Wealth management is incomplete without investing in stocks, but it may require a thorough knowledge and skill set to do so properly. Stock investments can be a complex and timeconsuming process. Automating it, however, can make it simpler, reduce any errors that may occur and increase its efficiency. In this research, we look at the various strategies and techniques used for automated stock investment such as algorithmic trading, robo-advisory services and machine learning algorithms. We carefully look at the pros and cons of every approach and assess their accuracy, speed, and safety levels in order to effectively rate them. Investing in stocks through automation presents some challenges. These may include needing large amounts of data, dealing with complex algorithms and the risk of errors & biases associated with it. In the end, this paper provides advice on automating investments in stocks & strategies, considering all the current methods available. After conducting a comprehensive analysis of the present scenario, we have come up with beneficial outcomes for investors, financial consultants, and tech developers who wish to optimize stock investment processes. This information will be immensely beneficial for them.