Enzymes are fundamental protein catalysts essential to life processes and widely applied in industrial and healthcare sectors. However, the broader application of natural enzymes is constrained by their inherent catalytic limitations, and traditional discovery methods such as microbial enrichment are often slow and low-throughput. Driven by advances in multi-omics and artificial intelligence, a range of novel screening strategies has been developed, enabling significant enhancements in both catalytic efficiency and stability of enzymes. This chapter assesses high-throughput approaches, such as metagenomics, metaproteomics, machine learning, and de novo design, comparing their respective advantages and limitations for enzyme discovery. Furthermore, we discuss the application potential of lignocellulose-degrading and plastic-degrading enzymes in biomass conversion and plastic waste recycling.