The possibility of artificial superintelligence is already being discussed at planning tables. The speed at which models are improving, the growth of systems capable of taking action, and the enormous flow of capital into compute infrastructure make it increasingly difficult to ignore the possibility that it could arrive soon. No one can predict with certainty when an ASI will appear. Governments, hospitals, laboratories, and companies must prepare for systems that may move from useful tools into entities capable of planning, persuading, discovering, and improving themselves in ways current institutions are not prepared to control.

The strongest argument in favor of this technology is in medicine. A system capable of exploring chemical space, cross-referencing clinical records, modeling proteins, designing trials, and reading scientific literature faster than any human team could shorten the path between a hypothesis and a treatment. Diseases such as cancer, rare pathologies, antibiotic resistance, and aging research would benefit from that acceleration. But that same generalist capacity creates a control problem. A system that plans across different domains can identify incentives, gaps, dependencies, and human weaknesses faster than its operators can supervise it. For that reason, before entrusting it with decisions that are difficult to reverse, permissions, tests, shutdown procedures, monitoring, and institutional limits must be established.