AgentSLA : Towards a Service Level Agreement for AI Agents

2025-11-04

AI Summary

Current AI Agent-as-a-Service paradigms lack quantifiable, verifiable mechanisms for defining Quality of Service (QoS) and Service-Level Agreements (SLAs). To address this, we propose the first end-to-end SLA framework for the AI Agent lifecycle: (1) an extensible AI Agent quality model grounded in ISO/IEC 25010; (2) a domain-specific language (DSL) for formal, unambiguous SLA clause specification; and (3) a model-driven engineering approach enabling automated SLA modeling, consistency verification, and runtime compliance checking. Our framework systematically adapts established software quality standards to the AI Agent context—enabling structured QoS metric definition, machine-readable SLA representation, and automated conformance assessment. It bridges a critical gap between AI service delivery and rigorous, auditable quality assurance, thereby significantly enhancing trustworthiness and service reliability in intelligent systems. (149 words)

Technology Category

• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Multiagent Systems: Agent/AI Theories and Architectures

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Agentic search
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

AI components are increasingly becoming a key element of all types of software systems to enhance their functionality. These AI components are often implemented as AI Agents, offering more autonomy than a plain integration of Large Language Models (LLMs), moving from a Model-as-a-Service paradigm to an Agent-as-a-Service one, bringing new challenges to the development of smart software systems. Indeed, while support for the design, implementation, and deployment of those agents exist, the specification of Quality of Service (QoS) and definition of Service Level Agreements (SLAs) aspects for those agents, important to ensure the quality of the resulting systems, remains an open challenge. Part of this is due to the difficulty to clearly define quality in the context of AI components, resulting in a lack of consensus on how to best approach Quality Assurance (QA) for these types of systems. To address this challenge, this paper proposes both a quality model for AI agents based on the ISO/IEC 25010 standard, and a domain specific language to support the definition of SLAs for the services provided by these AI agents.

Problem

• Defining Service Level Agreements for autonomous AI agents
• Establishing quality models for AI components in software systems
• Creating domain-specific language for AI agent SLA specification

Innovation

• Defines quality model for AI agents
• Proposes domain-specific language for SLAs
• Adapts ISO/IEC standard for agent services