A hybrid approach is often the most practical solution. Companies may benefit from specialized private clouds for consistent workloads that demand strong data governance while also using public clouds for experimentation and overflow capacity. By the way, that is more challenging than it sounds.
Ultimately, specialized private clouds, especially those focused on AI, are increasingly indispensable in certain contexts. They are better than the private clouds of the past, which were more like scams than legit solutions. However, organizations must weigh the advantages against the drawbacks, particularly the potential limitations and costs associated with static technology infrastructures.
Here’s some general advice. If you plan on changing a lot during the next five years and your existing requirements are not at all settled, public cloud providers are likely the best solution for things like AI development, deployment, and operations. If you’re unlikely to have a lot of change within the next five years, private cloud options, such as for AI, are genuinely cost-effective, assuming that your requirements lead you there. This is another one of those “it depends” situations.
