arXiv:2606.13405v1 Announce Type: new Abstract: LLM-based agents are entering regulated industries where they automate judgment intensive quality management processes. We argue that symbolic structures already embedded in these domains, including regulations, typed process models, and compliance constraints, should be treated not merely as external monitoring mechanisms but as core architectural components that shape the agent's decision-making and behavior. We propose compliance-by-construction as a complementary paradigm to guardrail-based monitoring: a structural foundation that prevents co
The rapid deployment of LLM-based agents into critical, regulated industries necessitates new architectural approaches to ensure compliance and prevent failures.
This research addresses a fundamental challenge for the widespread adoption of AI agents in high-stakes environments, potentially unlocking significant automation in regulated sectors.
The proposed 'compliance-by-construction' paradigm shifts from reactive monitoring to proactive integration of regulations into agent design, fundamentally altering how AI agents are built and deployed in regulated spaces.
- · AI software developers
- · Regulated industries
- · Compliance technology providers
- · Companies relying on guardrail-only AI compliance
- · Inefficient manual process industries
Increased trust and accelerated adoption of AI agents in financial services, healthcare, and legal sectors.
New standards and certifications for 'compliance-by-construction' AI agent architectures will emerge.
The definition of legal and ethical accountability for AI systems will evolve, embedding regulatory frameworks deeply into their core design and operation.
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Read at arXiv cs.AI