Cognitive Orchestration of Enterprise Workflows Using AI-Augmented Decision Engines in Distributed Systems
DOI:
https://doi.org/10.22399/ijcesen.5506Keywords:
AI-augmented decision engines, Distributed workflow orchestration, Predictive process monitoring, Prescriptive analytics, Enterprise cognitive automationAbstract
In a growing number of enterprise workflows, decision latency, uncertainty, and inter-service dependency across cloud, edge, robotic process automation, event-streaming, and human-in-the-loop applications can negatively impact the operational performance. The evidence base is fragmented across BPM, predictive process monitoring, prescriptive analytics, distributed systems, RL, explainable AI, and federated learning, and there is clear evidence of the potential value of the decisions that can be made with AI assistance. This review assesses peer-reviewed publications and academic books and outlines the issues of implementing, governing, and scaling cognitive orchestration in distributed enterprise systems. This review is not meant to be general and introductory, but is supposed to focus on methodological patterns, architectural implications, model classes, runtime constraints, and unfulfilled research needs. The general direction is from prediction and scheduling modules to closed-loop orchestration, with the event logs, contextual streams, constraint modelling, optimization routines and learning agents all feeding into the run-time decision making. In current work the problem of prediction, prescription, explainability, fault tolerance, privacy and human oversight are considered as distinct design problems. But there is a lot more to be done to craft causally grounded decision engines, to allow cross-organizational workflow learning, to provide benchmark datasets, to have runtime verification, to implement drift-aware governance, and to have a standard way to evaluate enterprise-scale deployments, including under stress like API migrations spanning more than 200 endpoints across 18 services, or transaction-critical workflows approaching US$20 billion in annualized transaction value. Distributed consistency, interpretable decision logic, adaptive optimization, and auditable control, within realistic enterprise constraints, will be essential to the future.
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