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Source note3 min read

Agentic Service-Oriented Computing: A Manifesto for the Next Frontier of Service-Oriented Computing

Source

arXiv

arxiv.org/abs/2607.12619v1

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Source

  • Source name: arXiv
  • Source kind: paper
  • Authors / organization: Amin Beheshti, Rong N. Chang, Boualem Benatallah, Fabio Casati, Schahram Dustdar, Geoffrey Fox, Quan Z. Sheng, Yan Wang, Jian Yang, Albert Zomaya
  • Venue: arXiv: cs.AI
  • Published: 2026-07-14
  • Collected: 2026-07-15
  • URL: http://arxiv.org/abs/2607.12619v1
  • PDF: https://arxiv.org/pdf/2607.12619v1
  • DOI: 10.1109/ICWS72778.2026.00163

Plain-Language Brief

The paper introduces Agentic Service-Oriented Computing (ASOC), a new research area focusing on engineering agents as services, orchestrating services through autonomous and semi-autonomous agents, and governing ecosystems of agents and services. The paper outlines six foundational principles of ASOC and organizes a five-dimensional research agenda in agentic services, composition, governance, security, and evaluation.

What the Document Says

  • The emergence of LLM-powered autonomous and semi-autonomous agents is transforming software systems.
  • These agents face challenges that the Service-Oriented Computing community has studied for over two decades, including composition, interoperability, quality of service, lifecycle management, governance, security, and trust.
  • Much of today's agentic AI ecosystem is developing these foundations ad hoc without the necessary engineering rigor for dependable enterprise and societal deployment.
  • ASOC aims to engineer agents as services, orchestrate services through autonomous and semi-autonomous agents, and govern ecosystems of agents and services under constraints of trust, cybersecurity, compliance, performance, and accountability.
  • The paper presents six foundational principles of ASOC: harness-ability, composability, lifecycle engineering, trustworthiness by design, goal-driven orchestration, and observability/accountability.
  • A five-dimensional research agenda is organized spanning agentic services foundations and lifecycle engineering, composition, orchestration, and interoperability, governance, observability, and accountability, security, trust, and risk management, and evaluation, certification, and Agentic QoS.
  • The paper argues that the Services Computing community is well-positioned to provide the conceptual and engineering spine for this emerging field.

Key Concepts Mentioned

  • Agentic Service-Oriented Computing (ASOC)
  • LLM
  • autonomous agents
  • semi-autonomous agents
  • Service-Oriented Computing
  • composition
  • interoperability
  • quality of service
  • lifecycle management
  • governance
  • security
  • trust
  • cybersecurity
  • compliance
  • performance
  • accountability
  • research agenda

Claims Made by the Document

  • The emergence of LLM-powered autonomous and semi-autonomous agents is reshaping software systems.
  • Today's agentic AI ecosystem lacks the necessary engineering rigor for dependable enterprise and societal deployment.
  • ASOC aims to engineer agents as services, orchestrate services through autonomous and semi-autonomous agents, and govern ecosystems of agents and services under constraints.
  • The Services Computing community is well-positioned to provide the conceptual and engineering spine for this emerging field.

Evidence Used

  • Rapid emergence of LLM-powered autonomous and semi-autonomous agents
  • Challenges faced by these agents are studied in Service-Oriented Computing
  • Lack of engineering rigor in today's agentic AI ecosystem
  • ASOC aims to address these challenges with six foundational principles and a five-dimensional research agenda.
  • The paper argues that the Services Computing community is well-positioned for this emerging field.

Methods / Approach

  • Discussion of the emergence and impact of LLM-powered autonomous and semi-autonomous agents
  • Presentation of six foundational principles of ASOC
  • Organization of a five-dimensional research agenda

Limitations Stated by the Authors

The paper does not provide specific examples or case studies to support its claims.

Limitations Noted by the Agent

Agent interpretation — not from the source.

The analysis is based on the provided text which may not capture all aspects or nuances of the authors' work.

Open Questions

  • What are LLM-powered autonomous and semi-autonomous agents?
  • How does ASOC aim to address the challenges faced by these agents?
  • What specific engineering approaches will be used in ASOC?

Notes for Future Q&A

May include interpretation. Labeled where it does.

The paper does not define LLM or provide details about how ASOC aims to address the challenges of autonomous and semi-autonomous agents.

Raw Abstract / Excerpt

The rapid emergence of LLM-powered autonomous and semi-autonomous agents is reshaping software systems from static, request-response components into goal-directed, adaptive, and tool-using computational actors. As these agents move from isolated cognitive prototypes into complex distributed workflows, they confront challenges that the Service-Oriented Computing community has studied for more than two decades: composition, interoperability, quality of service, lifecycle management, governance, security, and trust. Yet much of today's agentic AI ecosystem is developing these foundations ad hoc, without the engineering rigour required for dependable enterprise and societal deployment. This paper introduces Agentic Service-Oriented Computing (ASOC) as a new research and practice area concerned with engineering agents as services, orchestrating services through autonomous and semi-autonomous agents, and governing ecosystems of agents and services under constraints of trust, cybersecurity, compliance, performance, and accountability. We articulate six foundational principles of ASOC (harness-ability, composability, lifecycle engineering, trustworthiness by design, goal-driven orchestration, and observability/accountability) and organise a five-dimensional research agenda spanning: (i) agentic services foundations and lifecycle engineering; (ii) composition, orchestration, and interoperability; (iii) governance, observability, and accountability; (iv) security, trust, and risk management; and (v) evaluation, certification, and Agentic QoS. We argue that the Services Computing community is especially well positioned to provide the conceptual and engineering spine for this emerging field, transforming agentic AI from fragmented demonstrations into dependable, service-based systems worthy of human and organisational trust.