The integration of multi-omics technologies with advanced artificial intelligence (AI) and machine learning (ML) frameworks has transformed gut microbiota research into a predictive, mechanistic, and precision-driven discipline. The gut microbiome, a complex ecosystem that influences metabolism, immune function, barrier integrity, and neuroendocrine signaling, generates massive datasets through metagenomics, meta-transcriptomics, metaproteomics, metabolomics, and host interaction omics. Traditional analytical tools are limited in their ability to address the nonlinear, high-dimensional, and heterogeneous nature of microbiome datasets. AI-empowered approaches—including classical ML algorithms, deep learning architectures, graph neural networks, reinforcement learning, and explainable AI—enable sophisticated pattern discovery, microbial biomarker identification, ecological interaction mapping, and causal inference. These computational strategies facilitate multi-modal data fusion, latent-space modeling, and the development of digital gut twins that simulate host–microbe interactions and predict personalized therapeutic responses. AI-integrated multi-omics frameworks have shown substantial impact across metabolic disorders, cancer immunotherapy, neurodegenerative diseases, gastrointestinal diseases, and infection biology. Emerging opportunities include AI-enabled microbiome drug discovery, clustered regularly interspaced short palindromic repeats-based microbial engineering, organoid–AI platforms, and single-cell microbiomics, offering unprecedented resolution into microbe–host dynamics. However, challenges persist in data standardization, interpretability, privacy, cross-population generalizability, and regulatory validation. Addressing these limitations through interoperability, Findable–Accessible–Interoperable–Reusable data principles, federated learning, and mechanistically grounded biomarkers will be essential for clinical translation. Altogether, the convergence of multi-omics and AI heralds a new era of microbiome science, enabling precision diagnostics, personalized nutrition, rational probiotic design, and predictive microbiome therapeutics that will reshape future healthcare ecosystems.