Integrating machine learning into business and management in the age of artificial intelligence
Summary
The article explores the integration of machine learning in business and management, analyzing its applications, challenges, and the intellectual landscape based on a review of over 9,399 documents.
Why It Matters
Understanding the role of machine learning in business is crucial as companies seek to enhance efficiency and competitiveness. This study provides a structured overview of existing research and identifies key areas for future exploration, helping organizations navigate the complexities of AI integration.
Key Takeaways
- Machine learning significantly influences business and management practices.
- The study identifies 15 clusters of research on machine learning applications.
- Companies face challenges like the digital divide and security concerns when adopting machine learning.
- Strategic considerations are essential for effective machine learning integration.
- The article serves as a foundational resource for firms looking to implement machine learning.
Download PDF Subjects Business and managementInformation systems and information technology AbstractMachine learning, with its capacity to leverage computational techniques for experiential learning, has profoundly influenced various disciplines, including business and management. Despite its contributions to the progress of these fields and the advent of artificial intelligence presenting new challenges, there remains ambiguity regarding the specific areas of significant advancement and those with potential for further development. This study addresses three central questions: (1) How is the intellectual landscape of machine learning in business and management research organized and structured? (2) What are the primary applications of machine learning in business administration? And (3) What strategic considerations should companies adopt to effectively leverage machine learning in their business applications? By means of co-occurrence analysis of over 9399 peer-reviewed documents retrieved from Scopus discussing machine learning in business and management, we identified fifteen clusters within the literature. This classification serves as a starting point for firms looking to integrate ML into their routines across fifteen distinct topics. Although some firms have appropriated ML, the upsurge of artificial intelligence presents new challenges, including the digital divide, infrastructure and acquisition dilemmas, security concerns especially with outsourced services, and...
