Google aims for post-quantum security by 2029, and 'Q-Day' could arrive sooner than expected.
The announcement was made in a Google technical blog post, in which the company for the first time clearly outlined its roadmap for transitioning to cryptographic algorithms capable of withstanding quantum attacks.
Google has just announced an ambitious roadmap to protect its entire infrastructure from the threat of quantum computing, aiming to complete the transition to post-quantum cryptography (PQC) by 2029. This timeline is significantly earlier than the plans of many governments and tech companies, suggesting the company is preparing for a 'Q-Day' scenario – the point at which quantum computers could break current encryption standards – that may arrive sooner than expected.
The announcement was made in a Google technical blog post, in which the company for the first time clearly outlined its roadmap for transitioning to cryptographic algorithms capable of withstanding quantum attacks. According to a representative from Google's security team, the announcement of this plan is not only for internal use but also a way to accelerate the entire technology industry's preparation for the post-quantum era.
For many years, most technology organizations and government agencies, particularly in the US, have aimed to complete the PQC transition by 2030–2033. Therefore, Google's 2029 target is considered quite bold. Some cryptography experts believe this represents a significant acceleration, even faster than the official requirements from the US government, and question whether Google is seeing clearer signs of the rapid development of quantum computing.
Although Google didn't elaborate on the reason for shortening the deadline, recent research has shown that the ability to break traditional encryption may come faster than scientists previously predicted. A study published in 2024 showed that a 2048-bit RSA key – a common standard in internet security – could be broken in less than a week using a quantum computer with about one million noisy qubits. This is significantly lower than previous estimates, when researchers believed tens of millions of qubits would be needed.
Along with the overall roadmap, Google also announced specific plans to integrate PQC into the Android ecosystem. Starting with Android 17, the operating system will support the ML-DSA (Post-Quantum Digital Signature) algorithm, which is standardized by the National Institute of Standards and Technology (NIST). This algorithm will be integrated into the hardware security system, allowing developers to sign and verify applications using post-quantum keys.
ML-DSA will also be integrated into Android Verified Boot to ensure the operating system boot process is not tampered with. Simultaneously, Android's remote authentication mechanism – used to prove device integrity to servers or cloud services – will be migrated to PQC. In subsequent phases, Google plans to expand support to the Android Keystore, Play Store, and the entire app signing process, forcing developers to update their security systems.
From a broader perspective, Google's move shows the race to prepare for the post-quantum era is heating up rapidly. Since the Shor algorithm was announced in the 1990s, cryptographers have known that quantum computers could break current encryption systems, but the specific timeline has always been unknown. Now, many large organizations and technology companies have begun integrating PQC algorithms into their products, albeit on a limited scale.
Google's 2029 timeframe is seen as a strong signal to the entire industry: quantum computing is no longer a distant dream. When one of the world's largest tech companies publicly announces its transition plans ahead of schedule, the pressure to accelerate will spread to other businesses and organizations. With data becoming an increasingly crucial asset, the post-quantum security race could become one of the biggest technological competitions of the next decade.
Update 28 March 2026
Kareem Winters
Kareem Winters is an AI integration expert, a strategic process of embedding artificial intelligence technologies—such as machine learning (ML), natural language processing (NLP), and computer vision—directly into an organization's existing systems, applications, and workflows.