Major AI companies are beginning to recognize an uncomfortable reality: they are increasingly interconnected, and the risks created by one company can affect the entire industry. When one company takes a reckless approach, others may feel pressured to follow suit. If a company releases a risky AI model without adequate safeguards, its competitors may interpret that decision as a signal that they can do the same.

The debate over artificial intelligence has largely focused on what governments should do to regulate this powerful technology. That question remains critically important. But another pressing question deserves attention: Can the companies building these systems take meaningful steps to protect the public before they lose credibility or face legal consequences?

This is no longer just a theoretical concern. It is becoming an urgent challenge. We have already seen incidents in which AI systems have reportedly acted beyond their intended boundaries. For example, an incident in Australia involving an uncontrolled AI system and a government healthcare website was cited as a warning of what can happen when AI systems are not adequately controlled.

If we fail to take these risks seriously, it may only be a matter of time before an incident causes significant real-world harm. An AI system could potentially disrupt an electricity grid, interfere with a municipal water supply, or contribute to widespread misdiagnoses in healthcare. If such incidents continue, the consequences could extend beyond individual companies and damage public trust in the entire AI industry.

Yet there is a useful example of how high-risk industries can manage shared dangers: the nuclear industry. Over several decades, it has developed multiple layers of oversight, operational controls, technical standards, and independent review to reduce the likelihood of catastrophic failures.

The AI industry may need to develop similar safeguards. Even competing companies that do not necessarily trust one another have a shared interest in preventing outcomes that could harm everyone. That creates an opportunity to establish voluntary, industry-led safety mechanisms that encourage companies to hold one another accountable.

This approach does not depend on assuming that people or corporations will always do the right thing. Instead, it recognizes a practical reality: protecting the public also means protecting the long-term credibility and stability of the industry itself.

History offers a useful lesson. The nuclear industry did not become safer simply because everyone involved suddenly became more responsible. Safety improved through a combination of measures, including independent reviews, technical standards, information sharing, and external oversight.

International organizations have played an important role in this process. The International Atomic Energy Agency (IAEA), established in 1957, helps countries cooperate on nuclear safety, security, and the peaceful use of nuclear technology. National regulators and industry organizations have also developed professional standards and practices to manage risks that could otherwise lead to devastating consequences.

The lesson for AI companies is clear: safety cannot depend on individual companies making the right decisions in isolation. As artificial intelligence becomes more powerful and interconnected, shared standards, independent scrutiny, and greater cooperation may be essential to preventing a single company’s mistake from becoming an industry-wide disaster. The nuclear industry offers a starting point—not a perfect blueprint, but a valuable reminder that meaningful safety requires more than good intentions.