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Cyber risk can hold flat for years, then jump sharply once attackers find a way to exploit a new technology, an artificial intelligence (AI) appears that is heading down a similar path, cyber insurance specialist Coalition believes.
The insurance industry collectively has close to a trillion dollars of cyber insurance limits outstanding. Underwriters face two possible threats from AI: a steady, grinding escalation in the frequency and severity of regular attacks, or a single event that hits many insureds at once.
Industry alarms peaked in September 2026 Anthropic CEO Dario Amodei warned that an AI swarm could take over “the entire internet” within a year.
The warning was promptly backed by AI executives Sam Altman and Elon Musk, who called for vendors to slow the pace of model development.
The cyber insurance industry has also heard warnings like this before. OpenAI delayed GPT-2’s release in 2019 over malicious-use risk, Turing and Nobel laureate Geoffrey Hinton resigned from Google in 2023 to warn against existential threats and later flagged sophisticated phishing schemes, and Anthropic withheld Mythos from public release in April 2026 due to concerns about its cyber attack capability.
All of these models were eventually released without destabilizing the cyber insurance market. It’s easy to read that track record as reassurance, but it doesn’t mean that AI will never impact cyber risk.
The cyber threat environment has historically demonstrated initial stability as threat actors test new technology.
A heightened level of risk usually manifests years later, following attackers finding an effective business model to leverage or exploit that innovation. Cybercriminals established the premier online marketplace for trading stolen credit card information in 2001.
Although adoption was initially gradual, this technical advancement ultimately structured an entire illegal ecosystem.
By 2009, law enforcement concluded these forums created a black market for stolen data by allowing “criminals to quickly sell the fruits of their ill-gotten gains to thousands of eager fraudsters.”
Criminals adopting a new technology made data breaches profitable. Businesses holding sensitive data experienced a dramatic increase in data breach risk, but only years after criminals started using online forums.
In the 2010s, ransomware actors began demanding cryptocurrency payments. Initially targeting individual machines for minor sums, they found little success because victims preferred replacing hardware over paying in unknown digital currencies.
The strategy became profitable only after attackers transitioned to compromising full networks.
Unable to bypass the threat, victims learned to pay in cryptocurrency, allowing attackers to collect million-dollar ransoms, untraceable by law enforcement Though this shifted the risk landscape slowly, by 2020, after the cryptocurrency-back ransom model gained traction, ransomware incidents surged over 1,000% from 2017’s claims, with a maximum losses soaring from $500,000 to $20 million.
By 2025, ransomware represented 75% of all claims paid by the cyber insurance industry.
Coalition sees the same pattern taking shape with AI today, moving fastest where the underlying attack was already easy to automate, and slower where more manual steps stand in the way.
While widespread disruption has not yet crippled balance sheets, the incubation phase is well underway, Coalition stated.
The post AI-driven incidents will escalate in frequency once attackers find the right business model: Coalition appeared first on ReinsuranceNe.ws.
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Cyber risk can hold flat…
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