Leveraging IoT and Artificial Intelligence to Enhance Financial Forecasting and Customer Insights in Modern Marketing Systems

Abstract

This study examines how the Internet of Things (IoT) and Artificial Intelligence (AI) synergistically combine to transform financial prediction and understanding of customers with modern marketing environments. As companies shift their focus on shifting their reactive company to proactive company, the real-time data collected via IoT devices i.e. wearables and smart retail sensors, helps in giving fine details of consumer metrics. Coupled with AI-driven analytics, encompassing things such as predictive modeling, machine learning, and sentiment analysis, organizations can attain new heights in terms of personalization, operational efficiency, and strategic visioning as never before. The paper will suggest a well-structured framework that will involve data capture, combination, model-based analysis, decision support and feedback levels to make marketing operations and financial forecasting more efficient. Empirical claims reveal better forecasting accuracy (up to 30 percent), a better customer segmentation, and responsiveness in the campaign optimization. With the possibilities of transformation, there are still impediments in terms of data privacy, ethical issues, infrastructural restriction, and interpretability of the models. Via case studies and literature review, the paper demonstrates how it has been applied in real life across industry, outlining both advantages and hindrances. It ends on the note of endorsing a balanced action that enshrines the adoption of ethical AI practices, quality data governance, and organizational preparedness to make full use of the potentialities of AI IoT convergence under dynamic market conditions. Finally, the study offers a whole new picture of the idea on how the intelligent technologies can unlock the data-driven marketing transformation and long-term business growth.