Agentic AI in Enterprise: Harnessing Agentic AI for Business Transformation
暫譯: 企業中的代理式人工智慧：利用代理式人工智慧推動商業轉型
Ranjan, Sumit, Chembachere, Divya, Lobo, Lanwin
相關主題
商品描述
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 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.
This book is for: Enterprise Architects.
商品描述(中文翻譯)
這本書深入探討了企業代理人工智慧（Enterprise Agentic AI）的變革力量，追溯其從基本自動化到能夠進行情境推理、記憶保留和自主決策的智能代理的演變。它為希望將代理人工智慧無縫整合到其運營中的企業提供了一個戰略路線圖，同時確保可擴展性、效率和安全性。
讀者將探索架構最佳實踐，包括雲端、混合和本地部署模型，並獲得有關大型語言模型（LLM）優化策略的見解，如檢索增強生成（Retrieval-Augmented Generation, RAG）和微調。這本書還涵蓋了先進的提示工程技術、向量資料庫在人工智慧驅動應用中的角色，以及確保道德、透明和負責任的人工智慧採用的治理框架。
通過真實案例研究，這本書展示了人工智慧在零售、醫療保健、供應鏈管理和客戶互動中的影響。它還探討了人工智慧進步的下一波浪潮，如自主決策、人工智慧增強的領導力，以及人類專業知識與智能代理在企業環境中不斷演變的協同作用。
在本書結束時，讀者將擁有設計、部署和管理不僅是尖端技術，還符合企業安全、治理和道德標準的人工智慧代理的知識和工具。
您將會：
- 了解人工智慧代理如何超越傳統模型，通過整合情境推理、長期記憶和自主決策來增強企業運營。
- 探索可擴展的部署模型（雲端、混合、本地）以及將大型語言模型、向量資料庫和提示工程整合到您的人工智慧工作流程中的最佳實踐。
- 發展健全的人工智慧治理框架，進行風險評估，並實施安全協議以保護企業數據，同時確保負責任的人工智慧採用。
- 獲得有關人工智慧部署中的透明度、問責制和公平性的見解，確保人工智慧代理與企業價值觀和全球道德標準保持一致。
這本書適合：企業架構師。
作者簡介
Sumit Ranjan is a visionary artificial intelligence leader with over a decade of experience designing and deploying enterprise-grade AI solutions grounded in trust, security, and scalability. As the Head of Responsible AI at Forcespot in Dubai, he leads the development of intelligent systems that enable organizations to adopt AI confidently while maintaining rigorous standards of safety and accountability.
A recognized expert in NLP, Computer Vision, Generative AI, and Agentic AI, Sumit specializes in architecting adaptive, high-impact AI agents tailored to complex, real-world industry needs. His work bridges cutting-edge innovation with principled design, ensuring AI systems remain both effective and ethically grounded.
Sumit is currently pursuing his PhD at BITS Pilani, Dubai Campus, where his research focuses on the intersection of advanced AI technologies and responsible governance frameworks. He is also an active contributor to the OWASP AI Exchange, where he collaborates on global initiatives to strengthen AI security and transparency.
Divya Chembachere is a seasoned Lead Data Scientist at MResult Corp, with over 12 years of experience in software engineering, cloud architecture, and enterprise application development. Recognized for her technical acumen and innovative approach, she specializes in designing advanced AI solutions, with deep expertise in Generative AI, NLP and Computer Vision. Her research, published in globally acclaimed journals such as Springer Nature, underscores her contributions to cutting-edge advancements in data science.
Currently, Divya leads the development of enterprise-grade AI systems for the pharmaceutical sector, addressing industry-specific challenges through scalable, AI-driven frameworks. Her work prominently features the implementation of large language models (LLMs) for downstream tasks, demonstrating her ability to translate complex research into practical, high-impact applications.
Lanwin Lobo, Director of Data Science and Generative AI at Mresult Corp, is a visionary in the field of Enterprise Agentic AI, particularly as it applies to the pharmaceutical industry. With a Masters in Bioinformatics and over 14 years of experience, Lanwin has been at the forefront of integrating advanced Agentic and Generative AI technologies to transform complex pharma operations. His work in developing intelligent, autonomous systems has not only streamlined decision-making and enhanced predictive analytics but has also set a new standard for responsible and secure AI implementation in healthcare.
作者簡介(中文翻譯)
Sumit Ranjan 是一位具前瞻性的人工智慧領導者，擁有超過十年的經驗，專注於設計和部署以信任、安全性和可擴展性為基礎的企業級 AI 解決方案。作為位於杜拜的 Forcespot 負責任 AI 部門負責人，他領導開發智能系統，使組織能夠自信地採用 AI，同時保持嚴格的安全和問責標準。
作為自然語言處理 (NLP)、計算機視覺、生成式 AI 和代理 AI 的公認專家，Sumit 專注於架構適應性強、影響深遠的 AI 代理，這些代理針對複雜的現實行業需求量身定制。他的工作將尖端創新與原則設計相結合，確保 AI 系統既有效又符合倫理。
Sumit 目前在 BITS Pilani 杜拜校區攻讀博士學位，他的研究重點是先進 AI 技術與負責任治理框架的交集。他也是 OWASP AI Exchange 的活躍貢獻者，參與全球倡議以加強 AI 的安全性和透明度。
Divya Chembachere 是 MResult Corp 的資深首席數據科學家，擁有超過 12 年的軟體工程、雲架構和企業應用開發經驗。因其技術敏銳度和創新方法而受到認可，她專注於設計先進的 AI 解決方案，並在生成式 AI、自然語言處理和計算機視覺方面擁有深厚的專業知識。她的研究發表在全球知名期刊如 Springer Nature，突顯了她對數據科學前沿進展的貢獻。
目前，Divya 領導為製藥行業開發企業級 AI 系統，通過可擴展的 AI 驅動框架解決行業特定挑戰。她的工作顯著體現了大型語言模型 (LLMs) 在下游任務中的應用，展示了她將複雜研究轉化為實用、高影響力應用的能力。
Lanwin Lobo 是 MResult Corp 的數據科學和生成式 AI 總監，在企業代理 AI 領域具有前瞻性，特別是在製藥行業的應用方面。擁有生物資訊學碩士學位和超過 14 年的經驗，Lanwin 一直站在整合先進代理和生成式 AI 技術的最前沿，以改變複雜的製藥運營。他在開發智能、自主系統方面的工作不僅簡化了決策過程和增強了預測分析，還為醫療保健中負責任和安全的 AI 實施樹立了新標準。
