The Microsoft AI Insider's Playbook

Your Guide to Cloud Strategy and Digital Transformation
1. Auflage 2026
ISBN: 979-8-8688-2729-7
Verlag: Apress

Buch, Englisch, 651 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 1264 g

Most books on Microsoft AI explain what the tools do. This one explains why they were built that way—and how to use that knowledge to your advantage.

Krishna C. Mukherjee is a pioneering Microsoft technologist whose teams shipped the intelligent assistance features now used by hundreds of millions of people, including AutoCorrect, AutoFormat, and the spelling and grammar checkers in Microsoft Office. He architected the Intelligent Filing Manager, an AI-driven compliance system whose declarative, service-oriented design foreshadowed patterns that would later become common in SaaS platforms. He led the creation of the Bloomberg Valuation Service, applying predictive analytics to millions of financial instruments across asset classes. His career spans mainframes, personal computing, and the current era of cloud computing and AI, with a consistent focus on turning advanced capabilities into practical enterprise tools.

Tracing the evolution from Microsoft’s early innovations to the intelligent enterprise, the book shows how usability, scalability, and automation shaped the modern platform. It then moves into practice: Agile delivery and efficient process design; Azure, SaaS, and strategic cloud–AI architecture; Azure AI Services; the Copilot ecosystem; and the Power Platform—all grounded in real patterns, case studies, and lessons from finance, health care, retail, and legal services.

The result is a clear, experience-driven guide to building modern cloud–AI systems—connecting Microsoft’s platform decisions with the systems you are building today.

What You Will Learn

• Architect and implement Azure AI Services (now Foundry Tools), including Azure OpenAI Service, Speech, Language, Vision, and Document Intelligence, to build enterprise-grade conversational AI and virtual assistants
• Apply reference patterns for data pipelines, retrieval-augmented applications, model serving, and SaaS integration, while balancing latency, reliability, quality, and cost
• Map business processes, assess data readiness, quantify impact, and prioritize a staged roadmap from proof of concept to production
• Design cloud–AI architectures that balance performance, cost, and governance from the outset
• Govern AI deployments in practice, covering security, privacy, compliance, monitoring, drift detection, incident response, and cost control

Who This Book Is For 

Enterprise and cloud architects, Azure practitioners, and data and machine learning leaders responsible for planning or executing AI-driven digital transformation

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Mukherjee, Krishna C.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Microsoft Programmierung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Chapter 1: Foundations: Microsoft from BASIC to AI.- Chapter 2: Usability and Scalability: Lessons from Windows.- Chapter 3: The Need for Automation.- Chapter 4: The Intelligent Filing Manager.- Chapter 5: Declarative Programming.- Chapter 6: Business Process Efficiency.- Chapter 7: Agile Software Development.- Chapter 8: Cloud Computing Essentials: Understanding Azure.- Chapter 9: The Evolution of SaaS: From Cloud Modernization to AI-native Design.- Chapter 10: Strategic Cloud-AI Architecture.- Chapter 11: Azure AI Services: A Deep Dive.- Chapter 12: The Copilot Ecosystem.- Chapter 13: The Power Platform.- Chapter 14: The Intelligence Revolution: Bringing It All Together.- Glossary.- Appendix 1: Historical Computer Storage Formats.- Appendix 2: Programming Languages Used with Mainframes.- Appendix 3: Key Moments in the History of Windows.- Appendix 4: Architecture of the Windows Operating System.- Appendix 5: Sophisticated Document Management Systems.- Appendix 6: INTELLIFM: AI Meets COM Architecture.- Appendix 7: Prompt Engineering in Practice.- Appendix 8: Overview of Software Development Roles.- Appendix 9: Popular Design and Prototyping Tools.- Appendix 10: Popular AI Tools.- Appendix 11: Popular SaaS Products.- Appendix 12: API Architecture Overview.

Über Autor(innen)

Krishna C. Mukherjee is a pioneering Microsoft technologist, software architect, and technology executive whose work in artificial intelligence (AI) and enterprise systems has helped shape widely adopted computing platforms. His career spans mainframes, personal computing, and modern cloud-based AI, with a consistent focus on turning advanced capabilities into practical tools for enterprise use. 

Krishna earned his bachelor’s degree in electronics and electrical communication engineering from the Indian Institute of Technology (IIT) Kharagpur and his master’s degree in computer science and engineering from IIT Kanpur. His early research in AI planning systems and natural language processing at IIT Kanpur laid the foundation for his long-term work in intelligent systems. 

Recruited from IIT Kanpur to Microsoft Corporation in 1988, Krishna served on core engineering teams from the late 1980s through the mid-1990s and contributed to foundational technologies that underpin modern software ecosystems. His work included interoperability technologies such as Object Linking and Embedding and the Component Object Model, as well as automation capabilities in Microsoft Word and Microsoft Office. He helped develop WordBASIC, the macro language for Microsoft Word, and later contributed to Visual Basic for Applications. His teams shipped the early, largely rule-based intelligent assistance features in Microsoft Office, including AutoCorrect and AutoFormat. They also developed proofing capabilities, such as spelling and grammar checking, on the personal computer hardware of the time. 

At Wolters Kluwer, Krishna shaped technology and business strategy, and architected the Intelligent Filing Manager. Its declarative design and service-oriented architecture foreshadowed patterns later common in software as a service platforms. At Bloomberg L.P., he led the creation of the Bloomberg Valuation Service, integrating AI-driven predictive analytics with advanced pricing algorithms to deliver transparent, defensible valuations for millions of financial instruments across asset classes. 

Krishna later applied enterprise architecture and Microsoft technologies to modernize operational platforms at Icon Parking Systems (Icon) and Fidelity National Information Services, Inc. (FIS). His recent work centers on cloud strategy and digital transformation, using Azure AI Services to design and deploy interactive voice response systems, intelligent chatbots, and virtual assistants across finance, health care, retail, and legal services. 

Krishna has received awards recognizing his contributions to AI and enterprise systems, including distinguished achievement awards from Microsoft and Wolters Kluwer, as well as the Albert Nelson Marquis Lifetime Achievement Award. His work at Bloomberg and FIS earned multiple commendations. In 2014, he received the Microsoft Most Valuable Professional (MVP) Award in the Microsoft Integration expertise category, recognizing exceptional contributions to technical communities. He is a senior member of the Institute of Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM).