Architecting Autonomous Enterprise Platforms for Scalable, Self-Regulating Digital Systems
Abstract
The article goes deep into how businesses are moving off-hand manual platforms to autonomous digital systems that are capable of controlling their activities on their own. The paper addresses the basic structural architecture that enables self-regulation with emphasis put on event-driven architectures, AI-driven decision making engines, and closed-loop control systems. Such systems are meant to regulate, investigate, and adjust the operations since they do not need close management by the human beings. Some of the key concerns discussed include the type of government to rule the entities to maintain control of the risks and operational liability which ought to be present to maintain transparency and trust. The paper also explains that, a limited autonomy can provide a tradeoff between full autonomy and human intervention and this will provide a model that will not only be reliable but also provide the enterprises with the ability to scale and adapt in a dynamical environment. Lastly, this writing provides a futuristic vision of building autonomous enterprise systems with an implication that human agency must remain intact in a digital based future.
Article Information
Journal |
International Journal of Advanced Engineering Science and Information Technology (IJAESIT) |
|---|---|
Volume (Issue) |
Vol. 8 No. 5 (2025): International Journal of Advanced Engineering Science and Information Technology (IJAESIT) |
DOI |
|
Pages |
17292-17302 |
Published |
September 11, 2025 |
| Copyright | |
Open Access |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
How to Cite |
Prasanna Kumar Natta (2025). Architecting Autonomous Enterprise Platforms for Scalable, Self-Regulating Digital Systems. International Journal of Advanced Engineering Science and Information Technology (IJAESIT) , Vol. 8 No. 5 (2025): International Journal of Advanced Engineering Science and Information Technology (IJAESIT) , pp. 17292-17302. https://doi.org/10.15662/IJAESIT.2025.0805002 |
References
[2]Okkular, "The Metadata Revolution: Enhancing Fashion Search & Filters." [Online]. Available: https://www.okkular.io/the-metadata-revolution-boosting-search-and-filters-in-fashion-e-commerce-with-okkular-ai/
[3]Databricks, "Data Pipelines." [Online]. Available: https://www.databricks.com/glossary/data-pipelines
The Future of Data Platforms: AI-Driven Automation and Self-Optimizing SystemsPage | 488
[4]HenryJosh, et al., "Self-Healing Infrastructure: AI-Powered Automation for Fault-Tolerant DevOps Environments," ResearchGate, 2024. [Online]. Available: https://www.researchgate.net/publication/388634507_Self-Healing_Infrastructure_AI-Powered_Automation_for_Fault-Tolerant_DevOps_Environments
[5]Torana Kamble et al., "Predictive Resource Allocation Strategies for Cloud Computing Environments Using Machine Learning," ResearchGate, 2023. [Online]. Available: https://www.researchgate.net/publication/382150088_Predictive_Resource_Allocation_Strategies_for_Cloud_Computing_Environments_Using_Machine_Learning
[6]PP. BODORIK, J.S. RIORDON and C. JACOB, "DYNAMIC DISTRIBUTED QUERY PROCESSING TECHNIQUES," ACM, 1989. [Online]. Available: https://dl.acm.org/doi/pdf/10.1145/75427.75474
[7]Coherent Solutions, "AI-Powered Data Governance: Implementing Best Practices and Frameworks." [Online]. Available: https://www.coherentsolutions.com/insights/ai-powered-data-governance-implementing-best-practices-and-frameworks
[8]Stanford University Human-Centered Artificial Intelligence Institute, "The 2024 AI Index Report," 2024. [Online]. Available: https://hai.stanford.edu/ai-index/2024-ai-index-report
[9] van Eijk, T., Kumara, I., Di Nucci, D., Tamburri, D. A., & van den Heuvel, W.-J. (2024). Architectural design decisions for self-serve data platforms in data meshes. arXiv. https://arxiv.org/abs/2402.04681
[10] Padur, S. K. R. (2024). AI-augmented platform engineering: Redefining developer experience through autonomous, self-optimizing enterprise systems. International Journal of Scientific Research & Engineering Trends, 11(6). https://www.academia.edu/145277042/AI_Augmented_Platform_Engineering_Redefining_Developer_Experience_through_Autonomous_Self_Optimizing_Enterprise_Systems