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NEAR Protocol Outlines AI Money Thesis and Sovereign Agent Infrastructure

Photorealistic figure of autonomous AI agents trading on a neon NEAR hub, illustrating AI money and sovereign infra.

NEAR Protocol has detailed a comprehensive framework for the role of digital assets in an economy dominated by autonomous agents, introducing what it describes as an “AI money” thesis. The protocol is positioning its native infrastructure as the coordination layer for “sovereign AI,” a stack designed to allow AI agents to operate with independent identity, private execution, and native settlement capabilities.

According to official communications from NEAR Protocol, the new economic model for AI agents shifts the function of money into four primary roles. It serves as a store of value to ensure network sustainability, a settlement asset for high-frequency micro-transactions between agents, a bonding standard for security, and a metering unit used to price inference and compute tasks.

Infrastructure for Autonomous Agents

The push toward sovereign AI infrastructure focuses on moving beyond open-source models to create a decentralized environment where agents can function without central intermediaries. NEAR has identified several “sovereign agent” requirements that it intends to support through its protocol, including:

  • Identity and Verifiability: Procedures to ensure agent authenticity and the ability to verify actions on-chain.
  • Private Inference and Confidential Execution: Technologies that allow AI models to process data without exposing sensitive information.
  • Open Settlement Rails: Financial infrastructure that allows agents to trade and move value autonomously.
  • Liquidity and Coordination: Mechanisms to facilitate interactions between millions of independent digital entities.

The protocol describes itself as a holistic stack that integrates the base blockchain layer with “Intents” and “NEAR AI” to act as a coordinator for this open AI ecosystem. This positioning is detailed in a Q2 2026 report, which frames NEAR’s evolution not as a pivot, but as a return to its founders’ original focus on distributed training and compute systems.

Economic Sustainability and Token Burn

A central component of this infrastructure is the “Intents” layer, which is already impacting the protocol’s tokenomics. Current estimates suggest that the burn mechanism associated with Intents volume is a primary driver of network sustainability. According to some projections, net buyback pressure could exceed total token issuance if daily volume on the Intents layer reaches approximately $175 million, a figure the team views as a milestone for the agent-to-agent economy.

Despite the growth in this sector, the protocol acknowledges significant competition. While NEAR is scaling its infrastructure through milestones such as Multi-Party Computation (MPC) node expansion, its agent framework faces competition from other industry standards. Practical adoption for enterprise AI remains in the proof-of-concept stage, with long-term validation depending on repeatable commercial contracts and the velocity of “post-human” or agent-driven transaction volume.

The success of the “AI money” thesis will likely depend on the protocol’s ability to differentiate its settlement integration as autonomous workloads increase.