Gen-Optimizer: A Generative AI Framework for Strategic Business Cost Optimization

Strategic cost optimization is a critical challenge for businesses aiming to maintain competitiveness in dynamic markets. This paper introduces Gen-Optimizer, a Generative AI-based framework designed to analyze and optimize business costs through intelligent decision support. The framework employs a transformer-based model with over 140 million parameters, fine-tuned using a diverse dataset of cost-related business scenarios. By leveraging generative capabilities, Gen-Optimizer minimizes inefficiencies, automates cost analysis tasks, and provides actionable insights to decision-makers. The proposed framework achieves exceptional performance metrics, including a prediction accuracy of 93.2%, precision of 93.5%, recall of 93.1%, and an F1-score of 93.3%. The perplexity score of 20.17 demonstrates the model’s superior language understanding and generative abilities. Gen-Optimizer was tested in real-world scenarios, demonstrating its ability to reduce operational costs by 4.11% across key business functions. Furthermore, it aligns with sustainability objectives, promoting resource efficiency and reducing waste. This paper highlights the transformative potential of Generative AI in business cost management, paving the way for scalable, intelligent, and cost-effective solutions.