AI 2040: Plan A

AI companies are racing to build AIs that are smarter than humans in every way. In AI 2027, we predicted that this would result in either extinction or irreversible concentration of power. Plan A is our positive vision for what should happen instead. https://ai-2040.com/

In this scenario, humanity delays the development of superintelligence until 2040, makes all AI research public, allows dozens of companies globally to catch up to the frontier, and intentionally enters a regime of mutually assured compute destruction.

Plan A is our positive vision for how humanity can avoid AI-driven existential catastrophe and reach a flourishing future

Plan A is primarily a recommendation, not a prediction

While the implementation of Plan A is a recommendation and not what we actually expect to happen, the subsequent effects depicted are predictions.2

See summary (2026-07-11) ZviM Introduction For, And Reactions To, Plan A.

AI companies will probably succeed at their stated goal of building smarter-than-human (ASI) AI systems within the next 1 to 10 years.

The industry has convinced itself that controlling superintelligent AI can be figured out on the fly, and thus has no remotely adequate plan. We think this situation is terrible and could easily get us all killed.

Moreover, even if the AI companies somehow align their AIs, the result will be an unprecedented concentration of power—that is, the result will be a situation where a tiny group of people, or possibly just a single individual, is effectively in control of the world’s only army of superintelligences

As best as we can guess, the CEOs of OpenAI, Anthropic, xAI, and Google DeepMind understand this and are proceeding anyway, perhaps because they think they are the lesser evil and will use their immense power responsibly

We think most AI policy proposals fall apart under scenario scrutiny—that is, if you try to write down a detailed and plausible scenario in which that proposal succeeds, you will find it difficult to do so, and you will realize the plan is less likely to work than it seemed, or has more unpleasant side-effects than its proponents acknowledged.

Perhaps that’s why scenario scrutiny is so rare in AI policy.

We think the discourse would be improved if more AI policy proposals were subjected to scenario scrutiny. So we’re starting with our own, even though this opens us up to criticism.

we’d like to see something like it implemented soon because we are uncertain about how much time remains.11 But for purposes of writing a concrete scenario, we need a concrete timeline.

The timeline of this scenario is:

• In 2029, the US and China agree to avoid a reckless race to superintelligence.
• In 2030, we would have fully automated AI R&D, leading to superintelligence by the end of the year. Thanks to the deal, we avoid this.
• Between 2030 and 2035, we scale within the human range,*
• In 2040, we unpause and scale to superintelligence.12 (Hence the title: AI 2040)

In our previous scenario, AI 2027, AI fully automated the process of building smarter AIs in 2027, leading to an intelligence explosion and superintelligence within the year. The two differences in this scenario are (1) the default timeline is now 2030, and (2) thanks to governance actions, generally-superhuman AIs first appear in 2040.

2027: The Writing on the Wall

America has two workforces now. The first is people, 165 million of them. The second is AI agents

Congress is starting to pay more attention.

Now they step back and ask: Where are we going with this? What does the world look like five, ten, or fifteen years from now? Will there still be jobs? What if there aren’t?

One question weighs especially heavily on their minds: Who will control all these AIs?
Congress settles on an important part of the answer: Probably not us.

AI Transparency Act of 2027, an omnibus bill that does many things, some good and some bad, but doesn’t fundamentally change the situation

Incremental AI Policy Wishlist

Our main recommendation is to begin negotiating something like Plan A as soon as possible. But in this scenario, we depict Plan A happening imperfectly and only in the nick of time. So here is a list of less ambitious ideas that still help.

limiting the gap between internal and external deployment. The internally deployed AIs are where most of the AI takeover risk comes from because those are AIs involved in recursive self-improvement. The externally deployed AIs allow the broader public to interact with and understand AI capabilities, which is vastly more informative than any abstract report or evaluation.

Existing US export controls are poorly enforced. Epoch estimates that roughly a third of Chinese total compute is acquired via smuggling.

We have major reservations about introducing new export controls because they exacerbate the US/China race, but given the existence of export controls, we should obviously enforce them. If we don’t enforce them, then we should consider repealing them.

In 2026, big AI companies spend roughly half their compute budget on AI R&D

We could limit the fraction of compute spent on AI R&D. This would slow capabilities progress, giving the world a bit more time to react and prepare for each new wave of AI capabilities

2028: AI on the Ballot

The 2028 election cycle is heated, as usual. AI is the biggest topic.

Most white-collar professions are seeing disruption like software engineering saw in 2026; such jobs now heavily involve managing AI agents

On the default path, the next presidential term will see AIs that are far beyond human level, created entirely by AIs, themselves created entirely by other AIs, without any human in the loop since several generations back

Eventually the President and his protégé converge on one plan; the opposition candidate converges on another. Then it’s Election Day.

2029: Choose a Path

Plan A

*The President announces that the US will pursue international cooperation to avoid an imminent intelligence explosion.

“This mad race toward superintelligence must end. For too long, we have been pursuing lesser-evils and least-bad solutions. We need a Plan A. We can still proceed with AI development, but we must do it more cautiously, more transparently, and involving many more countries and companies.”*

*The US and China don’t trust each other. Fortunately, they don’t have to: Plan A includes provisions for verifying compliance. But setting it up will take time.

So for now, they start with something crude. For the rest of 2029, they put a temporary halt to AI training, because that's relatively easy to verify. In 2030, they’ll have the infrastructure in place to proceed with Plan A.*

2029: Hurried Negotiation

• Compute Declaration
• Training Pause
• Get Worldwide Buy-in

2030: Plan A is Established

• Buy Time
• Total Research Transparency
• Diffuse AI Broadly
• Reversibility

2031: Safety Cases

Although it’s supposed to be a slowdown, it doesn’t feel like one. In fact, if you were to rank every period of human history by how much it felt like a slowdown, this one would be dead last. A few AI researchers appreciate that progress is “slow” relative to the counterfactual with no deal and an uncontrolled intelligence explosion. Everyone else is too whiplashed to care.

2032: Controlled Explosive Growth

Across a variety of companies, there are now 60 million AI agents running continuously at 20x human speed. In the US, they are doing more cognitive labor than all humans combined—collectively matching a workforce equivalent to around 3 billion humans. White-collar professions have been transformed; many people have lost their jobs, but mostly have been able to get new jobs doing things AIs still can’t do or aren’t trusted to do.

Now that the United States is limited in the number of total robots it can build, it must choose how to allocate this capacity between companies. They decide to use the free market via a cap-and-trade system. Permits to build robots or compute are sold to the highest bidder and can be freely traded.

The permits also give the government much-needed revenue. In 2032, the US has a cap of 80M robots and 5 billion H100-equivalent GPUs. The market is so desperate for more robots and compute that permits become the expensive binding constraint, costing on the order of $200k per robot permit and $10k per chip permit, allowing the US government to collect roughly ten times the 2025 US federal revenue in permit fees (a total of $50T in FY2032).105 In 2034, when the AIs and robots will be even more capable and valuable, the permits generate $180T.

2033: The Citizen’s Dividend

Most of this newfound wealth is spent addressing soon-to-be-rising unemployment. The implementation takes different forms in different countries, but the eventual American version distributes the majority of compute and robot permit fees as a Citizen’s Dividend, distributed to all American adults.107 This starts at $45,000 per person (inflation-adjusted) in 2032 but climbs to ~$1M per person by 2035. It comes just in time: the share of labor done by AIs and robots (weighted by economic value) increases from ~20% in 2032 to ~85% in 2035. (UBI, The RICH Economy)

2034: Mutually Assured Compute Destruction

2035: Pause at Top Expert AI

2036: Life After Work

The economy has been rebuilt from the ground up. The fraction of tasks automated has gone from “a sizable chunk of cognitive labor and basically none of physical labor” in 2030, to now “pretty much everything.”

The world is basically being divided into three kinds of territory:

• Industrial Special Economic Zones: Picture a gigantic strip mine–an artificial Grand Canyon–next to a city-sized factory full of robots and empty of humans.
• Arcologies: Picture a tall skyscraper-mall complex surrounded by nature. Good weather, close to beaches and other cities, but not close enough to be blocked by zoning regulations.
• Historic & Nature Preserves: Everything else, i.e., 99% of the world. Yosemite, Paris, SF, New York—these places look basically the same as they did in 2025, or 1995 for that matter. A lot more tourists, though.

When the Citizen’s Dividend was first passed, people found it shameful to quit their job and live off government largesse. But the changing economic situation steamrolled over the stigma: By now, only 26% of Americans have jobs.

2037: The Apocalyptic Arrival of Truth on Earth

2038: AI Alignment Is Now a Science

2039: Beginning to Trust AIs

2040: Passing the Torch to AIs

Postscript

We think that following only incremental proposals will lead to a scenario like the race ending of AI 2027, in which misaligned AIs take over.179 If we get lucky and alignment is easier than expected, then they’ll lead to a scenario like the slowdown ending of AI 2027, in which a tiny group of individuals get to decide the shape of the future and could easily become permanent oligarchs if they so choose. Something more ambitious must be done. But what?