Generative AI at AWS
Turn business strategy into production-ready AI applications and agents
Published on 29. May 2026
Book
Paperback/Softback
520 pages
978-1-80610-445-1 (ISBN)
Description
Bridge business goals and technical execution to build, deploy, and govern generative AI solutions on AWS
Key Features
Align business strategy with practical generative AI use cases on AWS
Build MVPs, agents, and production systems with Bedrock and SageMaker
Apply governance, scaling, and responsible AI practices across industries
Purchase of the print or Kindle book includes a free PDF eBook
Book DescriptionCut through the noise around generative AI and learn how to turn promising ideas into secure, scalable solutions on AWS. This book helps you connect business priorities with technical execution, so you can identify worthwhile use cases, select the right models and services, and move from pilot to production with confidence.
You explore the fundamentals of generative AI, understand how foundation models and agents work, and see where services such as Amazon Bedrock AgentCore and Amazon SageMaker AI fit into a modern AI stack. From there, the book guides you through preparing data, building an MVP, deploying production-ready applications, and designing for scalability, governance, and responsible AI.
Real-world industry examples and practical decision frameworks help you evaluate when to use generative AI, when traditional approaches are a better fit, and how to measure business value. You also examine advanced topics such as agentic AI, emerging patterns, and the future direction of enterprise AI.
By the end of this book, you will be able to plan, build, and govern generative AI solutions on AWS that deliver measurable value for your organization.
What you will learn
Understand how generative AI creates business value
Compare models, prompts, fine-tuning, and RAG
Navigate the AWS generative AI stack with confidence
Prepare data and select models for real use cases
Build MVPs and production-ready AI applications
Apply governance, ethics, and responsible AI controls
Evaluate agentic AI patterns and emerging trends
Measure impact across enterprise AI initiatives
Who this book is forDevelopers, solutions architects, technical product managers, innovation leaders, CTOs, and business decision-makers who want to plan, build, and scale generative AI solutions on AWS. It is ideal for teams moving from experimentation to production and for leaders aligning AI initiatives with business outcomes. A basic understanding of cloud concepts and software delivery is helpful.
Key Features
Align business strategy with practical generative AI use cases on AWS
Build MVPs, agents, and production systems with Bedrock and SageMaker
Apply governance, scaling, and responsible AI practices across industries
Purchase of the print or Kindle book includes a free PDF eBook
Book DescriptionCut through the noise around generative AI and learn how to turn promising ideas into secure, scalable solutions on AWS. This book helps you connect business priorities with technical execution, so you can identify worthwhile use cases, select the right models and services, and move from pilot to production with confidence.
You explore the fundamentals of generative AI, understand how foundation models and agents work, and see where services such as Amazon Bedrock AgentCore and Amazon SageMaker AI fit into a modern AI stack. From there, the book guides you through preparing data, building an MVP, deploying production-ready applications, and designing for scalability, governance, and responsible AI.
Real-world industry examples and practical decision frameworks help you evaluate when to use generative AI, when traditional approaches are a better fit, and how to measure business value. You also examine advanced topics such as agentic AI, emerging patterns, and the future direction of enterprise AI.
By the end of this book, you will be able to plan, build, and govern generative AI solutions on AWS that deliver measurable value for your organization.
What you will learn
Understand how generative AI creates business value
Compare models, prompts, fine-tuning, and RAG
Navigate the AWS generative AI stack with confidence
Prepare data and select models for real use cases
Build MVPs and production-ready AI applications
Apply governance, ethics, and responsible AI controls
Evaluate agentic AI patterns and emerging trends
Measure impact across enterprise AI initiatives
Who this book is forDevelopers, solutions architects, technical product managers, innovation leaders, CTOs, and business decision-makers who want to plan, build, and scale generative AI solutions on AWS. It is ideal for teams moving from experimentation to production and for leaders aligning AI initiatives with business outcomes. A basic understanding of cloud concepts and software delivery is helpful.
More details
Language
English
Place of publication
Birmingham
United Kingdom
Dimensions
Height: 235 mm
Width: 191 mm
Thickness: 28 mm
Weight
960 gr
ISBN-13
978-1-80610-445-1 (9781806104451)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Nestor Gandara is a technology leader with over 20 years of IT experience specializing in Generative AI, cloud, and digital transformation. As Principal Partner SA and Generative AI Strategist at Amazon Web Services, he partners with C-suite executives to bridge the gap between technology and business value. Nestor is a program lead, mentor, and learning facilitator for MIT Professional Education and a faculty member at IENYC and ISDI. As the Founder of NextLevelguru and author of "The Art of Building Your Resilience and Adaptability," by combining executive leadership with talent mentoring, he holds a unique position at the intersection of Next-Gen Enterprise technology, education, and business strategy. Eduardo Ordax is a Principal GenAI Go-to-Market Lead at AWS with 15+ years of experience across technology, combining technical and business leadership with a strong passion for AI. Recognized as the #1 AI influential voice in Spain and among the #Top20 worldwide, I'm an international keynote speaker and postgraduate lecturer. I actively share insights on AI innovation, strategy, and real-world adoption with a community of 200,000+ professionals on LinkedIn, contributing to shaping the future of artificial intelligence. Srikanth Daggumalli is a Senior Analytics & AI Specialist Solutions Architect at Amazon Web Services, specializing in generative AI, machine learning, and cloud-native data architectures. With nearly two decades of experience, he has architected mission-critical data platforms across financial services, insurance, retail, automotive, ISV, and digital-native sectors, spanning global payments, anti-money laundering, credit-risk management, and enterprise analytics for Fortune 500 organizations. He is an IEEE Senior Member, IETE Fellow, and Technical Program Committee member and peer reviewer for IEEE conferences and Manning Publications. His articles on InfoQ and the AWS Big Data Blog have been syndicated across more than 15 international platforms. Ashutosh Dubey is a technology leader and recognized expert in Generative and Agentic AI at Amazon Web Services. He empowers enterprise leaders to operationalize artificial intelligence at a global scale. A dedicated advocate for technical education and community engagement, he regularly shares industry insights through his public blogs. He is the coauthor of Generative AI for Software Developers and Interview Guide for Solution Architects, providing practical guidance for engineering and leadership teams navigating the complexities of modern software design.
Content
Table of Contents
The Generative AI Revolution - Why It Matters Now
How Generative AI Works
The AWS Generative AI Stack - Tools of the Trade
Data Readiness and Model Selections
Build an Agentic GenAI Application
Production-Ready Agentic & GenAI Applications
Advanced Techniques and Emerging Trends
From Strategy to Use Case - Identifying Business Value
Industry Spotlights and Case Studies
Governance Ethics and Responsible AI
Empowering People, Teams, and Culture in the Age of GenAI
The Future of Generative AI
The Generative AI Revolution - Why It Matters Now
How Generative AI Works
The AWS Generative AI Stack - Tools of the Trade
Data Readiness and Model Selections
Build an Agentic GenAI Application
Production-Ready Agentic & GenAI Applications
Advanced Techniques and Emerging Trends
From Strategy to Use Case - Identifying Business Value
Industry Spotlights and Case Studies
Governance Ethics and Responsible AI
Empowering People, Teams, and Culture in the Age of GenAI
The Future of Generative AI