HOW BI/ANALYTICS TECHNOLOGIES AND ENTERPRISE SEARCH SUPPORT THE USE OF KNOWLEDGE IN DECISION-MAKING IN PRIVATE ORGANIZATIONS: A SYSTEMATIC LITERATURE REVIEW
TL;DR
The study concludes that knowledge-support technologies generate greater value when combined with organizational capabilities and governance strategies capable of transforming information into actionable decisions.
Abstract
This systematic literature review investigates how Business Intelligence and Analytics (BI/Analytics) technologies and enterprise search mechanisms support knowledge use in decision-making processes within private organizations. The study addresses a research gap regarding the integration of knowledge management, analytical systems, semantic search, generative artificial intelligence, and decision support systems. The review followed PRISMA 2020 and PRISMA-S guidelines and used the OpenAlex database to retrieve open-access articles published between 2021 and 2025 in English and Portuguese. After identification, screening, and quality assessment procedures, six studies were included in the final synthesis. The findings indicate that analytical technologies, enterprise search systems, ontology-based approaches, and AI-supported solutions operate complementarily to reduce cognitive effort, improve access to organizational knowledge, and enhance decision quality and speed. However, the observed benefits depend on factors such as information governance, data quality, analytical maturity, digital competencies, and knowledge management routines. The review also highlights challenges associated with the adoption of these technologies, including organizational resistance, information integration issues, algorithmic bias, and risks related to generative AI. The study concludes that knowledge-support technologies generate greater value when combined with organizational capabilities and governance strategies capable of transforming information into actionable decisions.