Author(s)

Jianwei Ma ¹, Qi Tian ¹

Affiliation(s)

¹ School of Economics and Management, Lanzhou University of Technology, Lanzhou, Gansu, China

Corresponding Author

Jianwei Ma

ABSTRACT

With the rapid development of science and technology, enterprises are further promoting intelligent transformation to adapt to the needs of social development. Technologies such as artificial intelligence are widely used in financial management and other aspects of enterprises, injecting new development momentum into enterprises. RPA financial robots have had an important impact on the digital transformation of corporate finance. With the in-depth development of AI technology, enterprises have higher and higher demands for intelligence. Based on RPA, the application of IPA (Intelligent Process Automation), which incorporates the complexity of AI, will be more popular. In enterprises, the financial system serves as a hub connecting the enterprise's production, operation, sales and other business activities. Many enterprises choose to build financial shared service centers to centralize some businesses to improve efficiency and reduce costs. Combining financial skills and work with new technologies such as RPA and AI to improve the service quality of financial shared service centers. The use of RPA financial robots, combined with the powerful deep learning capabilities of AI, can enable the financial field to apply AI technology to independently collect and analyze information like humans do, and make business decisions on behalf of humans, responding to customer needs faster and ensuring service quality. This paper explains how "AI+RPA" promotes the intelligent development of enterprise financial shared service centers from the connotation, advantages and application of "AI+RPA" in enterprise financial shared service centers.

KEYWORDS

Artificial Intelligence, Robotics Process Automation, Financial Shared Service Center

CITE THIS PAPER

Jianwei Ma, Qi Tian, "AI+RPA" and the Intelligent Development of Enterprise Financial Shared Service Centers. Journal of Artificial Intelligence Practice (2024) Vol. 7: 95-101. DOI: http://dx.doi.org/10.23977/jaip.2024.070311.

REFERENCES

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