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Yes. Artificial superintelligence (ASI) might never be achieved: AI progress could stall, plateau below it, or develop along a path that does not produce a society-transforming superintelligence. There is no reliable consensus probability or timeline for ASI. Recent advances make major change plausible, but they do not show that ASI is inevitable.
What would count as ASI—and what would count as radically changing society?
ASI is not a standardized, measurable milestone. Google DeepMind’s 2026 report describes it intuitively as a system more intelligent and cognitively capable than large organizations of humans. The report focuses on possible transitions from artificial general intelligence (AGI) to ASI; it does not identify a particular system or date as the threshold.
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The social-change part of the question is also open to interpretation. It could mean one abrupt transformation, or a sequence of substantial changes as AI enables advances in science and technology. Those are different outcomes, and neither follows automatically from a capability label.
That ambiguity matters when weighing claims about whether ASI is likely. A forecast about machines performing many tasks, a prediction about AGI, and a claim that society will be radically transformed do not measure the same thing.
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How might AI reach ASI—and where could progress run into friction?
Google DeepMind’s 2026 report discusses four possible routes from AGI to ASI. They are proposed pathways, not predictions or guarantees.
- Scaling AGI: Extending the capabilities of AGI systems through greater scale.
- Shifts in AI paradigms: Moving to different approaches or methods that could enable further capability gains.
- Recursive improvement: AI systems contributing to the development of more capable AI systems.
- Large-scale multi-agent collectives: Coordinating many AI agents so their combined work produces capabilities beyond those of individual systems.
Each route could encounter bottlenecks or other frictions. The report says it remains an open research question whether their effects would be negligible or substantial. Until those questions are resolved, neither a smooth climb to ASI nor a firm ceiling below it is established.
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Why recent progress does not settle the question
The International AI Safety Report 2026 describes rapid progress in some evaluated capabilities, while cautioning that benchmark performance is not a direct forecast of general real-world competence. Success tends to fall as tasks get longer, and benchmark exercises can leave out complications such as resource limits and incomplete information.
The UK AI Security Institute reports that a model completed some expert-level cyber tasks in 2025 and that performance improved in its autonomy evaluations. It also reports that, within the cyber tasks it assessed, the duration of tasks models could complete with a 50% chance roughly doubled every eight months during the period evaluated. That is a trend in a particular evaluation suite—not a universal law of AI progress or proof that ASI will follow.
These results are relevant signs of capability change, but they answer bounded questions about evaluated tasks. They do not establish that ASI has been achieved, set a date for it, or show that development must continue at the same pace.
What expert forecasts can—and cannot—tell you
Surveys provide context, but their results depend on what respondents were asked, who answered, and what assumptions they made. For example, AI Impacts lists 2,778 respondents for its 2023 Expert Survey on Progress in AI. The figure describes the survey’s respondent count; it is not an ASI probability.
An earlier survey of attendees at three AI conferences, published in 2019 as Forecasting Transformative AI: An Expert Survey, reported median forecasts that AI could automate 90% of current human tasks with 50% probability within 25 years and 99% within 50 years. Those numbers concern task automation, not the chance of achieving ASI. The survey also found that conference attendance significantly affected respondents’ forecasts.
These estimates should not be combined into a single answer to “How likely is superintelligence?” They refer to different outcomes, samples, and time horizons. A useful forecast should make clear whether it concerns task automation, AGI, ASI, technical capability, deployment, or societal impact.
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What determines whether AI progress continues?
Technical developments are only part of the picture. The international interim safety report records expert disagreement about the pace of general-purpose AI progress, along with limits in technical evaluation and risk reduction. It also says future outcomes depend in part on choices made by societies and governments. As the report puts it, “nothing about the future of AI (artificial intelligence) is inevitable.”
That does not mean policymakers can guarantee a particular outcome, or that social choices alone determine technical progress. It means the path from current systems to any future capability—and how widely that capability is built and used—is shaped by human decisions as well as unresolved technical questions.
How to judge a claim that ASI is likely or inevitable
Before accepting a headline or forecast, check what it actually predicts:
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- Time horizon: Is the forecast about the next few years, a generation, or an unspecified future?
- Evidence and sample: Does it come from benchmark results, a bounded task evaluation, or a survey? If a survey, who responded and how was it conducted?
- Assumptions: Does it assume continued scaling, new AI paradigms, recursive improvement, or effective coordination among agents? Does it address bottlenecks?
- Outcome: Does the claim concern technical capability, real-world deployment, or the scale and speed of societal change?
A claim that skips these distinctions may sound more certain than its evidence supports. In particular, an estimate about automating a large share of tasks cannot be treated as an estimate of the probability of ASI.
So, could AI progress stop short?
Yes. ASI is a possible future endpoint, not an established certainty. Current capability gains support the view that major AI-driven changes are plausible, but they do not determine whether progress will reach ASI, how long it might take, or whether any transition would be abrupt. The sources cited here do not establish a reliable probability or timeline under a consistent definition of ASI.
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