AI Speeds Quantum Threat to Bitcoin and Ethereum, Forcing Post-Quantum Shift
Updated
Updated · CoinDesk · May 24
AI Speeds Quantum Threat to Bitcoin and Ethereum, Forcing Post-Quantum Shift
6 articles · Updated · CoinDesk · May 24
Security researchers say AI is compressing the timeline for cryptographically relevant quantum computers, raising the risk that today’s encryption protecting blockchains and the wider internet could fail sooner than expected.
Machine learning is already helping optimize quantum error correction and broader scientific discovery, while also giving attackers better tools to find software flaws and potentially weaken cryptographic implementations.
The threat is no longer viewed as purely theoretical: experts warn governments and other sophisticated actors may already be stockpiling encrypted traffic for “harvest now, decrypt later” attacks once quantum systems mature.
Bitcoin, Ethereum and other networks are exposed because they rely on elliptic curve cryptography; ecosystems including Ethereum, Zcash, Solana, Ripple and NEAR are researching or rolling out post-quantum migration plans.
Post-quantum systems remain bigger and slower than current standards, reinforcing a broader shift toward security as a continuous upgrade cycle rather than infrastructure refreshed once every decade.
As the 2027 deadline looms, is AI speeding up the quantum threat faster than our defenses can adapt?
Could quantum computers retroactively forge digital signatures, effectively rewriting our documented history?
Quantum Threat Accelerates: AI Pushes Crypto-Breaking Timeline to 2029, Exposing 6.9 Million Bitcoin and Ethereum to Imminent Risk
Overview
Quantum computers are quickly becoming a real threat to current cryptographic standards, with Artificial Intelligence (AI) playing a major role in speeding up this timeline. Recent breakthroughs show that AI is making quantum systems more reliable and capable, pushing expert predictions for when these threats could appear much closer to today. A key example is Google's AlphaQubit, an AI designed to improve quantum error correction, which has shown strong performance even in scenarios far beyond its training data. These advances highlight the urgent need for new security solutions as the risk of quantum attacks grows rapidly.