This study synthesizes the current state of research on the application of artificial intelligence (AI) in business decision-making contexts. A comprehensive search strategy was employed to identify relevant studies published between 2015 and 2024. Findings reveal a diverse range of AI applications, including predictive analytics, natural language processing, and recommendation systems, across various business functions such as finance, marketing, and supply chain management. Machine learning algorithms, particularly deep learning, were prominently featured in the literature. Reported benefits of AI adoption include improved decision accuracy, efficiency gains, and enhanced strategic insights, while challenges such as data privacy concerns, algorithmic bias, and organizational resistance were also identified. Furthermore, emerging trends such as explainable AI and human-AI collaboration present opportunities for advancing the field. This review contributes to a comprehensive understanding of the landscape of AI in business decision-making and offers insights for researchers, practitioners, and policymakers seeking to harness the potential of AI in driving organizational success.

Title

Achieving Sustainable Business Through AI, Technology Education and Computer Science

Publisher

Springer Nature Switzerland

Publisher Country

Switzerland

Indexing

Scopus

Impact Factor

None

Publication Type

Online only

Volume

3

Year

2024

Pages

125-135