Ranjan / Chembachere / Lobo Agentic AI in Enterprise

Harnessing Agentic AI for Business Transformation
1. Auflage 2025
ISBN: 979-8-8688-1542-3
Verlag: APRESS
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 406 Seiten

Reihe: Professional and Applied Computing

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. 

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Ranjan, Sumit

Chembachere, Divya

Lobo, Lanwin

Inhaltsverzeichnis

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.

Über Autor(innen)

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.