Autonomous Enterprise Platforms Using Cognitive Computing Techniques
TL;DR
Cognitive computing is a key enabler of intelligent, adaptive, and autonomous enterprise ecosystems and the proposed framework combines data acquisition, cognitive analytics, machine learning, knowledge management, and autonomous execution layers, supported by reinforcement learning, deep learning, and NLP.
Abstract
Digital transformation has increased enterprise complexity, creating a need for intelligent systems that can autonomously learn, adapt, and make decisions. Cognitive computing integrates AI, machine learning, natural language processing, and reasoning techniques to develop Autonomous Enterprise Platforms (AEPs) that optimize business operations with minimal human intervention. The proposed framework combines data acquisition, cognitive analytics, machine learning, knowledge management, and autonomous execution layers, supported by reinforcement learning, deep learning, and NLP. Experimental results show improvements in decision accuracy, operational efficiency, automation, adaptability, and customer satisfaction compared to traditional systems. The study also addresses challenges such as data governance, security, scalability, and AI ethics, while highlighting future technologies including generative AI, explainable AI, federated learning, digital twins, and autonomous agents. The findings demonstrate that cognitive computing is a key enabler of intelligent, adaptive, and autonomous enterprise ecosystems.