The Artificial Intelligence (AI) Model Canvas Framework and Use Cases

Abstract

Artificial Intelligence (AI) has grown increasingly in the past decade. The growth and development bring up several issues for a successful AI project. The AI project requires communication across different domains, like specialists, engineers, data scientists, stakeholders, and ecosystem partners (analytic, storage, labeling, and open-source platforms). It offers numerous vital qualities to give deeper insights into user behavior and give recommendations based on the data. The AI project is hard to define, it requires more than mastery of data, and every enterprise needs guidance and a simple plan on how to use AI. This research creates a wide-view approach of different types of AI Model Canvas for companies that do projects, produce, promote and provide AI technology to organizations. We selected three canvases that represented AI, Machine Learning (ML), and Deep Learning (DL) method. We illustrate and interpret those canvas along with some case studies. We conclude our research by writing the final case report for each use case from the AI model canvas. By filling the one-page Canvas, it will help us explain what AI will provide, how it will interact with humans judgment, and how it will be used to influence decisions, how you will measure success & outcome, and the type of data needed to train, operate, and improve AI. The AI Model Canvas purposed a clear description and differentiation of the roles of stakeholders, customers, and AI strategy. This canvas also can be used in analytical and assembly projects in making new product lines.