XRP Ledger targets quantum risk and AI payments by 2029

Early action against quantum risk

The possibility that quantum computers might someday threaten the security of major cryptocurrency networks, including Bitcoin, has been debated for years. Akinyele now asserts that this is a practical concern rather than just theoretical. Citing a recent study from Google’s AI team, he said new algorithms could breach traditional digital signatures in as little as nine minutes—potentially as early as 2029.

The luxury of being unprepared is not an option. That’s why the RippleX team began collaborating early in 2024 and 2025 with cryptographers Dennis Ongu and Arthav Ali.

Within this scope, developers are integrating hybrid signature schemes into XRPL. As outlined in the plan, the blockchain will continue normal operations, but if a quantum attack is detected, the network can instantly shift to a more robust cryptography structure.

Mini glossary: A hybrid signature scheme combines today’s standard digital signature methods with new cryptographic tools designed for the post-quantum era. The goal is to maintain current compatibility while adding extra protection against future quantum threats.

Ripple is also collaborating with Project 11, a team examining vulnerabilities within the XRPL ledger, asset custody systems, and stablecoin issuance infrastructure. Akinyele further pointed out that attackers may already be capturing encrypted files to decrypt years down the line, emphasizing the need to establish safeguards now.

New use cases for the AI economy

Artificial intelligence integration emerges as the second major development area for XRPL. As part of this strategy, Ripple joined Mastercard’s Agent Pay for Machines initiative. Simultaneously, the RippleX team enhanced support for autonomous AI payments through its XRPL AI Starter Kit.

Akinyele envisions that in the near future, AI agents will become direct participants in financial markets. These autonomous agents will possess their own wallets, executing payments for activities such as server rentals, API access, or data transfers—without human involvement.

Nanopayments and the KYA model

Within this context, conventional transfers might be replaced by real-time, automated nanopayments of minute value. The report notes XRPL could become the prime venue for such payments, with payments between machines potentially surpassing those between humans over time.

To counter the risk of malicious individuals creating vast numbers of rogue AI agents, Akinyele explained the Know Your Agent (KYA) approach. Drawing on work from the T54 project, this model embeds an extra digital layer into XRPL, issuing unique “passports” to each agent to enable reputation tracking.

According to the information provided, this setup would enable regulators and participants in the market to swiftly identify the owner behind any AI agent, without noticeably slowing the pace of micropayments.