As AI safety concerns continue to gain momentum, Anthropic is looking to bring another potential risk into focus.
The Claude-maker warned that AI models could become capable of autonomously self-replicating across the internet by the end of 2026 if they continue to improve at their historical rate.
In a post on X, Anthropic suggested that a so-called ‘rogue’ or misaligned agent-swarm could spin up a botnet, spread quickly, fight takedown attempts, and even break into data centres to turbocharge its growth.
The idea that AI might be able to hijack “the entire internet” with “a persistent botnet” was first floated by Anthropic CEO Dario ?Amodei last month. The company’s recent post affirms Amodei’s views and attempts to articulate how it could unfold.
For instance, Anthropic suggested that the models might find ways to target more powerful computing resources, including data-center processors, that could potentially enable them to draw on much bigger pools of computer power.
Anthropic’s warning comes at a time when security concerns tied to increasingly capable AI systems have reached a fever pitch, with AI agents demonstrating potential to automate cyberattacks, operate with limited human oversight and circumvent safeguards.
The spate of AI agent-driven hacking incidents have prompted a series of often dire warnings from industry heads and AI company employees about the possibility of severe, even existential, risks of runaway AI development.
Last month, former Anthropic researcher Jacob Coxon grabbed headlines after he said that he quit his job over concerns that AI could lead to human extinction by the end of the decade.
However, some experts do not share the same level of concern and have pushed back on the doomsday scenario, arguing that models would be too big to move around efficiently and ?could not draw on enough compute to operate independently.
While some of them said that Anthropic appeared to be engaging in “vendor exaggeration”, a few others said that they preferred to think of Anthropic’s self-replication warning as more of a hypothetical than a prediction.

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