Articles Open Access
Accelerating Enterprise Innovation Using Generative AI for Autonomous Intelligence and Cloud-Native Platforms
IFCO Systems, Spain
Abstract
The increasing demand for digital transformation has encouraged enterprises to adopt advanced technologies that improve innovation, operational efficiency, and business agility. Generative Artificial Intelligence (Generative AI), autonomous intelligence, and cloud-native platforms have emerged as critical technologies enabling organizations to build intelligent, adaptive, and scalable enterprise ecosystems. Generative AI enhances enterprise capabilities by generating knowledge, automating complex workflows, supporting software development, and providing intelligent decision assistance through advanced machine learning models. Autonomous intelligence extends these capabilities by enabling systems to perceive operational environments, analyze real-time information, make decisions, and execute actions with limited human intervention. Cloud-native platforms provide the foundation for deploying these intelligent applications through scalable architectures based on microservices, containers, orchestration frameworks, serverless computing, and automated infrastructure management. This paper explores how enterprises can accelerate innovation by integrating Generative AI with autonomous intelligence and cloud-native engineering practices. The proposed approach focuses on intelligent automation, continuous software delivery, predictive analytics, cybersecurity, observability, and adaptive resource management. The integration of these technologies enables organizations to improve productivity, reduce operational complexity, enhance customer experiences, and rapidly respond to changing market requirements. The study highlights the importance of responsible AI governance, secure architecture design, and continuous optimization for developing reliable and sustainable enterprise platforms capable of supporting future digital innovation.
Keywords
Generative AIAutonomous IntelligenceEnterprise InnovationCloud-Native PlatformsArtificial IntelligenceMachine LearningIntelligent AutomationDigital TransformationCloud ComputingMicroservicesKubernetesDevOpsContinuous IntegrationContinuous DeploymentInfrastructure as CodeEnterprise ArchitectureAI GovernancePredictive AnalyticsSoftware EngineeringIntelligent Enterprise Systems
DOI
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Publication Information
| Journal | International Research Journal of Innovative Engineering |
|---|---|
| Volume | 9 |
| Number | 6 |
| Pages | 17890-17902 |
| Published | 2025-11-06 |
| Issue | Vol. 9 No. 6 (2025): International Research Journal of Innovative Engineering (IRJIE) |
References
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27. Kanji, R. K. (2021). Real-Time Big Data Processing with Edge Computing. European Journal of Advances in Engineering and Technology, 8(11), 152-155.
28. Velishala, S. (2025). AI-based decision support systems for healthcare DevOps: Improving reliability and decision-making in software development. Journal of Advanced Research in Engineering and Technology, 2(1).
29. Chettiyar, S. S. S. (2024). Agentic AI orchestrated conversational payment pipelines with drift-aware transaction. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(3), 8166–8174. https://doi.org/10.15662/IJEETR.2024.0603008
30. Anbazhagan, K. (2024). Trustworthy and Adaptive AI Systems for Enterprise Analytics Cybersecurity and Decision Optimization Using API-First and Cloud-Native Architectures. International Journal of Technology, Management and Humanities, 10(03), 65-74.
31. Mannem, S. (2024). From requirements to production: Managing cross-regional API deployments at Capital One. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(2), 7892–7898. https://doi.org/10.15662/IJEETR.2024.0602013
32. Devineni, A. (2025). Automated Remediation Guardrails: A Risk-Aware Framework for Validating AI-Generated Production Scripts in Regulated Financial Infrastructure. International Journal of AI, BigData, Computational and Management Studies, 6(2), 113-118.
33. Gurram, S. K. (2024). Federated learning for anomaly detection in distributed systems. International Journal of Future Innovative Science and Technology (IJFIST), 7(6), 14031–14040.
2. Veershetty, G. (2019). From Legacy Back Office to Intelligent Utility Enterprise a Practitioner Case Study of SAP Cloud Transformation and Utility IT Landscape Modernization. American International Journal of Computer Science and Technology, 1(1), 23-27.
3. Makkena, B. (2025). Zero-Downtime Deployment Strategies In Financial-Grade CI/CD Pipelines: Enabling Continuous Compliance And Resilience. International Journal of Environmental Sciences, 11(19s), 2025.
4. Rao, G. R. (2023). Index lifecycle and shard allocation optimization in large-scale Elasticsearch clusters: A performance–cost trade-off analysis. International Journal of Engineering & Extended Technologies Research (IJEETR), 5(4), 6903–6907.
5. Sugumar, R. (2025). Open Ecosystems in Finance: Balancing Innovation, Security, and Compliance. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 8(1), 11548-11554.
6. Gurram, S. K. (2024). Federated learning for anomaly detection in distributed systems. International Journal of Future Innovative Science and Technology (IJFIST), 7(6), 14031–14040.
7. Potdar, A., Kodela, V., Srinivasagopalan, L. N., Khan, I., Chandramohan, S., & Gottipalli, D. (2025, July). Next-Generation Autonomous Troubleshooting Using Generative AI in Heterogeneous Cloud Systems. In 2025 International Conference on Information, Implementation, and Innovation in Technology (I2ITCON) (pp. 1-7). IEEE.
8. Gummadi, V. P. K. (2019). Microservices architecture with APIs: Design, implementation, and MuleSoft integration. Journal of Electrical Systems, 15(4), 130-134.
9. Mathew, A. (2024). Cloud data sovereignty governance and risk implications of cross-border cloud storage. Information Systems Audit and Control Association.
10. Govindan, V. (2025). Vendor dependency to enterprise sovereignty: A phased migration approach for enterprise applications. International Journal of Computer Technology and Electronics Communication (IJCTEC), 8(4), 11176–11185. https://doi.org/10.15680/IJCTECE.2025.0804021
11. Soundappan, S. J. (2024). Generative AI Enabled Enterprise Systems with Autonomous Operations and Cloud-Native Architectures. International Journal of Computer Technology and Electronics Communication, 7(4), 9247-9253.
12. Konakalla, K. (2022). Automating customer feedback integration in the sales cycle: Enhancing sales performance and accountability through Salesforce and Medallia. Journal of Marketing & Supply Chain Management, 1-3.
13. Navandar, P. (2024). Quantum safe public key infrastructure: Hybrid classical PQC certificate chains and migration framework for enterprise TLS. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(4), 8153–8160. https://doi.org/10.15662/IJEETR.2024.0604014
14. Mohammed, S. (2024). Resilient multi-region cloud architecture for high availability and disaster recovery. International Journal of Multidisciplinary and Scientific Emerging Research, 12(3), 1412–1427. https://doi.org/10.15662/IJMSERH.2024.1203046
15. Kandula, S. T. R. (2025, July). Comparison and Performance Assessment of Intelligent ML Models for Forecasting Cardiovascular Disease Risks in Healthcare. In 2025 International Conference on Sensors and Related Networks (SENNET) Special Focus on Digital Healthcare (64220) (pp. 1-6). IEEE.
16. Juvvadi, R. R. (2019). Smart contracts in supply chain finance: Automating accounts payable and the three-way match. Journal of Information Systems Engineering and Management, 4(1), 1–12.
17. Gopisetty, S. (2024). What the Jenkins Logs Won’t Tell You: Using an AI Agent to Capture the Lost ‘Bank Memory’Behind a 76% Sprint Velocity Gain and Whether Another Community Bank Can Borrow It Without the Original Team. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 5(3), 259-276.
18. Adari, V. K. (2024). How Cloud Computing is Facilitating Interoperability in Banking and Finance. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 7(6), 11465-11471.
19. Gandikota, S. P. (2025). High-availability network diagnostics and configuration platform for real-time financial service delivery. International Journal of Computer Technology and Electronics Communication (IJCTEC), 8(4), 11147–11160. https://doi.org/10.15680/IJCTECE.2025.0804019
20. Chenna, S. (2024). Reinforcement learning-based dynamic load assignment for automated 3PL tendering systems. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(2), 7917–7932. https://doi.org/10.15662/IJEETR.2024.0602015
21. Gopinathan, V. R., & Mali, R. K. (2024). Enterprise digital transformation through AI Salesforce automation secure cloud infrastructure and event-driven architectures. International Research Journal of Innovative Engineering (IRJIE), 8(5), 15322–15331.
22. Polamreddy, V. R. (2022). Architecting Hybrid Synchronization Models to Enable Safe International Platform Transitions. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 5(1), 6216-6229.
23. Syed, S. (2025). Enterprise asset management digitalization for multi-site pharmaceutical manufacturing: A transatlantic Oracle eAM implementation. International Journal of Computer Technology and Electronics Communication (IJCTEC), 8(4), 11138–11146. https://doi.org/10.15680/IJCTECE.2025.0804018
24. Kotla, M. R. T. (2024). Optimizing enterprise integration pipelines using cloud-native data engineering and middleware solutions. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 7(5), 11311-11314.
25. Sarngadharan, S. (2025). Self-optimizing pipelines: ML systems that tune themselves in production. International Journal of Computer Technology and Electronics Communication (IJCTEC), 8(2), 10468–10476. https://doi.org/10.15680/IJCTECE.2025.0802015
26. Velishala, S. (2025). Leveraging machine learning in DevOps pipelines to enhance patient data management systems. ISCSITR–International Journal of Computer Science and Engineering, 6(1), 31–49.
27. Kanji, R. K. (2021). Real-Time Big Data Processing with Edge Computing. European Journal of Advances in Engineering and Technology, 8(11), 152-155.
28. Velishala, S. (2025). AI-based decision support systems for healthcare DevOps: Improving reliability and decision-making in software development. Journal of Advanced Research in Engineering and Technology, 2(1).
29. Chettiyar, S. S. S. (2024). Agentic AI orchestrated conversational payment pipelines with drift-aware transaction. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(3), 8166–8174. https://doi.org/10.15662/IJEETR.2024.0603008
30. Anbazhagan, K. (2024). Trustworthy and Adaptive AI Systems for Enterprise Analytics Cybersecurity and Decision Optimization Using API-First and Cloud-Native Architectures. International Journal of Technology, Management and Humanities, 10(03), 65-74.
31. Mannem, S. (2024). From requirements to production: Managing cross-regional API deployments at Capital One. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(2), 7892–7898. https://doi.org/10.15662/IJEETR.2024.0602013
32. Devineni, A. (2025). Automated Remediation Guardrails: A Risk-Aware Framework for Validating AI-Generated Production Scripts in Regulated Financial Infrastructure. International Journal of AI, BigData, Computational and Management Studies, 6(2), 113-118.
33. Gurram, S. K. (2024). Federated learning for anomaly detection in distributed systems. International Journal of Future Innovative Science and Technology (IJFIST), 7(6), 14031–14040.
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