Abstract: AI is the most talked about technology across the globe currently. Almost everybody is trying to find some way to claim that their products/services are powered by some AI magic. Undisputedly AI has done extremely well in the applications that are repetitive, having well-defined functionalities and plenty of data available for training purpose. But VLSI EDA tools are highly specialized and sophisticated software that rely on deep physics or complex optimizations or real-time empirical data collected from the Foundries. Moreover, nowadays majority of the SOC design companies use same/similar set of EDA tools and fabrication technologies, hence it has become difficult to differentiate the products based on the factors relying only on EDA tools and fabrication technologies. Many companies are resorting to some inhouse automation based on the past learnings or inhouse production data to gain the performance or cost advantage over the competition. All these secret recipes and data are company confidential items and never shared with anybody outside the organization. The lack of data and genuine feedback from users have become a bottleneck for EDA companies in adopting AI faster and stay upto date with actual problems seen in the field.