Digital transformation and artificial intelligence in organizations

[thumbnail of Subramaniam-0810.pdf]
Preview
Text - Accepted Version
· Please see our End User Agreement before downloading.
| Preview

Please see our End User Agreement.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Subramaniam, N. (2023) Digital transformation and artificial intelligence in organizations. Journal of Financial Transformation, 58. pp. 90-97. ISSN 1755-361X

Abstract/Summary

Digital transformation revolutionizes how businesses provide value by seamlessly integrating digital technologies into operations, strategies, and culture. Its core objectives encompass enhanced effi ciency, elevated customer experiences, and heightened competitiveness, while ensuring adaptability in the face of swiftly evolving technology and market landscapes. A key enabler in this transformation is artifi cial intelligence (AI), which infuses intelligence and automation into digital technology utilization. AI’s capabilities encompass mining and analyzing diverse organizational data to unearth patterns that drive recommendations and inferences. For instance, customer data analysis unveils preferences, enabling personalized marketing and lucrative opportunities such as cross-selling and up-selling. AI, with its pattern recognition, inference, recommendation, and predictive analytics, is at the forefront of driving digital transformation in organizations. This article proposes a framework for successful digital transformation in organizations.

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/114249
Refereed Yes
Divisions Henley Business School > Finance and Accounting
Publisher CAPCO
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar