Artificial intelligence makes it possible to constantly monitor the project in order to monitor all changes that may occur at any time. Artificial intelligence provides suggestions to optimize project duration and costs and therefore improve its performance. Our goal is to help startups, businesses of all sizes, incubators to make the right choice, to make the right investment decision, to reduce the failure rate and to achieve financial performance, to through the design of a generic financial feasibility study model based on recommendation systems. Our model is applicable to all types of projects regardless of size, sector of activity, duration. In this work, we were interested in recommendation systems based on content-based filtering in the field of finance. This content is represented by the parameters of the financial feasibility study which will allow us through this system to see if the project is profitable, how to make it advantageous and more profitable, if it is not by using the different possible iterations/scenarios with a hierarchy from smallest gain to largest while exposing the parameters to be adjusted. Our model allows the decision-maker to have a clearer vision of the project and the stages of its implementation, which facilitates the decision-making process by presenting solutions allowing the user to define an optimization strategy in based on the recommendations and through which he will know how to manage his funds and resources in the most optimal way. Thus, this article is generally composed of three parts, first of a literature review through which we were able to identify all the concepts appropriate to our subject, second of an exploratory study which allowed us to discover through two analyses, a qualitative and a quantitative the perception of investors on the adoption of artificial intelligence in management sciences, and thirdly the application of our model on our case study.