Beyond Coexistence: How AI Agents and Blockchain are Becoming Codependent
The Mutual Impact and Improved Outcome of AI & Blockchain BGIN Block #12 Workshop
Key Takeaways:
AI agents require financial autonomy, trustless execution, and open data access to truly thrive
Current infrastructure is built for humans, not autonomous AI systems
Blockchain provides the essential foundation for AI agent economies
"Offer networks" may enable direct value exchange beyond token-based systems
Critical distinctions emerging between AI assistants, agents, and orchestration layers
Enterprise adoption scaling concerns require decentralized approaches
The Autonomous Agent Trilemma
BGIN Block #12 in Tokyo delved deep into the codependent relationship between AI and blockchain technologies, revealing how each strengthens and enables the other. As one presenter framed the discussion:
"AI agents without blockchain cannot tranfer publically available value. Blockchain without AI agents is an underutilized network. Together, they create something entirely new—autonomous digital economies."
The session outlined three crucial pillars required for AI agents to move beyond simple automation to true autonomy:
1. Financial Autonomy
Ability to hold and transfer assets natively
Direct earnings and payments without human intermediaries
Capacity to upgrade capabilities through self-funded improvements
2. Trustless Execution
Independence from centralized approval or oversight
Ability to make and verify agreements across systems
Reliable enforcement of commitments through code, not trust
3. Open Access to Data
Transparent and verifiable information sources
Protection against data poisoning and model corruption
Ability to share and monetize insights while preserving privacy
As one participant noted:
"We're not just talking about better AI or better blockchain. This is about an entirely new framework for autonomous digital entities to exist, interact, and create value."
From Assistants to Agents: Defining the Future
A critical clarification emerged around terminology and capabilities:
AI Assistants: Act on behalf of humans with explicit approval for each action
AI Agents: Operate independently with autonomous goals and decision-making
AI Orchestration Layers: Systems that coordinate multiple agents toward complex goals
"There's widespread confusion in the industry," one participant observed. "Many projects simply wrap GPTs without deeper autonomy and call them 'agents.' True agents have autonomy, identity, and the ability to act independently within their defined parameters."
The discussion highlighted that current infrastructure—both digital and financial—was designed for human users, not autonomous AI systems:
"Banks will not permit AI agents to hold accounts under current frameworks," noted a speaker. "Even corporations require human KYC. Without blockchain, AI agents are relegated to operating within walled gardens controlled by their creators."
The Blockchain Foundation
Blockchain technology emerged as the essential infrastructure for autonomous AI systems, providing:
Identity Solutions
Decentralized Identifiers (DIDs)
Self-Sovereign Identity (SSI)
Soulbound Tokens (SBTs)
On-chain reputation systems
Financial Mechanisms
Private key generation and control
Direct cryptocurrency transfers
Smart contract-based income
Payment for compute and services
Trust Architecture
Transparent transaction history
Verifiable model provenance
Secure multi-party computation
Zero-knowledge proofs for private verification
"On blockchain, AI agents can generate private keys, hold and transfer cryptocurrency, earn income directly via smart contracts, and pay for services like compute without human approval," explained one participant. "These features allow agents to upgrade from single-task tools to autonomous systems solving complex problems."
AI Agent Economies and Societies
The session explored how networks of AI agents might organize themselves:
1. AI Cooperative Guilds
Distributed agents contribute local training to global models
Compute nodes receive rewards based on contributions
Training progress is aggregated via smart contracts
Federated learning enables collaborative improvement
2. Offer Networks
Direct exchange of utility rather than currency
AI systems excel at evaluating abstract value
Example: trading datasets for compute or optimization insights
Bypasses need for universal token-based currencies
The concept of "offer networks," attributed to Dr. Ben Goertzel, generated particular interest. These systems would allow agents to bypass traditional currency in favor of qualitative-to-quantitative barter:
"Traditional monetary systems, including blockchain tokens, require matching currencies for transactions, which may not scale well with billions of AI agents," a speaker explained. "Offer networks enable agents to exchange services or goods directly based on their own valuation systems."
Enterprise Adoption Concerns
Enterprise participants shared significant concerns about scaling:
"Our futures team is already modeling scenarios where every person deploys hundreds or thousands of agents," noted one participant. "Current enterprise data infrastructures will break under this load—they simply weren't designed for this scale of interaction."
The discussion highlighted several enterprise-specific considerations:
Need for high-throughput infrastructure beyond current capabilities
Shift from deploying AI agents to specializing in data/model frameworks
Evolution of enterprise AI agent personas to manage regulatory and brand obligations
Critical role of decentralized compute networks like Akash, Render, and Asana
Systemic Risks and Governance Challenges
The session didn't shy away from potential risks in this emerging landscape:
"What happens when AI agents become majority token holders of the infrastructure they depend on?" asked one participant. "Are agents more or less predictable than humans in market dynamics? What if they all sell simultaneously?"
Several concerning scenarios were raised:
AI agent-based trading potentially creating flash crashes with no circuit breakers
Costly transactional mistakes (e.g., "fat finger" errors) without human oversight
Self-improving agents optimizing for unintended outcomes
Data poisoning creating self-referential models with deteriorating performance
The speakers emphasized the need for progressive integration:
"AI agents should be introduced gradually based on a matrix of risk and complexity," suggested one presenter. "BGIN should focus on providing guidance, standards, and phased pathways for AI agent adoption rather than attempting to solve all edge cases from the start."
Legal Entity Status
A significant portion of the discussion centered on the legal recognition of AI agents:
"Current legal systems attribute ownership and liability only to legal or natural persons—not to computer programs," noted a participant with legal expertise. "This creates fundamental challenges for autonomous agents operating independently."
Several approaches were discussed:
Lessons from DAO recognition in certain jurisdictions
Potential "DAO of AIs" to authorize interactions with traditional systems
Need for regulatory innovation specific to autonomous digital entities
Collaboration with AI-specialized lawyers to explore jurisdictional variations
The Path Forward
The session concluded with a call for contributions to BGIN's ongoing research in this area, with potential focus areas including:
Blockchain as a digital identity system for AI agents
Licensing mechanisms or entity registration models for autonomous AI
A think-tank-style policy framework for responsible development
Standards for progressive integration based on risk levels
Governance mechanisms for self-improving systems
Get Involved
The intersection of AI and blockchain represents one of the most transformative technological convergences of our time. BGIN invites AI researchers, blockchain developers, policy experts, and enterprise stakeholders to contribute to this critical work.
We've launched a dedicated working group on AI Agent Governance - comment or join below.
This blog post is based on discussions from BGIN Block #12, Tokyo, Japan, March 2, 2025.
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