In order to improve the management mode of the human resources system and enhance the work efficiency of employees, this paper uses artificial intelligence (AI) technology to enhance the psychological empowerment of employees. It affects employees' work performance from a psychological perspective with the help of psychological empowerment. The questionnaire survey method collects data on the influencing factors of employees' psychological empowerment. The statistical data are analyzed by regression. Back propagation neural network (BPNN) algorithm based on deep learning is used to establish the work condition evaluation model. The job satisfaction, pressure, and performance of employees based on psychological empowerment are analyzed.

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With the development of the Internet and the continuous innovation of artificial intelligence, the study of financial data based on quantitative analysis methods of machine learning has also emerged. Quantitative analysis of financial data is a method of using computers to analyse financial data to predict the direction of stock market fluctuations in order to obtain excess returns. Machine learning has become an important tool in quantitative analysis methods, and has shown better performance than traditional quantitative analysis methods. Investing in financial data through quantitative analysis methods based on machine learning has advantages that traditional investment methods do not have, such as objectivity and accuracy, and is thus used by a wide range of investors and financial institutions. This paper firstly explains the feasibility of forecasting financial markets through the efficient market hypothesis, followed by the characteristics of quantitative analysis methods and the application of machine learning in quantitative analysis methods.