AI Agents Require Decentralized Network for Trust and Accountability

AI is becoming integral to trading, functioning as agents that negotiate and execute trades on decentralized platforms. This evolution offers institutional crypto desks faster transactions and innovative products.

However, discrepancies in recorded values between agents, such as one recording $100 million and another $120 million in a derivatives contract, raise accountability issues. Such gaps could lead to failures or investigations, highlighting the risks of unverified data.

The need for reliable systems is critical, as conflicting records can create systemic risks. In finance, even minor mismatches in large contracts traded globally can result in significant consequences.

To address these challenges, three foundational layers are necessary:

Decentralized infrastructure: Enhances resilience and sustainability by removing single points of control.
A trust layer: Ensures verifiability, identity, and consensus for secure transactions.
Verified AI agents: Guarantee accountability and auditability, allowing agents to operate effectively.

Agents must operate in environments with:

Consensus on events
Provenance identification
Auditability of actions

Enterprises should prioritize transparent, auditable systems supported by policymakers endorsing open-source networks. The future of AI in finance demands a focus on building trust from the outset.