Agentic Payments Need Trust: Turning AI Agents into Economic Actors on Walrus
The missing piece that transforms AI from helpful assistant to autonomous decision-maker.
The capabilities of AI agents are rapidly evolving, with every day bringing a new headline about what they can achieve. Instead of just answering simple questions or performing straightforward tasks, they’re beginning to take real-world actions on behalf of everyday people. But there’s one critical piece of the puzzle missing: agentic payments.
Imagine you asked an AI agent to book you a trip to Miami. You share the dates, the airport details, and your budget, and ask the agent to watch for prices to fall within your range. At 2AM one day, prices slip into the perfect range for your dream vacation. But without the ability to actually purchase that ticket, the agent is useless, and prices will likely increase by the time you’re awake to hit “buy.”
Verified agents making purchases on behalf of verified users is the next frontier for AI-powered automation.
Sam Blackshear, CTO and Co-Founder of Mysten Labs
Agentic payments solve this problem by enabling AI agents to execute financial transactions independently, transforming them from advisors into true economic actors. But giving agents control over money introduces a new challenge: how do we ensure their payment decisions are trustworthy, auditable, and based on verified information?
That's where decentralized infrastructure becomes essential.
The Trust Challenge: Why Centralized Systems Fall Short
When agentic payments work, humans can move from being the executor to simply overseeing their actions. You set goals and define constraints, but the agent handles the actual decision-making and transaction execution.
Trust is the fundamental challenge of agentic payments. When an agent makes decisions, you need certainty about three things:
- The data the agent accessed was authentic
- The rules it followed were correct
- The decision process is auditable
Traditional centralized logging mechanisms are vulnerable to tampering by external attackers or insider threats with elevated privileges, and centralized storage poses a single point of failure. When critical financial decisions are at stake, this vulnerability won’t work.
How Walrus Enables Agentic Payments
Walrus addresses these challenges with decentralized infrastructure designed with verifiability, traceability, and security in mind.
Cryptographically verifiable data
On Walrus, data is verifiable by default. Metadata and proof of availability are stored on Sui, allowing users to leverage the chain's composability, expressivity, and security. When an agent makes a purchase at 3AM, you can verify exactly what data informed that decision.
Complete auditability
When agents process payments, execute trades, or verify identity, Walrus ensures every action is traceable. Each piece of data an agent accesses—spending limits, merchant information, transaction history—is cryptographically timestamped, creating an audit trail of what informed each decision. Teams of agents can even share memory with proof of availability, making their collaboration auditable and trustworthy.
Privacy-preserving access control
Walrus blobs can be protected with cryptographic access control, with policies specified in Move smart contracts. Agents can access sensitive payment information without exposing it to every service they interact with, creating an additional layer of security.
Agentic Payments Built on Walrus
Agentic payment systems are already using Walrus as their memory layer. In 2024, Google and Mysten Labs collaborated on the Agentic Payments Standard (A2P). Their demo shows an AI agent making six different purchases from three separate online stores, all bundled into one transaction on Sui. This ensures everything succeeds together or nothing goes through, so you're never left with incomplete orders (like a trip where the flight was booked, but the hotel wasn’t!).
Walrus stores the information the agent needs to make smart booking decisions: your budget limits, preferred airlines, hotel requirements, and past travel patterns. This combination of Walrus for trustworthy data and Sui for fast transactions enables agents to make autonomous financial decisions safely.
Conclusion
AI agents become more powerful when they handle payments autonomously. But this power hinges on trust: users need confidence that their agents are making good financial decisions based on verified information, not hallucinations or compromised data.
This is why Walrus is essential. By providing a decentralized data layer with cryptographic proof of availability, Walrus creates the foundation of trust that agentic payments require. When your AI agent books that 2AM flight or processes an invoice while you sleep, you can verify exactly what data informed that decision and trust that the information was authentic and tamper-proof.
The future of AI isn't just agents that can think and reason—it's agents that can act as true economic participants on your behalf. That future is already here.
