Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

An Experimental Case Study on How AI May Improve Communication and Resource Allocation

Version 1 : Received: 13 March 2023 / Approved: 14 March 2023 / Online: 14 March 2023 (09:59:51 CET)

How to cite: Obinnaya Chikezie Victor, N. An Experimental Case Study on How AI May Improve Communication and Resource Allocation. Preprints 2023, 2023030254. https://doi.org/10.20944/preprints202303.0254.v1 Obinnaya Chikezie Victor, N. An Experimental Case Study on How AI May Improve Communication and Resource Allocation. Preprints 2023, 2023030254. https://doi.org/10.20944/preprints202303.0254.v1

Abstract

This paper explores how Artificial Intelligence (AI) can help reduce the communication gap and streamline the distribution of resources. It uses an exploratory case study to examine the current state of the communication gap and the potential opportunities AI can bring to close it. The paper will discuss the current state of the communication gap, the current methods of resource distribution, and the potential opportunities AI can bring to reduce the communication gap. It will also explore the potential implications of AI on resource distribution and the communication gap. The paper will review the existing literature on the communication gap, resource distribution, and AI. It will then focus on the opportunities AI can bring to the communication gap. It will analyze the use of machine learning, natural language processing, and other AI-based technologies to reduce the communication gap. It will also examine the potential implications of AI on resource distribution, such as developing more efficient distribution channels, increasing transparency, and reducing costs. Finally, the paper will analyze the impact of AI on the communication gap and resource distribution. It will discuss the potential challenges and benefits of using AI, such as the need for data security, the potential for bias, and the limitations of AI technology. The paper will also explore the potential for AI to improve the distribution of resources and reduce the communication gap. Overall, this paper provides an exploratory case study on the opportunities of how AI can contribute to reducing the communication gap and streamlining the distribution of resources. It discusses the potential implications of AI on the communication gap and resource distribution, and it reviews the potential challenges and benefits of using AI. The paper provides an in-depth analysis of the potential opportunities of using AI to reduce the communication gap and streamline the distribution of resources.

Keywords

Artificial Intelligence; Machine Learning; Natural Language Processing

Subject

Computer Science and Mathematics, Artificial Intelligence and Machine Learning

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