Open Access
American Research Journal of Computer Science and Information Technology
ISSN (Online): 2572-2921
DOI: 10.46568/arjcsit
Approaches for Adopting AI-Powered Business Intelligence in the Organization to Ensure Consistent Decision-Making
Abstract
Integrating Artificial Intelligence (AI) into Business Intelligence (BI) is fundamentally transforming how organizations
process data and make decisions. This article analyzes current trends in AI applications within BI, focusing on key
innovations such as augmented analytics, generative AI assistants, automated machine learning models, and neural
networks. These advancements enable non-technical users to extract insights independently, enhance data preparation,
and facilitate informed decision-making, thereby democratizing access to data analytics.
Despite these benefits, the adoption of AI-driven BI introduces significant challenges. These include accountability for
AI-assisted decisions, ethical governance to prevent biases in AI models, cost implications associated with implementing
large language models, and data security and privacy concerns. The article discusses the crucial role of Explainable AI
(XAI) in providing transparency and building user trust. It also outlines strategies for mitigating biases, conducting cost
benefit analyses, and establishing robust data governance policies.
By addressing both the opportunities and the challenges, the article proposes comprehensive approaches for integrating
AI-oriented solutions into organizational processes. This ensures consistent, ethical, and effective decision-making,
aligning technological advancements with business objectives.
