Cloud Migration and AI Readiness

Chapter 4. Accelerating Your AI Journey

Now that you know what cloud migration has to offer, and the key stages of AI progression, you can accelerate your journey to achieve AI readiness at scale.

You already understood it, right? Overall, AI readiness doesn’t rely purely on technology factors; the public cloud makes those technology capabilities more accessible and scalable. The cloud also facilitates the other pillars (e.g., enabling business cases and overall strategy, managing technology and data, building a systematic AI strategy and growing experience, supporting processes and training at the organization and culture level, and making the governance exercise a bit less complex with specific data and AI governance tools).

As the author of this report, and an AI practitioner, here are my top 10 recommendations to accelerate your AI journey and make the most of existing cloud platforms:

1. Recognize that AI is not only about the models

AI adopters in general try to focus mostly on the models, but the reality is that with cloud migration, access to one or multiple models is seamless (a simple connection to an API). If that access to the models becomes a commodity, you can easily use and test them, but don’t forget other pieces such as vector databases, AI search engines to connect and search within databases, LLM frameworks that automate actions in the back (e.g., Semantic Kernel, LangChain, Ollama), safety and security resources, and the end-to-end architecture to guarantee ...