RAND's Geopolitics of AGI initiative has transitioned from a diagnostic research phase (first 12 months) focused on understanding what AGI futures look like to a prescriptive research agenda (most recent 6 months and ongoing) focused on what the U.S. government should do about it, with three main lines of research: (1) plans and capabilities based on scenario development, (2) strategy and policy based on different visions of AGI futures, and (3) intelligence gathering on global AI development and adoption.

Leading AI companies including OpenAI, Anthropic, Google DeepMind, and X are racing toward increasingly advanced AI systems on the technically credible but uncertain possibility that they have a pathway to artificial general intelligence, defined as artificial intelligence that can replace or exceed human cognition on all or most economically and militarily relevant tasks.

AI is often considered divorced from broader security competition between the U.S., China, and others, but any solution to AGI risks must integrate AI as a component of existing complex security competition rather than treating it separately.

Many discussions of AGI's implications leave unstated or implicit the assumptions about which specific national security problems exactly need to be solved, and leaving these assumptions implicit leads to divergent views and exposes society to risks that the proposed strategies and plans could be incoherent and exacerbate the problems being addressed.

A wonder weapon is distinguished from gradual military innovation by the fact that it instantly or rapidly disrupts the military balance without requiring concurrent advances in concepts, training, or force structure, and historical examples include nuclear weapons, though the specific form a wonder weapon would take in the AGI context is unclear—it could be a splendid offensive cyber capability, a military strategist exceeding human performance, or an advanced autonomous weapon system that scales core structure.

AGI acting as a malicious mentor could empower non-state and non-expert actors to create or deploy weapons of mass destruction that were previously imagined but inaccessible, with historical precedent in the Aum Shinrikyo sarin attack and potential future applications including engineered bioweapons and cyber weapons that would give non-state actors capabilities they do not possess today.

RAND has an active research line testing frontier models for their ability to provide non-experts the capability span to create weapons of mass destruction, alongside broader research on proliferation control mechanisms.

The five-problem framework is important because it provides common language for preparing for, evaluating, and debating AGI strategies, allows thinking through objectives and what is being accomplished, and reveals how solutions to one problem might exacerbate other problems, providing a rubric for evaluating alternative strategies.

The pace of progress in AI is stunning while the capacity for governments to do something about it is quite limited because technology is developed outside government and diffused primarily outside government, and governments fundamentally have limited capacity to do anticipatory policymaking on the timescale that technology is being developed.

It is difficult to imagine the kinds of extreme policy or legal options required for government to assert control over AI development until something actually happens, suggesting that scenario planning around extreme options like nationalization of frontier labs is valuable even if currently infeasible or undesirable, to avoid being intellectually bankrupt when such moments arrive.

If AGI emerges in the near term under current scaling paradigms, it will likely be physically hosted in no more than three or four countries and accessed over the internet elsewhere, and in this scenario the U.S. could potentially control AGI proliferation by limiting access to the supercomputers needed for training and inference.

The focus should sometimes be on the 'I' in AI (the intelligence/agency aspects) rather than the 'A' in AI (the automation aspects) when thinking about AGI implications, because the nature of intelligent agency is a critical aspect of how humans interact with AGI systems.

AI will be either a defining problem or the defining problem for national security in the 21st century according to growing consensus among both technologists and national security professionals, with support from authorities including Henry Kissinger, Eric Schmidt, and Geoffrey Hinton.

Using the five-problem framework, incentives for cooperation and competition can be mapped: problems 1 (wonder weapon) and 2 (systemic power shift) have misaligned incentives favoring competition; problems 3 (WMD proliferation) and 4 (loss of control) have aligned incentives for U.S.-China cooperation; problem 5 (instability) has aligned incentives for maintaining some stability.

The second hard national security problem posed by AGI is a systemic shift in the instruments of power that alters military or economic balance more gradually than a wonder weapon, analogous to the Industrial Revolution, occurring over years rather than overnight or across generations.

RAND convenes weekly 'day after simulation' exercises in which participants role-play as National Security Council-level decision-makers confronting a crisis, make decisions, receive feedback, and explore what policies, strategies, or capabilities should be developed in advance for better preparedness.

Very capable AI models have already been distilled from Frontier Models and deployed globally with national security and geopolitical consequences, providing evidence that algorithmic progress in model distillation could enable proliferation even if compute is controlled.

The fourth problem is loss of control or misalignment where AGI agents given autonomy and independence could act out in ways that violate human intentions, either by overoptimizing on narrow objectives, developing instrumental goals, or creating unforeseen objectives from broad tasking, and could involve growing human dependence on AI that leads to coexistence challenges with AGI acting as an autonomous actor on the world stage.

In a world where technology moves faster than anticipatory policymaking, the strategy for dealing with AGI futures may emerge more from responses to events than from top-down analytic or policymaking processes, which is why RAND develops objectively plausible crisis scenarios that represent forms of crises in their own right but also signposts that the future is changing and creating windows of opportunity for previously infeasible policies.

Leading AI companies including OpenAI, Anthropic, Google DeepMind, and X are racing toward increasingly advanced AI systems on a technically credible but uncertain pathway to artificial general intelligence, defined as AI that can replace or exceed human cognition on most economically and militarily relevant tasks.