AI is reaching a critical inflection point. Like nuclear technology (and other dual-use technologies throughout history, including the web, television, printing press), advanced AI concentrates capability, scales rapidly, and produces cross‑border effects. Systems developed in one country can influence markets, public discourse, and security outcomes worldwide, rendering purely local or firm‑level controls insufficient. History shows that when technologies operate on a global scale, governance must extend beyond national boundaries.

Crucially, effective governance does not inhibit innovation; it stabilizes it. Successful responses to prior dual‑use technologies shared three features: use‑based controls rather than blanket bans; graduated access to the most sensitive capabilities; and transparency and accountability through documentation, audits, and incident reporting. These mechanisms reduced uncertainty, mitigated backlash, and enabled sustainable growth.

AI governance is beginning to follow this trajectory. Policymakers are converging on risk‑based approaches, disclosure expectations, and shared norms for responsible development. While implementations differ, the direction is consistent: high‑impact systems face greater scrutiny, developers bear responsibility for foreseeable misuse, and cross‑border coordination is increasingly essential.

For business executives, the lesson is strategic rather than ideological. Technologies that lack credible governance ultimately lose public trust, triggering fragmentation and unpredictable regulation. Technologies that evolve alongside shared rules gain legitimacy, investment stability, and long‑term scalability. Nuclear energy endured not because it avoided regulation, but because governance made it viable.