mlsanityData to 7 Oct 2026

AgentSLA : Towards a Service Level Agreement for AI Agents

arXiv 2511.02885 ↗First posted 4 Nov 2025cs.SE cs.AIcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 14 of its 44 references that are in the map. First posted on arXiv 4 Nov 2025.

Builds on

14 of 44 references.

References · 14

  1. 2017A Unified Approach to Interpreting Model Predictionscited by 6,488
  2. 2016"Why Should I Trust You?": Explaining the Predictions of Any Classifiercited by 5,040
  3. 2018Model Cards for Model Reportingcited by 1,068
  4. 2016Measuring Neural Net Robustness with Constraintscited by 90
  5. 2024Croissant: A Metadata Format for ML-Ready Datasetscited by 79
  6. 2023A Systematic Review of Green AIcited by 77
  7. 2023Model-as-a-Service (MaaS): A Surveycited by 24
  8. 2021Quality Assurance for AI-based Systems: Overview and Challengescited by 19
  9. 2022A domain-specific language for describing machine learning datasetscited by 12
  10. 2025Measuring AI agent autonomy: Towards a scalable approach with code inspectioncited by 10
  11. 2019Adapting SQuaRE for Quality Assessment of Artificial Intelligence Systemscited by 7
  12. 2024Building BESSER: an open-source low-code platformcited by 7
2 more
  1. 2024Service Level Agreements and Security SLA: A Comprehensive Surveycited by 3
  2. 2025Towards Sustainability Model Cardscited by 1

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Citing papers per year: 2026: 1.

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  1. 2026A Large-Scale Empirical Study of Quality Assurance Practices and Gaps in AI Agents
  2. 2025Agentic Services Computing
  3. 2026From Obligation to Specification: A Survey on Validating EU AI Act Requirements in RE
  4. 2025AgentDNS: A Root Domain Naming System for LLM Agents
  5. 2026Agentic Service-Oriented Computing: A Manifesto for the Next Frontier of Service-Oriented Computing
  6. 2025Agent-as-a-Service based on Agent Network
  7. 2023Enhancing Trust in LLM-Based AI Automation Agents: New Considerations and Future Challenges
  8. 2024LLM-based agents for automating the enhancement of user story quality: An early report