LEADER 04481nam 22005415 450 001 9911021144803321 005 20250814130233.0 010 $a979-88-6881-542-3 024 7 $a10.1007/979-8-8688-1542-3 035 $a(MiAaPQ)EBC32262222 035 $a(Au-PeEL)EBL32262222 035 $a(CKB)40332808900041 035 $a(CaSebORM)9798868815423 035 $a(OCoLC)1532521571 035 $a(OCoLC-P)1532521571 035 $a(DE-He213)979-8-8688-1542-3 035 $a(OCoLC)1535400231 035 $a(EXLCZ)9940332808900041 100 $a20250814d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAgentic AI in Enterprise $eHarnessing Agentic AI for Business Transformation /$fby Sumit Ranjan, Divya Chembachere, Lanwin Lobo 205 $a1st ed. 2025. 210 1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2025. 215 $a1 online resource (267 pages) 225 1 $aProfessional and Applied Computing Series 311 08$a979-88-6881-541-6 327 $aChapter 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. 330 $aThis 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 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. 410 0$aProfessional and Applied Computing Series 606 $aArtificial intelligence$xIndustrial applications 606 $aBusiness enterprises$xTechnological innovations 615 0$aArtificial intelligence$xIndustrial applications. 615 0$aBusiness enterprises$xTechnological innovations. 676 $a658.5/14 700 $aRanjan$b Sumit$01844475 701 $aChembachere$b Divya$01844476 701 $aLobo$b Lanwin$01844477 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911021144803321 996 $aAgentic AI in Enterprise$94427130 997 $aUNINA