The Role of AI-Driven Automation in Enhancing Administrative Efficiency for U.S. Small Businesses: A Conceptual Design of the AdminAI Pro System

Siqi You

doi:10.71222/f8n9nw45

Authors

Siqi You University of Southern California, Los Angeles, CA, 90007, USA Author

DOI:

https://doi.org/10.71222/f8n9nw45

Keywords:

administrative automation, artificial intelligence, small business productivity, workflow optimization, digital transformation, AdminAI Pro

Abstract

U.S. small businesses face mounting administrative burdens due to intensifying regulatory requirements, fragmented documentation flows, and increasingly complex communication channels. Existing automation solutions are often either overly simple or built for enterprise-scale organizations, leaving small businesses with limited feasible options. This paper presents an expanded conceptual design for AdminAI Pro, a unified AI-driven automation system tailored to the structural, economic, and organizational realities of U.S. small enterprises. Rather than offering empirical findings, this paper develops a comprehensive theoretical model describing the system's architecture, workflow logic, intelligent components, and anticipated organizational impacts. The goal is to offer a deep, integrative conceptual framework that may guide future prototype development and empirical evaluation.

References

1. E. Brynjolfsson, and A. McAfee, "The second machine age: Work, progress, and prosperity in a time of brilliant technologies," WW Norton & company, 2014.

2. T. H. Davenport, "The AI advantage: How to put the artificial intelligence revolution to work," mit Press, 2018.

3. Y. LeCun, Y. Bengio, and G. Hinton, "Deep learning," nature, vol. 521, no. 7553, pp. 436-444, 2015. doi: 10.1038/nature14539

4. G. C. Kane, R. Nanda, A. N. Phillips, and J. R. Copulsky, "The transformation myth: Leading your organization through uncertain times," MIT Press, 2021.

5. M. E. Porter, and J. E. Heppelmann, "How smart, connected products are transforming companies," Harvard business review, vol. 93, no. 10, pp. 96-114, 2015.