Azure Communication Services for Email

R. Ranjan, R. Buyya, S. Nepal, D. Georgakopoulos

D. Pettinga, Azure Angelov, D. Bateman

Robert Kumar, Yanzhen Qu

The growing complexity and volume of communication in business environments significantly hinder timely decision-making processes. This paper addresses the problem of delays and inefficiencies in business decision-making by exploring how large language models (LLMs)-enabled agents to streamline communication and accelerate the business decision making process. Our project aims to develop and evaluate an LLM-enabled Agent as an innovative tool for semi-automating communication and decision making in business processes. The central research question asks how LLMs can be utilized to reduce communication complexities in business processes. Guided by a design science research framework, this project follows a structured artifact design, implementation, and evaluation process. The virtual environment simulates real-world conditions using synthesized business communication data like emails and meeting notes. The LLM-enabled Agent leverages Azure OpenAI services and integrates domain-specific customization to align the LLM’s outputs with business needs. Quantitative testing of the agent’s performance assesses its effectiveness in automating information gathering, document synthesis, and decision-making.

Shalini Sharma, Satyajit Padhy, Vikram Verma

C. Krintz