Abstract: This research is aimed towards building an architecture for the web-based applications to be generated as per the Web 3.0 framework standards with the assistance of Artificial Intelligence. The web 2.0 framework is a user generated web framework and is heavily subjected to the content generated by the users. In keeping up with the Web 3.0 standards, the web content is generated with the assistance of Artificial Intelligence, which is highly personalized and consistent with the user preferences. The value of this research is to supply a coherent perspective on various technologies like Machine Learning, Semantic Web, Neural Network, Natural Language Processor and Recommendation System and the way it can be adopted to transform the web framework. The mix of these technologies together with an intelligent recommender algorithm can efficiently help in building AI - enabled web applications and conform to the standards set by Web 3.0 framework.This paper further talks about the comparison between Web 2.0 and Web 3.0 in conjunction with the semantic web and various data transfer protocols. The paper also provides an in-depth research of the different ways in which the personalized recommendation may be generated for the user to setup user preferences. The recommender engine is developed with the collaborative filtering, content-based filtering and hybrid filtering approach which provides knowledge-based data filtering method and aims to form user specific content. This paper also gives an understanding about how AI may be integrated with a recommender system and website template builder to develop a web application which fully conforms to the Web 3.0 standards and generates user specific website templates.Keywords: Artificial Intelligence, Web 3.0, Intelligent Web, Semantic Web, Web Development, Web Design, Recommender System, Collaborative Filtering, Content Based Filtering, Knowledge Based Filtering