Forecasting Research Institute × LEAP

Probability of AI's Impact by 2040

Probability of AI's Impact by 2040

Asked again in Wave 8, experts had grown more confident of Level 8 by 2040 — 35%, up from 31% in Wave 1.

Experts
Superforecasters
Public

Our Analysis

How do we interpret these results

Experts and superforecasters place most of their probability at AI achieving a Technological Richter Scale (TRS) Level 8 impact, or “Technology of the Century” (e.g., electricity), forecasting mean probabilities of 35% and 34% respectively. They also forecast substantial probability of AI achieving Level 9 impact (24% and 23% respectively), but relatively little to the lower levels 5 and 6 (roughly 10% combined for both groups). The public forecasts a meaningfully different distribution, placing more weight across lower impact levels: they forecast roughly 31% to Levels 5 and 6 combined and only 23% to Level 8.

We previously asked participants this question as part of the Wave 1: Headliners survey between Jun 26, 2025 and Aug 16, 2025. Among participants who completed both Wave 1 and Wave 8, all three groups shifted upward, with superforecasters showing the largest increase: means rose by +0.39 for superforecasters (from 7.50 to 7.89), +0.20 for experts (from 7.86 to 8.06), and just +0.07 for the public (from 7.18 to 7.25). Additionally, 74% of participants remained within ±1 point of their forecasted mean TRS level from Wave 1, while 15% increased by more than one point and 11% decreased. Among experts, 13% increased and 6% decreased by more than one point; among superforecasters, 11% increased and none decreased. When comparing mean TRS levels across participants, we find that Wave 1 and Wave 8 levels are strongly correlated for superforecasters (r = 0.78), moderately correlated for experts (r = 0.56), and weakly correlated for the public (r = 0.31). This suggests that superforecasters’ basic views about AI may be more consistent across waves than those of experts and the public, even as they updated their numeric forecasts somewhat more over time..

Forecasts by group

Median forecasts from each group

groupLevel 5Level 6Level 7Level 8Level 9Level 10
Experts
3.81%
5.69%
20.88%
35.05%
23.97%
10.6%
Superforecasters
3.7%
6.7%
24%
34.14%
23.34%
8.5%
Public
16.08%
15.47%
23.1%
23.46%
15.06%
6.83%

Click any cell to compare

Rationale analysis

The main lines of reasoning driving the spread in estimates

Direction of update from Wave 1

The majority of respondents who reference their LEAP Wave 1 forecasts on this question shift toward higher TRS outcomes, typically citing faster-than-expected AI capabilities progress: “Since Wave 1, I've updated upward. The evidence keeps coming in faster than the models predicted --> FrontierMath blew past expert forecasts, METR's task horizon is already at 90 minutes and climbing on a log curve that doesn't look like it's slowing down. That's why I've moved my modal from Level 7 to Level 9.”; “Given that my previous forecasts under-predicted the rate of progress on the questions that have resolved so far, moving some mass from my previous answer to this question onto level 10.”; “We're already at 7/8 and 2040 is a long time away.” A smaller group does not adjust their forecast relative to Wave 1, often emphasizing that that 2040 is likely too soon for the highest levels; a few even shift their probability mass downward: “My thinking [has] only changed marginally since August 2025 when I answered the same question. Once again, the key point is that not much in human societies changes fundamentally over ~15 years.”; “The 2040 horizon is a key constraint: even ASI arriving in the late 2030s leaves little runway for epoch-defining impact to materialize and be recognizable.”

Capabilities vs. diffusion

Relatedly, low-TRS respondents often distinguish between the pace of AI capabilities progress and AI diffusion: “People, institutions, cultures, simply don't change that quickly.” One writes, “Electricity took + 50 years from [the establishment of the first commercial power plant at] Pearl Street to full societal impact.” Another emphasizes that reaching higher levels requires the co-evolution of “societal readiness, human cognitive and cultural adaptation, regulatory and political alignment, and economic integration.” High-TRS respondents tend to argue that technical capabilities are scaling so rapidly that they will overcome these traditional roadblocks: “FrontierMath hit 50% by March 2026, HLE gained 30 points in a year, METR task horizons reached 1.5 hours…This warrants shifting 10pp from L8 into L9 (+7pp) and L10 (+3pp).”; “If the next 14 [years] see autonomous research agents, AI-accelerated scientific discovery, and widespread cognitive automation, ‘technology of the millennium’ isn’t too far of a stretch.”

Emergence of AGI/ASI

Several high-TRS respondents point to the arrival of AGI or ASI as a likely tipping point: “I have roughly 65% on ASI by 2040 [and] conditional on ASI, Level 10 seems quite likely.”; “I expect AGI by around 2030 and an intelligence explosion likely within around a year of that.” The ability, in an AGI scenario, for AI to automate its own research and development was also cited: “Recursive self-improvement has moved from theory to practice… If this holds, AI becomes an autonomous engine of scientific discovery by the early 2030s, restructuring how knowledge is produced.” Low-TRS respondents tend to express more uncertainty regarding AGI, with one writing that “while I don't think it is impossible before 2040, I think it is very unlikely.” Others emphasize the potential for an “AI winter in the next few years,” to result in a capabilities plateau or for AI investment to contract if “the AI boom is actually a bubble that pop[s] in the next few years.”

Competing technologies

High-TRS respondents typically view AI as a meta-technology whose impact will be partly measured by the degree to which it accelerates other technologies: “Given the general-purpose technology (GPT) characteristics of AI, it is most likely to be a ‘technology of the century,’ comparable to past disruptive technologies such as electricity and the automobile.” Low-TRS respondents, however, point to this same quality as having the potential to result in a lower TRS score: “Other technologies seem more likely to be ‘of the millennium,’ such as space travel, quantum, [and] nuclear energy advances.”

Existential and evolutionary scenarios

While less frequently the primary driver of the forecasts, some high-TRS respondents assign a non-trivial probability to an AI-driven extinction event or a global takeover by AI: “The conceptual arguments are pretty strong that AI will be Level 10, e.g., the AIs will get really smart, kill all humans, and do what they want with the reachable universe.” Low-TRS respondents generally dismiss these outcomes for the 2040 timeframe: “[Level 10] either assumes that a) ‘AGI’ will emerge as a new ‘species’ to take over the world (which is just fantasy), or b) that a massive degree of somewhat voluntary societal change will take place to accommodate whatever ‘AI’ is in 2040, which does not make sense sociologically...”

Rationale examples

High-quality rationales from forecasters across the range

High-TRS respondents

Amara's Law…states we tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run. I'm not going to generalize to “we” here, but I certainly underestimated AI's capabilities if not its effects in the short run. So maybe there's a personalized corollary here: "I tend to underestimate the effect of AI in the short run and the long run.

The progress that has occurred between Wave 1 and now has only served to reaffirm my confidence that machine intelligence will be the most disruptive technology ever invented.

Current trajectories in capability scaling, multimodal reasoning, agentic systems, scientific automation, and economic integration suggest AI is unlikely to remain merely a sector-specific technology. Even under relatively conservative assumptions, AI already appears positioned to reshape knowledge work, education, software, media production, scientific research, and organizational decision-making at global scale.

Over the next 14 years algorithms will continue to improve along with transistor density. Then there is the possibility of breakthroughs in quantum computing. But even without quantum computing, simply extrapolating the last 4 years' rate of progress translates to unbelievable advances by 2040. Advances in medicine, education, manufacturing and robotics, and of course warfare, will yield a world very different from today.

If AI reaches a point where it can improve its own code without us, it stops being a tool and starts being a new era for the planet. I put that at 20% because while it sounds like sci-fi, the current speed of progress makes it a real possibility.

Low-TRS respondents

The question presupposes that technology will be the main driver of social change. All of the technologies listed above (and some of them aren’t technologies) changed the world through human adoption, innovation, socio-economic adaption, regulation and all sorts of other human activities. In 2040 the biggest impact on AI will be how we’ve adapted to it, not the benchmark measure of an AI model or how fast a robot can run a 10k. The social and political changes that may be turbo charged by AI may have more of an impact than the technology itself. We're already seeing this, especially in the US where scepticism of AI and a push back against data centres is manifesting.

The determinant of the development across levels 6-9 won't so much be the advancement of the technology itself, but the speed and degree of change across institutions, workplaces, regulations and norms, expectations and habits that will allow AI to diffuse more widely, be adopted more generally, and trusted more broadly. Policymakers have a great deal of influence here in terms of building frameworks for safe innovation and experimentation, shaping education and training curricula, and much more.

Unlike electricity or the automobile, [AI] is not a horizontal technology that reaches all of humanity equally. Its transformative power is concentrated among those with education, connectivity, and the means to leverage it, which is why I weight it heavily at Level 7 but discount higher levels.