Architecting AI in the Real Enterprise

If you are reading this, chances are you have spent the better part of your career doing something that most people outside of technology do not fully appreciate: you have been designing the...

Why most AI initiatives fail — and the three-pillar framework that changes the outcome.

If you’ve been working in enterprise architecture for any meaningful stretch of time, you’ve lived through several tectonic shifts. You were there when mainframes gave way to client-server models,...

If you’ve been in enterprise architecture for any length of time, you’ve lived through waves of technology hype before. You saw it with cloud computing, with microservices, with blockchain, and now...

Over the course of your career as an enterprise architect, you have built up a mental library of components that you instinctively reach for when designing systems. Databases, message queues, API...

If you’ve been working in enterprise architecture for any length of time, you already have a data architecture. You have data warehouses humming along, data lakes that may or may not be...

Let’s start with a reality check. Your enterprise already has hundreds of systems in production — ERPs, CRMs, data warehouses, customer portals, internal tools, and probably a few legacy monoliths...

If you’ve spent any time in enterprise software, you already know the value of CI/CD. You wouldn’t dream of pushing code to production without automated builds, tests, and deployment pipelines. So...

Let me be direct about something that too many organizations get wrong: responsible AI is not a compliance checkbox, and it is not a slide deck you dust off when the board asks uncomfortable...

Every enterprise architect eventually faces a question that carries more weight than it might first appear: which cloud platform should we build our AI strategy on? It is a decision that affects...

Nobody gets to build an AI-native enterprise from a blank slate. You have legacy systems that were architected years ago under entirely different assumptions. You have technical debt that accumulated...

When you first sit down to build something with a large language model, the sheer number of possible architectures can feel overwhelming. Should you just call an API? Do you need a vector database?...

If you spent the last decade designing microservices, wrestling with API gateways, and untangling event-driven architectures, you already have the instincts you need for what comes next. Chapter 3...

A fintech company launched a GenAI-powered feature, and it was an instant hit. Users loved the experience, adoption curves looked beautiful, and the product team was celebrating. Then the first...

You can design the perfect AI architecture. You can pick the right models, build an elegant RAG pipeline, set up a gateway that routes requests with sub-second latency, and implement monitoring that...

There is no substitute for learning from other people’s mistakes — or their hard-won successes. The case studies in this chapter are composites, drawn from real enterprise AI transformations I have...

We have spent fourteen chapters talking about technology, architecture patterns, governance frameworks, and organizational design. All of that was about transforming your enterprise. This final...

This appendix presents ten reference architectures for common enterprise AI use cases. Each diagram shows the key components, data flows, and integration points that an AI Enterprise Architect needs...