AI AGENT INFRASTRUCTURE ANALYSIS
Infrastructure for AI Agents
AI agents plan and execute interactions in open-ended environments. For example, OpenAI's Operator can use a web browser to do product comparisons and buy online goods. Much research on making agents useful and safe focuses on directly modifying their behaviour, such as by training them to follow user instructions. Direct behavioural modifications are useful, but do not fully address how heterogeneous agents will interact with each other and other actors. Rather, we will need external protocols and systems to shape such interactions. For instance, agents will need more efficient protocols to communicate with each other and form agreements. Attributing an agent's actions to a particular human or other legal entity can help to establish trust, and also disincentivize misuse. Given this motivation, we propose the concept of agent infrastructure: technical systems and shared protocols external to agents that are designed to mediate and influence their interactions with and impacts on their environments. Just as the Internet relies on protocols like HTTPS, our work argues that agent infrastructure will be similarly indispensable to ecosystems of agents. We identify three functions for agent infrastructure: 1) attributing actions, properties, and other information to specific agents, their users, or other actors; 2) shaping agents' interactions; and 3) detecting and remedying harmful actions from agents. We provide an incomplete catalog of research directions for such functions. For each direction, we include analysis of use cases, infrastructure adoption, relationships to existing (internet) infrastructure, limitations, and open questions. Making progress on agent infrastructure can prepare society for the adoption of more advanced agents.
Executive Impact & Key Metrics
AI agents are poised to transform enterprise operations, from automating complex tasks to facilitating inter-company coordination. However, unlocking their full potential requires robust external infrastructure to ensure accountability, security, and seamless interaction. Our analysis highlights critical areas where foundational systems are needed to manage risks and amplify benefits, similar to how internet protocols underpin digital commerce.
3
Core Functions of Infrastructure
20+
Research Directions Explored
$900M+
Potential Economic Impact (Est.)
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Attribution: Ensuring Accountability & Trust
Attribution infrastructure is crucial for linking agent actions, properties, and other information to specific agents, their users, or other actors. This is fundamental for establishing trust and accountability in an agent-driven ecosystem, enabling legal recourse and deterring misuse.
Attribution Process Flow
User Authentication
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Agent Instance Binding
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Action Execution
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Counterparty Interaction
Accountability
Enhanced via Identity Binding for Agents
Identity Binding associates an agent's actions with a legal entity (human or corporation), vital for legal frameworks and trust. Certification provides verifiable claims about an agent's operation, behavior, and properties (e.g., data handling, autonomy level), analogous to SSL certificates for websites. Agent IDs serve as unique identifiers, linking to certifications and supporting incident response across sub-agents or platforms.
Widespread adoption of attribution infrastructure will likely be driven by digital platforms requiring it for accountability and to prevent Sybil attacks. However, privacy concerns and the risk of identity compromise necessitate careful design and robust security measures.
Interaction: Shaping Agent Behavior & Collaboration
Interaction infrastructure defines the protocols and affordances that shape how agents interact with their environments and with each other. This includes isolating agent traffic, enabling human intervention, facilitating agent-to-agent communication, and enforcing commitments.
Agent Interaction Framework
Agent Channels
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Oversight Layers
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Inter-agent Communication
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Commitment Devices
Agent Channels separate agent traffic from other digital traffic, reducing attack surfaces and enforcing agent-specific rules. Oversight Layers provide monitoring and intervention interfaces for humans or automated systems, ensuring agents adhere to intended behavior and enabling graceful recovery from malfunctions.
| Feature | Agent Channels | Existing Digital Interfaces |
|---|---|---|
| Traffic Isolation | Dedicated pathways for AI traffic, enabling targeted monitoring and control. | Mixed traffic, harder to isolate AI activity. |
| Security/Attack Surface | Reduced surface via optimized APIs, fewer prompt injections. | Vulnerable to human-interface exploits (e.g., website changes). |
| Rule Enforcement | Easier to enforce agent-specific rules (e.g., rollbacks, data handling). | General rules, less granular control for AI specific issues. |
Inter-agent Communication protocols facilitate joint activities and negotiations between agents, essential for complex collaborations. Commitment Devices enforce agreements between agents, from funding projects to upholding safety guardrails, leveraging mechanisms like smart contracts to ensure reliable cooperation.
Response: Detecting & Remedying Harmful Actions
Response infrastructure equips society with tools to detect and remediate harmful actions from agents. This includes robust incident reporting systems and mechanisms to void or undo agent actions, mitigating risks and building resilience.
Agent Action Response Flow
Agent Action
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Incident Detected
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Report & Investigate
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Rollback or Remedy
Incident Reporting for Proactive Safety
Just as aviation uses confidential reporting to improve safety, AI incident reporting can surface novel harms and impacts from agents. This allows developers and regulators to incorporate insights, enhance monitoring, and refine safeguards, moving from reactive fixes to proactive prevention. This fosters a safer, more robust AI ecosystem.
Incident Reporting Systems collect information about events that could result in harm, enabling organizations to learn from incidents, improve safety practices, and monitor locally run agents. They will require careful design to prevent spurious reports and ensure scalability.
Rollbacks provide mechanisms to void or undo an agent's actions, such as incorrect financial transactions or the spread of malicious content. This protects users from unintended actions and minimizes contagion. While powerful, rollbacks face challenges related to practical undoing of certain actions and potential moral hazard, suggesting the need for integration with insurance models.
Projected ROI Calculator
Estimate the potential savings and efficiency gains your enterprise could achieve by implementing robust AI agent infrastructure.
Annual Cost Savings
$0
Hours Reclaimed Annually
0
Your AI Agent Infrastructure Roadmap
A phased approach to integrate and leverage AI agent infrastructure within your enterprise for maximum benefit and minimal disruption.
Phase 1: Foundation & Identity
Establish core attribution systems including identity binding for agents, unique Agent IDs, and initial certification frameworks. This phase focuses on building the verifiable trust layer necessary for agent interactions.
Phase 2: Interaction Protocols
Develop and implement specialized agent channels for digital services and initial inter-agent communication protocols. This ensures controlled, efficient, and secure interactions between agents and with existing systems.
Phase 3: Oversight & Response
Deploy oversight layers to monitor agent behavior and enable human intervention. Integrate incident reporting systems for detecting harmful actions and build foundational rollback mechanisms for key operations.
Phase 4: Advanced Commitments & Certification
Introduce sophisticated commitment devices for multi-agent coordination and expand agent certification to cover complex properties. This phase focuses on enabling robust cooperation and high-assurance operations.
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