What you'll learn

Organizations exploring generative AI need a clear view of whether their infrastructure, integrations, and operating model can support adoption. In today's Gen AI landscape, many enterprises start with managed models and API-based solutions, but they still must evaluate internal readiness before moving forward. In this course, Assessing Infrastructure Readiness for Gen AI, you'll learn how to evaluate enterprise infrastructure capabilities for Gen AI adoption. First, you'll examine how to audit compute, storage, and networking resources and how to work with technical experts to identify bottlenecks and system constraints. Next, you'll explore how to plan for scalability and integration by assessing cloud versus on-premises tradeoffs, reviewing API and orchestration needs, and checking compatibility with current enterprise applications and systems. Finally, you'll learn how to establish infrastructure practices that support deployment, including MLOps and continuous deployment practices, model versioning, updates, and workload scaling. When you're finished with this course, you'll be able to assess infrastructure readiness and recommend practical next steps for successful generative AI adoption.