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AI Agent–Driven Autonomous Service Delivery in Saudi Arabia: A Framework for Intelligent Telecom and Enterprise Operations under Vision 2030
Subject area: Science,Engineering and Technology · Area of research: Artificial Intelligence
DOI: 10.64388/IREV10I4-1723620
Abstract
The telecommunications and enterprise sectors in Saudi Arabia are progressing from digitally based service operations towards more autonomous operating models in which artificial intelligence is able to understand objectives, identify situations, coordinate tools, and carry out specific actions. This report looks at the way in which AI agents can help to achieve autonomous service delivery in both telecom and enterprise operations while at the same time meeting the requirements relating to reliability, governance, cybersecurity, and human accountability that are linked to Saudi Vision 2030. The study makes use of a structured integrative review of peer-reviewed literature published between 2020 and 2025, with a focus on agentic AI, zero-touch network and service management, intent-based networking, AIOps, service operations, AI governance, human oversight, and Saudi digital transformation. The analysis highlights five interdependent capabilities: context-aware intent interpretation, multi-source observability, agentic reasoning and orchestration, closed-loop execution, and governance-by-design. It is shown that autonomy is most believable when it is implemented as bounded, observable, and reversible automation rather than as unrestricted machine control. Research in the telecom field has developed well-established foundations in the areas of intent life cycles, assurance, closed loops, and zero-touch management, whereas research relating to enterprise services brings in aspects such as incident intelligence, workflow enhancement, and service quality. The review introduces an Agentic Autonomous Service Delivery Framework that combines operational agents with policy constraints, confidence thresholds, digital audit trails, human escalation, and continuous assurance. This framework provides a practical research programme for Saudi organisations that wish to establish resilient, scalable, and trustworthy AI-enabled service operations in line with Vision 2030.
How to cite this paper
@article{1723620,
author = {Wamiq Rafi Syed},
title = {AI Agent–Driven Autonomous Service Delivery in Saudi Arabia: A Framework for Intelligent Telecom and Enterprise Operations under Vision 2030},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {4},
pages = {49-61},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1723620.pdf},
abstract = {The telecommunications and enterprise sectors in Saudi Arabia are progressing from digitally based service operations towards more autonomous operating models in which artificial intelligence is able to understand objectives, identify situations, coordinate tools, and carry out specific actions. This report looks at the way in which AI agents can help to achieve autonomous service delivery in both telecom and enterprise operations while at the same time meeting the requirements relating to reliability, governance, cybersecurity, and human accountability that are linked to Saudi Vision 2030. The study makes use of a structured integrative review of peer-reviewed literature published between 2020 and 2025, with a focus on agentic AI, zero-touch network and service management, intent-based networking, AIOps, service operations, AI governance, human oversight, and Saudi digital transformation. The analysis highlights five interdependent capabilities: context-aware intent interpretation, multi-source observability, agentic reasoning and orchestration, closed-loop execution, and governance-by-design. It is shown that autonomy is most believable when it is implemented as bounded, observable, and reversible automation rather than as unrestricted machine control. Research in the telecom field has developed well-established foundations in the areas of intent life cycles, assurance, closed loops, and zero-touch management, whereas research relating to enterprise services brings in aspects such as incident intelligence, workflow enhancement, and service quality. The review introduces an Agentic Autonomous Service Delivery Framework that combines operational agents with policy constraints, confidence thresholds, digital audit trails, human escalation, and continuous assurance. This framework provides a practical research programme for Saudi organisations that wish to establish resilient, scalable, and trustworthy AI-enabled service operations in line with Vision 2030.},
month = {October},
doi = {https://doi.org/10.64388/IREV10I4-1723620}
}