Vietnam should adopt a six-pronged policy framework to harness the productivity and innovation potential of autonomous AI agents while containing new privacy, security and displacement risks; the paper distils international practices into actionable regulatory and institutional steps for the Vietnamese context.

Main Finding

Vietnam should adopt a proactive, multi‑pronged regulatory framework to both capture the productivity and innovation gains of an emerging Agent Economy (AE) and to control its systemic, safety, privacy and labour risks. The paper synthesizes international practice and theory to propose a six‑group policy package (legal/regulatory; technical standards; trust/certification; market‑based incentives; sandboxes/experimental governance; human oversight & labour policies) tailored to Vietnam’s context.

Key Points

• Definition and significance

  • The Agent Economy (AE): an ecosystem in which autonomous, agentic AIs represent humans/organizations to transact, coordinate and make decisions across markets, potentially creating a “network of agents” that operates alongside the human economy.
  • Agentic AI key characteristics: autonomy, goal‑orientation, environmental interaction, learning, workflow optimization (language/reasoning/planning), and multi‑agent coordination.

• Economic effects

  • Benefits: lower transaction and information costs, reduced switching costs, personalized products, new business models (micro‑transactions, automated market search), productivity gains.
  • Risks: systemic contagion across agent networks; cyber/security misuse (fraud, misinformation, coordinated attacks); privacy and data‑sharing concerns; labour displacement for cognitive tasks; blurred legal responsibility and accountability.

• Regulatory design principles highlighted

  • Early, coordinated market architecture decisions will shape long‑term distribution of benefits (analogy to early Internet governance).
  • Mix of technical instruments (open standards, trust infrastructure, verifiable credentials) and policy instruments (laws, sanctions, economic incentives, human‑in‑the‑loop requirements).
  • Governance‑through‑economics: proposals such as collateral/deposits for agents performing high‑risk tasks to create economic incentives for safe behaviour.
  • Agent sandboxes: deliberate experimental environments (varying degrees of isolation/permeability) to observe agent behaviour before full integration into the economy.
  • Human oversight: clear boundaries for what must remain under human control, emergency stop mechanisms, lifecycle risk governance, transparency and labelling of AI interactions.

• International policy comparisons (selected)

  • United States: innovation‑first, light federal regulation; reliance on voluntary standards (NIST AI RMF), agencies using existing laws (FTC, EEOC); active state‑level patchwork; industry self‑regulation common.
  • European Union: risk‑based, prescriptive approach via the EU AI Act (risk tiers, registration, transparency, human oversight, emergency stop, lifecycle governance); emphasis on protecting rights and imposing obligations across the value chain.
  • China: tighter controls on generative AI services to protect national interests (paper discusses China as a restrictive model).
  • Singapore: pragmatic sandboxing and pilot mechanisms to encourage innovation while ensuring safety.

Data & Methods

• Method: document synthesis and comparative policy analysis.
• Sources: scientific literature (2020–2025) and updated international policy documents on agentic AI and the Agent Economy.
• Case selection: United States, European Union, China, Singapore — chosen to illustrate different regulatory approaches.
• Selection criteria: recency, reliability, direct relevance.
• Limitations noted: qualitative synthesis (no primary empirical data); early‑stage phenomenon with evolving technical and policy detail; recommendations intended as a conceptual policy framework requiring further empirical testing and contextual adaptation.

Implications for AI Economics

• Market structure and competition

  • Open standards and interoperability policies will influence whether the AE becomes decentralized or evolves into “walled gardens” dominated by incumbents; standards and certification reduce transaction costs and can enable entry by smaller firms.
  • Agent‑mediated interactions can lower consumer search costs and switching frictions, intensifying competition and enabling new pricing/delivery models (e.g., micro‑transactions, hyper‑personalized bundling).

• Risk externalities and systemic stability

  • Highly connected agent networks create potential for fast‑propagating externalities (e.g., automated sell‑offs, coordinated fraud); regulators must internalize these systemic risks via lifecycle governance, registration for high‑risk agents, and compulsory safety mechanisms.
  • Economic policy instruments (collateral, deposits, insurance markets for agent liability) can align private incentives with social stability and reduce moral hazard.

• Labour and distributional effects

  • Agentic AI will substitute for some cognitive tasks while complementing others; short‑run displacement risks require active upskilling, job transition policies, and possibly social safety nets.
  • The distribution of gains depends on early governance choices: strict entry barriers may slow diffusion and concentrate rents with incumbents; permissive regimes may accelerate adoption but raise social harms.

• Innovation policy trade‑offs

  • Regulatory stringency affects innovation location and timing: the U.S. model may accelerate deployment and investment, the EU model prioritizes trust and rights but may impose compliance costs that shape industry incentives; Vietnam’s policy choices will shape domestic capability building and foreign investment.
  • Sandboxes and phased regulation can balance experimentation and control, giving policymakers data to refine economic policy while limiting large negative externalities.

• Legal/institutional economics

  • Clarifying liability and accountability (who pays when agents cause harm) is crucial for functioning markets: predictable rules reduce litigation risk, lower insurance costs, and encourage responsible deployment.
  • Certification, reputation systems and verifiable credentials reduce information asymmetries and can create a market for trusted agents; enforcement powers (revocation, sanctions) are necessary to sustain credibility.

Policy takeaways for Vietnam (synthesized from the paper) - Adopt a hybrid, phased approach combining: 1) A risk‑aware legal framework aligned to AE characteristics (registration/oversight for high‑risk agents; lifecycle risk governance). 2) Investment in open technical standards and interoperability to avoid monopolistic lock‑in. 3) Trust infrastructure (agent identity, verifiable credentials, reputation systems) and enforcement capacity. 4) Market‑based incentive tools (collateral/deposit requirements, insurance/indemnity regimes). 5) Agent sandboxes (controlled, graded permeability) to observe agent behaviours and calibrate rules. 6) Human‑in‑the‑loop, liability clarifications, and workforce upskilling programs.

Overall, the paper argues that Vietnam can proactively embrace the Agent Economy by combining international lessons with domestic policy instruments to maximize economic benefits while managing systemic, social and distributive risks.