Agentic AI Platforms: From Generative Models to Autonomous Systems

Abstract

Agentic AI Platforms: From Generative Models to Autonomous Systems presents a comprehensive academic exploration of the technologies, architectures and practices shaping the transition from generative artificial intelligence to intelligent, autonomous enterprise systems. It establishes the foundations of agentic platforms through enterprise reference architectures, cognitive architecture patterns, multi-agent systems and orchestration layers, before examining foundation models, Amazon Bedrock, model evaluation, retrieval-augmented generation, fine-tuning and custom AI services. The book develops the technological foundations required for connected and scalable agent ecosystems, addressing Model Context Protocol (MCP), agent-to-agent communication, interoperability and cloud-native infrastructure on AWS. It further examines intelligent automation, workflow orchestration, human-in-the-loop mechanisms, autonomous decision support, AI copilots and digital workers. Scientific workflows, digital laboratories and genomics applications extend these concepts into research, bioinformatics, precision medicine and autonomous scientific discovery. Security, trust and governance remain central throughout, encompassing agent identity, authentication, authorisation, zero-trust architectures and regulatory compliance. Industry applications across financial services, healthcare, pharmaceuticals, cybersecurity and manufacturing demonstrate practical relevance, while the concluding discussions explore reinforcement learning, digital twins, autonomous enterprises and emerging pathways towards artificial general intelligence.