The company is making its AI Control Roadmap public to help other frontier AI labs corral rogue AI agents before they become more capable and autonomous.

Google DeepMind published a new framework designed to help AI companies control and monitor their own increasingly capable AI agents, releasing what it calls an “AI Control Roadmap” as the industry races toward more autonomous systems.

The roadmap focuses on ensuring advanced AI agents continue to act as intended, even as they gain access to more tools, data and decision-making authority.

Rather than concentrating on external cyber threats, the framework examines how AI developers can prevent their own systems from behaving in unexpected or undesirable ways. Google DeepMind describes the effort as part of a broader field known as AI control, which seeks to develop safeguards capable of detecting, constraining and correcting problematic AI behavior.

The company argues that traditional oversight methods will become less effective as AI systems become more autonomous. Developers may need additional mechanisms to ensure agents remain aligned with their intended objectives.

The roadmap outlines several areas of research, including methods for monitoring AI behavior, identifying deceptive actions, limiting an agent’s ability to cause harm, and creating systems that can safely intervene when problems are detected. The company said these approaches could eventually provide a foundation for managing risks associated with highly capable AI agents.

Google is sharing its work publicly. The company said the roadmap is intended to help other frontier AI developers pursue similar safeguards and encourage greater collaboration across the industry.

Google DeepMind noted that significant research is still needed before effective AI control mechanisms can be deployed at scale. However, the company argues that work on those safeguards should begin well before the most capable AI agents become widely available.