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[null,null,"Autore",null,"Ranjan Sumit"]
[null,null,"Titolo",null,"Agentic AI in Enterprise : Harnessing Agentic AI for Business Transformation / / by Sumit Ranjan, Divya Chembachere, Lanwin Lobo"]
[null,null,"Pubbl/distr/stampa",null,"Berkeley, CA : , : Apress : , : Imprint : Apress, , 2025"]
[null,null,"ISBN",null,"979-88-6881-542-3"]
[null,null,"Edizione",null,"[1st ed. 2025.]"]
[null,null,"Descrizione fisica",null,"1 online resource (267 pages)"]
[null,null,"Collana",null,"Professional and Applied Computing Series"]
[null,null,"Disciplina",null,"658.5/14"]
[null,null,"Soggetti",null,"Artificial intelligence - Industrial applications"]
[{"$nulls":4},"Business enterprises - Technological innovations"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Chapter 1: Introduction to Enterprise Agentic AI -- Chapter 2: Designing with the Well-Architected Agentic AI Framework -- Chapter 3: Architectural Patterns for LLM Adoption in Agentic AI -- Chapter 4: Enhancing LLMs for Agentic AI: RAG vs. Fine-Tuning -- Chapter 5: Mastering Prompt Engineering in Enterprise Agentic AI -- Chapter 6: Vector Databases in AI Applications in Enterprise Agentic AI -- Chapter 7: Ethical and Security Considerations in Enterprise Agentic AI -- Chapter 8: Case Studies: Agentic AI - Real-World Applications -- Chapter 9: AI AGENTS- Future Trends in Enterprise AI -- Chapter 10: Conclusion – The Age of Enterprise Agentic AI."]
[null,null,null,"Sommario/riassunto","This book delves into the transformative power of Enterprise Agentic AI, tracing its evolution from basic automation to intelligent agents capable of contextual reasoning, memory retention, and autonomous decision-making. It provides a strategic roadmap for enterprises looking to integrate Agentic AI seamlessly into their operations while ensuring scalability, efficiency, and security. Readers will explore architectural best practices, including cloud, hybrid, and on-premises deployment models, and gain insights into LLM optimization strategies like Retrieval-Augmented Generation (RAG) and fine-tuning. The book also covers advanced prompt engineering techniques, the role of vector databases in AI-driven applications, and governance frameworks to ensure ethical, transparent, and responsible AI adoption. Through real-world case studies, the book illustrates AI’s impact across retail, healthcare, supply chain management, and customer engagement. It also examines the next wave of AI advancements, such as autonomous decision-making, AI-augmented leadership, and the evolving synergy "]
[{"$nulls":4},"between human expertise and intelligent agents in enterprise settings. By the end of this book, readers will have the knowledge and tools to design, deploy, and manage AI agents that are not only cutting-edge but also aligned with enterprise security, governance, and ethical standards. You Will: Understand how AI agents go beyond traditional models by incorporating contextual reasoning, long-term memory, and autonomous decision-making to enhance enterprise operations. Explore scalable deployment models (cloud, hybrid, on-premises) and best practices for integrating LLMs, vector databases, and prompt engineering into your AI workflows. Develop robust AI governance frameworks, conduct risk assessments, and implement security protocols to safeguard enterprise data while ensuring responsible AI adoption. Gain insights into transparency, accountability, and fairness in AI deployments, ensuring AI agents align with corporate values and global ethical standards."]