Artificial intelligence has just compressed the timeline for quantum computers to threaten global internet security, potentially by years. Last week, Google and quantum startup Oratomic published research showing that AI-optimized algorithms could reduce the number of quantum bits, or qubits, required to build a dangerous quantum computer by roughly 100 times. The breakthrough has alarmed cybersecurity experts and prompted major tech companies to accelerate their defenses .

Why Does This Quantum Computing Breakthrough Matter Right Now?

Quantum computers represent an existential threat to modern encryption because they can theoretically solve mathematical problems that would take classical supercomputers longer than the age of the universe. A sufficiently powerful quantum computer could decrypt everything from WhatsApp messages to classified government documents in days. The U.S. National Institute for Standards and Technology (NIST) had set 2035 as the deadline to transition to quantum-resistant encryption, but the Oratomic and Google findings could "significantly" shorten that window .

The implications are immediate. Within days of the papers' publication, Cloudflare, which secures a significant fraction of the internet, announced it was "accelerating" its deadline to prepare for quantum computers to 2029, six years earlier than NIST's original timeline. Google itself announced a similar 2029 deadline for securing its own systems .

"The world is currently, in my view, not prepared," said Dolev Bluvstein, one of the paper's authors and co-founder of Oratomic.

Dolev Bluvstein, Co-founder, Oratomic

How Did AI Help Solve This Quantum Computing Problem?

The key innovation came from using AI to optimize quantum algorithms in ways human researchers hadn't considered. Robert Huang, one of the paper's authors, initially found that the team's algorithms performed about 1,000 times worse than needed. Rather than abandon the approach, he decided to use OpenEvolve, an open-source tool that harnesses large language models (LLMs) such as Google's Gemini and Anthropic's Claude, to optimize the algorithms through a process analogous to natural selection .

The results surprised everyone. The AI combined past scientific results in novel ways, demonstrating understanding of niche quantum computing sub-disciplines as it tested thousands of different ideas. Without the AI assistance, Huang explained, the team likely would have tried a few approaches, seen they didn't work, and concluded "the whole thing is not possible." Instead, the AI's proposals significantly improved the performance of some of the most critical algorithms in the paper .

Huang

"I didn't expect you would find anything useful," said Robert Huang, one of the paper's authors.

Robert Huang, Co-author, Oratomic

The breakthrough centers on atomic quantum computers, which use individual atoms as qubits. Traditionally, it takes 100 to 1,000 atoms to encode a single reliable qubit because quantum information is fragile and easily disrupted by environmental interference like cosmic rays. The Oratomic algorithm requires just three atoms to encode a qubit, reducing the total number of particles needed by roughly 100 times .

Steps to Understanding the Quantum-AI Connection and Its Implications

• The Qubit Problem: Quantum computers use qubits instead of classical bits, but qubits are extremely fragile and require redundancy to function reliably, meaning many physical atoms or particles are needed to create one logical qubit.
• The AI Solution: Machine learning models like Gemini and Claude can explore vast solution spaces far faster than human researchers, finding algorithm optimizations that reduce the physical resources required to build quantum computers.
• The Security Threat: As quantum computers become more efficient and require fewer qubits, the timeline for building encryption-breaking systems moves closer, making the transition to quantum-resistant encryption urgent.
• The Preparation Gap: Most organizations and governments have not yet implemented post-quantum encryption standards, leaving critical infrastructure vulnerable if quantum computers arrive sooner than expected.

What Do Quantum Computing Experts Say About the Timeline?

The research has generated significant concern within the cybersecurity and quantum computing communities. Bas Westerbaan, a cybersecurity researcher at Cloudflare, told TIME that the findings were "a real shock" and that the industry would "need to speed up our efforts considerably" .

"Almost every system in the world becomes vulnerable altogether to a quantum attacker," said Bas Westerbaan, cybersecurity researcher at Cloudflare.

Bas Westerbaan, Cybersecurity Researcher, Cloudflare

However, some experts urge caution. Jeff Thompson, an associate professor at Princeton and CEO of atomic quantum computing startup Logiqal, noted that the paper has not yet been peer-reviewed and that many of the authors' assumptions remain "untested." He pointed out that it's "very easy" to reduce the size of a quantum computer "if you just assume better qubits" .

John Preskill, a widely recognized pioneer of quantum computing and co-author on the paper, acknowledged the significance of the work while emphasizing that humans remained the primary drivers of the research. "Humans were still the primary drivers of the research, asking the right questions and then guiding the AI towards answers that are useful and informative," Preskill noted .

The Oratomic team spent months verifying the algorithms that AI had derived before publishing, and the authors emphasize that "many open challenges" remain before a dangerous quantum computer is built. Still, the implications are serious enough that the team briefed U.S. government officials prior to publication .

What Happens Next in the Quantum-AI Race?

The convergence of AI and quantum computing is accelerating industry investment. Google posted a job listing for a quantum researcher to develop AI-based "discovery pipelines" in early March, just weeks before announcing a new internal atomic quantum computing initiative on March 24. The timing suggests that major tech companies recognize AI as a critical tool for advancing quantum computing development .

The question of which quantum computing architecture will prove easiest to build remains the "million-dollar question," according to Umesh Varizani, a quantum computing researcher at UC Berkeley. The Oratomic breakthrough improves the efficiency of atomic quantum computers specifically, but does not affect the resources required for other approaches using superconducting circuits or photons .

What's clear is that AI has fundamentally changed the pace of quantum computing research. The technology that was supposed to accelerate scientific progress generally has now accelerated a development timeline that cybersecurity experts view with alarm. The world's race to implement quantum-resistant encryption has just become significantly more urgent.