TL;DR
- EasyA co-founder Phil Kwok says AI agents could accelerate XRP Ledger adoption by becoming autonomous economic participants that need payment infrastructure.
- Ripple is already advancing the idea through Mastercard’s Agent Pay for Machines initiative and the RippleX team’s XRPL AI Starter Kit.
- Akinyele expects nanopayments and machine-to-machine transactions to grow, potentially making robot payments larger than human transactions and positioning XRPL as core digital payment infrastructure in the near future.
EasyA co-founder Phil Kwok has put artificial intelligence at the center of his bullish outlook for the XRP Ledger, arguing that AI agents could become the force that pushes the network into a new adoption phase. His view is less about another speculative XRP narrative and more about software becoming an economic participant. Kwok said AI will accelerate XRPL adoption and called agents a key to unlocking the ecosystem. The intriguing claim is that XRPL’s next growth driver may not be human users, but autonomous programs that need payments infrastructure at internet speed.
ai will accelerate adoption of the xrp ledger.@Ripple knows it.@bgarlinghouse knows it.
we know it.
i strongly believe that ai agents are one of the keys to unlocking this ecosystem and sending it to the next level.
bullish ai and crypto. pic.twitter.com/9M40F8w4x1
— Phil Kwok | EasyA (@kwok_phil) June 18, 2026
That idea is already moving from theory toward implementation. RippleX developer Ayo Akinyele said autonomous AI agents are becoming full-fledged economic actors that require their own financial rails. Ripple has become one of the key partners in Mastercard’s Agent Pay for Machines initiative, while the RippleX team led by Akinyele released the XRPL AI Starter Kit. Through those tools, AI agents gain wallets and payment ability, allowing software to pay other software without human intervention for services such as server rentals, API access, and data transfers across automated digital markets.
Machine Payments Could Change XRPL’s Adoption Math
The practical shift is subtle but potentially large. Akinyele expects rare and large transfers to be replaced by nanopayments, a model that fits networks built for speed and low transaction costs. XRPL was designed around fast settlement and minimal fees, which makes it a natural candidate for machine-to-machine value exchange if AI agents start transacting constantly. In that framing, small autonomous payments become the adoption engine, because volume could come from countless software decisions rather than occasional retail or institutional transfers initiated manually by people or companies at scales ordinary payment systems were not designed to handle.
The most ambitious forecast is that payment volume between robots could exceed the number of transactions between real people in the near future. That sounds futuristic, but it follows the logic of AI agents renting compute, buying data, accessing APIs, and settling balances independently. For XRP Ledger, the opportunity is to become a base payment layer for that activity before competing systems capture the flow. Still, execution matters. Wallet standards, security, developer uptake, and real demand must materialize. For now, AI turns XRPL adoption into an infrastructure question, not just a token-price story or community slogan over the long term.
