Agent Orchestration: A New Paradigm for Autonomous and Scalable MarTech Ecosystems
DOI:
https://doi.org/10.63397/ISCSITR-IJCSE_2025_06_04_005Keywords:
Orchestration, Autonomous, Agent, ScalableAbstract
The paradigm presented in the paper extends the ability to orchestrate an agent in the context of MarTech ecosystem to achieve autonomous, scalable coordination of heterogeneous tools and compositions, including CRM systems, content engines, analytics platforms, and ad networks. Going further into dynamic automation, the suggested multi-layer orchestration architecture finds a holistic way to build and monitor on-the-fly agent workflows to satisfy changing campaign and CX goals. Empirical tests indicate increases in customisation accuracy, campaign responsiveness, system elasticity and consumer connectivity. Also, the orchestrator minimizes human interaction and delay of operations to a great extent. The paper also discusses the aspect of governance, compliance, and ethics with the view that agent orchestration is a foundation block of next-generation, intelligent marketing architectures.
References
Agrawal, K., & Nargund, N. (2025). Neural Orchestration for Multi-Agent Systems: A Deep Learning Framework for Optimal Agent Selection in Multi-Domain Task Environments. arXiv preprint arXiv:2505.02861. https://doi.org/10.48550/arXiv.2505.02861
Harper, J. (2024). AutoGenesisAgent: Self-Generating Multi-Agent systems for complex tasks. arXiv (Cornell University). https://doi.org/10.48550/arxiv.2404.17017
Tallam, K. (2025). From autonomous agents to integrated systems, a new paradigm: Orchestrated distributed intelligence. arXiv preprint arXiv:2503.13754. https://doi.org/10.48550/arXiv.2503.13754
Nguyen, T. T., Nguyen, N. D., & Nahavandi, S. (2020). Deep reinforcement learning for multiagent systems: A review of challenges, solutions, and applications. IEEE transactions on cybernetics, 50(9), 3826-3839. https://doi.org/10.48550/arXiv.1812.11794
Abbas, H. A., Shaheen, S. I., & Amin, M. H. (2015). Organization of multi-agent systems: an overview. arXiv preprint arXiv:1506.09032. https://doi.org/10.48550/arXiv.1506.09032
Herrera, V. V., Ramos, A. V., & Lastra, J. L. M. (2011). An agent-based system for orchestration support of web service-enabled devices in discrete manufacturing systems. Journal of Intelligent Manufacturing, 23(6), 2681–2702. https://doi.org/10.1007/s10845-011-0539-z
Chen, C. H., & Shiu, M. F. (2025). AgentFlow: Resilient Adaptive Cloud-Edge Framework for Multi-Agent Coordination. arXiv preprint arXiv:2505.07603. https://doi.org/10.48550/arXiv.2505.07603
Cao, Y., Yu, W., Ren, W., & Chen, G. (2012). An overview of recent progress in the study of distributed multi-agent coordination. arXiv (Cornell University). https://doi.org/10.48550/arxiv.1207.3231
Manda, C. (2024, December 27). SCALABLE MULTI-AGENT ARCHITECTURE FOR ENTERPRISE CUSTOMER EXPERIENCE: DESIGN PATTERNS AND IMPLEMENTATION. https://mylib.in/index.php/IJCET/article/view/1887-1898
Kishore, R., Zhang, H., & Ramesh, R. (2004). Enterprise integration using the agent paradigm: foundations of multi-agent-based integrative business information systems. Decision Support Systems, 42(1), 48–78. https://doi.org/10.1016/j.dss.2004.09.011
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Ashwaray Chaba (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
