The convergence of AI-driven engineering biology and emerging technologies advancing globally networked autonomous biofoundries

Since the emergence of synthetic biology, biofoundries have developed as enabling infrastructures that scale engineering biology globally. Landmark initiatives, such as Genome Project-Write, JCVI-syn3.0, Sc2.0, SynMoss and the Synthetic Human Genome Project, have significantly advanced the feasibility of constructing chromosome-sized DNA and revealed key principles of genome function and design. Nevertheless, the intrinsic complexity of cellular systems and the resource-intensive nature of experimental design-build-test-learn cycles continue to constrain innovation. Recent advances in artificial intelligence (AI), whole-cell modelling and digital twinning are now creating opportunities for self-improving, AI-driven biofoundries that seamlessly integrate in silico design and validation with miniaturised and automated in vitro testing. This review surveys the technologies shaping AI-driven synthetic biology, highlighting their convergence with automation, digitisation and miniaturisation to enable fully autonomous biofoundries that unify computational design, automated fabrication and data-driven learning within a single adaptive framework.