Cloud Migration and AI Readiness

Chapter 1. Introduction to the Era of AI

The wave of AI adoption has taken the technology ecosystem by storm. Companies around the world are looking for the key to AI success, while still dealing with ongoing digital transformation, cloud adoption, data governance, change management, and other transformational initiatives within their organization. Regardless of the company’s size (large companies or growing startups), there is increasing pressure to adopt AI to remain competitive, keep up with new technology trends, satisfy investors’ appetites, etc.

Meanwhile, technology companies work to create the best possible platforms that incorporate the widest range of AI models and connect them with the companies’ data platforms and productivity suites. All this while adding the layers for choosing and switching AI models, creating built-in AI safety mechanisms, evolving from machine learning operations (MLOps) to large language model operations (LLMOps) like GPT-4, and leveraging internal knowledge bases while preserving privacy and information control access.

But technology transitions are not simple, and the arrival of generative AI as a new subset of AI technologies and tools is a great example of that. Traditional AI technologies, such as machine learning or deep learning, are complex enough for many companies. Adding generative AI and LLMs to the equation adds a new layer of complexity and a sense of urgency to pursue what the industry defines as AI readiness. For that purpose, ...