Transforming Strategy with AI-Augmented Personas for Sustainability, Data Management, Regulatory Frameworks, Healthcare and Compliance

A. Suboyin, D. Sreedeth, M. M. Rahman, S. Diaz, J. Kannan, H. S. Sreedeth, A. Rehman, M. Valiyapalathingal, Y. Noor, B. Somra

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

This paper aims to present the development and application of an artificial intelligence (AI) platform designed for creating tailored personas in sustainability, data management, scope 3 emissions management, ISO standards compliance and policy creation. The scope includes the utilization of advanced large language models and curated document sets to generate highly accurate and context-specific personas, ensuring IT infrastructure excellence and sustainability. The AI platform employs advanced large language models (LLMs) specifically fine-tuned on domain-specific corpora, including sustainability reports, policy documents, and industry standards. Curated document sets, including regulatory texts, industry and healthcare reports, and academic literature, are integrated into the training data to enhance contextual relevance along with providing an accuracy score for the responses. Additionally, robust data management protocols are implemented to ensure data integrity and accessibility. The curated document sets are indexed and annotated to facilitate precise information retrieval. The persona creation process involves natural language processing (NLP) algorithms to analyze and synthesize data, followed by iterative model refinement through supervised learning. The platform's architecture ensures adaptability and precision, incorporating feedback loops to continuously improve persona accuracy. The IT infrastructure supporting the platform is optimized for scalability and reliability, ensuring seamless integration and performance for cloud, hybrid or on-premises solutions. The platform's effectiveness was validated through multiple case studies. In a sustainability context, the generated personas improved strategic planning accuracy by 25% compared to traditional methods, based on stakeholder feedback. For scope 3 emissions management, personas provided insights that can lead to a 15% improvement in supply chain engagement effectiveness. In ISO standards compliance, personas can facilitate a 20% increase in the understanding of regulatory alignment. The platform demonstrated a 95% accuracy rate in generating context-specific personas, with user feedback indicating a 30% increase in decision-making efficiency compared to traditional solutions. Additionally, the integration of advanced data management practices ensured data reliability and accessibility, while the optimized IT infrastructure can contribute to a 40% increase in operational efficiency. These results highlight the platform's capability to enhance strategic planning, compliance, and data management across various domains. This paper presents a novel approach to strategic planning and compliance leveraging advanced AI and curated datasets to address specific needs in sustainability and policy domains. The integration of data management and IT infrastructure excellence ensures the platform's robustness and reliability. The highly accurate and context-specific personas represent a significant advancement, contributing to the existing body of knowledge and providing a valuable tool for enhancing decision-making processes in these critical areas.

Original languageBritish English
Title of host publicationSociety of Petroleum Engineers - ADIPEC 2024
ISBN (Electronic)9781959025498
DOIs
StatePublished - 2024
Event2024 Abu Dhabi International Petroleum Exhibition and Conference, ADIPEC 2024 - Abu Dhabi, United Arab Emirates
Duration: 4 Nov 20247 Nov 2024

Publication series

NameSociety of Petroleum Engineers - ADIPEC 2024

Conference

Conference2024 Abu Dhabi International Petroleum Exhibition and Conference, ADIPEC 2024
Country/TerritoryUnited Arab Emirates
CityAbu Dhabi
Period4/11/247/11/24

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