Generative AI for Strategic Plan Development
Jesse Ponnock

TL;DR
This paper explores the use of Generative AI, specifically BERTopic and NMF, to automate and improve the development of strategic plans for government organizations, demonstrating high accuracy in theme generation.
Contribution
It introduces a modular GAI model for strategic planning and evaluates the effectiveness of BERTopic and NMF in generating relevant themes from government reports.
Findings
BERTopic achieved over 50% strong or medium correlation with Vision Elements.
Both models could generate themes similar to 100% of the evaluated elements.
BERTopic outperformed NMF in this application.
Abstract
Given recent breakthroughs in Generative Artificial Intelligence (GAI) and Large Language Models (LLMs), more and more professional services are being augmented through Artificial Intelligence (AI), which once seemed impossible to automate. This paper presents a modular model for leveraging GAI in developing strategic plans for large scale government organizations and evaluates leading machine learning techniques in their application towards one of the identified modules. Specifically, the performance of BERTopic and Non-negative Matrix Factorization (NMF) are evaluated in their ability to use topic modeling to generate themes representative of Vision Elements within a strategic plan. To accomplish this, BERTopic and NMF models are trained using a large volume of reports from the Government Accountability Office (GAO). The generated topics from each model are then scored for similarity…
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Taxonomy
TopicsBig Data and Business Intelligence
