The era of AI regulation is upon us. Executives often equate regulation with constraint, and for good reason. Noncompliance can result in significant consequences—see Meta’s $1.3 billion fine for violating EU–US data transfer rules. But the reality is much more nuanced. AI regulation is recognized as an increasingly urgent need not just among government officials but also among industry leaders and even some LLM developers—all of whom have expressed concern about the evolution of generative AI and the safety of future AI tools.

Regulators around the world are already hard at work. The EU AI Act is entering its final stage of negotiation; many believe this could become the global standard for AI regulation, much like GDPR has for data protection. In the US, the Federal Trade Commission has pledged to enforce the core principles of fairness, equality, and justice, and Chinese regulators have submitted a proposal to manage generative AI chatbots.

At this pivotal moment, companies pursuing AI transformation must have a deep understanding of current and emerging regulations, so they can ensure full compliance and engage productively with regulators through data-driven dialogue. Such collaboration is an opportunity to develop regulations that are mutually beneficial and technologically feasible—that provide effective safeguards while leaving room for companies to experiment and innovate.

Executives can start with four actions: creating a unified regulatory framework, managing contradictory regulations among countries, participating in sandboxes and incentive programs, and developing and sharing internal expertise with regulators.