data rapidly. As the world is increasingly populated by IoT devices and sensors that can sense their surroundings and communicate with each other, a digital environment has been created with vast volumes of volatile and diverse data. Traditional AI and machine learning techniques designed for deterministic situations are not suitable for such environments. With a large number of parameters required by each device in this digital environment, it is desirable that the AI is able to be adaptive and self-build (i.e. self-structure, self-configure, self-learn), rather than be structurally and parameter-wise pre-defined. This study explores the benefits of self-building AI and machine learning with unsupervised learning for empowering big data analytics for smart city environments. By using the growing self-organizing map, a new suite of self-building AI is proposed. The self-building AI overcomes the limitations of traditional AI and enables data processing in dynamic smart city environments. With cloud computing platforms, the self-building AI can integrate the data analytics applications that currently work in silos. The new paradigm of the self-building AI and its value are demonstrated using the IoT, video surveillance, and action recognition applications.

Purpose: The purpose of this paper is to investigate the associations among knowledge-oriented leadership (KOL), knowledge worker satisfaction (KWS), knowledge worker productivity (KWP) and organizational performance (OP). The study hypothesizes that the explicit mixtures, i.e. KOL, KWS and KWP can improve OP.Design/methodology/approach: The study sample was composed of 248 academicians and management staff of higher educational institutes (HEIs). The relations were tested through Smart PLS 3.2.9. The fuzzy-set qualitative comparative analysis (fsQCA) method was also used for examining configurational paths.Findings: The study found a substantial direct influence of KOL on OP. The findings revealed that KOL significantly affects KWS, and KWS enhances KWP, which ultimately improves the OP of HEIs. Grounded on the fsQCA, the outcomes exposed configurational trails to the enhanced OP.Originality/value: There is scarce of studies that determine the connection of KOL, KWS, KWP and OP. This is one of the preliminary studies that examine the association of KOL, KWS, KWP and OP in HEIs. From a procedural viewpoint, the research subsidizes by merging symmetric and asymmetric tools to further understand structural issues. The use of fsQCA discloses numerous paths to improve OP and renders asymmetric relations. fsQCA also aids to comprehend the relations that might not be directly understandable via symmetric means.