Digital Transformation Chatbot (DTchatbot): Integrating Large Language Model-based Chatbot in Acquiring Digital Transformation Needs

TL;DR

This paper explores a Large Language Model-based chatbot designed to gather digital transformation needs from organizations, aiming to replace traditional expert interviews with an automated, workflow-driven virtual interview system.

Contribution

It introduces a novel LLM-powered chatbot that integrates workflow instructions for effective digital transformation needs assessment, demonstrating its potential as a virtual expert tool.

Findings

Chatbot effectively follows predefined workflows.

Supports user interactions with areas for improvement.

Performs as designed in preliminary evaluation.

Abstract

Many organisations pursue digital transformation to enhance operational efficiency, reduce manual efforts, and optimise processes by automation and digital tools. To achieve this, a comprehensive understanding of their unique needs is required. However, traditional methods, such as expert interviews, while effective, face several challenges, including scheduling conflicts, resource constraints, inconsistency, etc. To tackle these issues, we investigate the use of a Large Language Model (LLM)-powered chatbot to acquire organisations' digital transformation needs. Specifically, the chatbot integrates workflow-based instruction with LLM's planning and reasoning capabilities, enabling it to function as a virtual expert and conduct interviews. We detail the chatbot's features and its implementation. Our preliminary evaluation indicates that the chatbot performs as designed, effectively following predefined workflows and supporting user interactions with areas for improvement. We conclude by discussing the implications of employing chatbots to elicit user information, emphasizing their potential and limitations.