As businesses rush to become more data driven and leverage AI to better serve customers and be more competitive, enterprises are quickly learning that the way to AI readiness leads straight to the cloud. Here’s an interesting article on the state of AI-readiness, sometimes called digital transformation.
But how do companies step up their infrastructure to become “AI ready”? Are they deploying data science platforms and data infrastructure projects on premises or taking advantage of a hybrid, multi-cloud approach to their infrastructure? As more and more companies embrace the “write once, run anywhere” approach to data infrastructure, we can expect more enterprise developments in a combination of on-prem and cloud environments or even a combination of different cloud services for the same application. In a recent O’Reilly Media survey, more than 85% of respondents stated that they plan on using one (or multiple) of the seven major public cloud providers for their data infrastructure projects,
Enterprises across geographies expressed interest in shifting to a cloud data infrastructure as a means to leveraging AI and Machine Learning with more than 80% of respondents across North America, EMEA and Asia replying that this is their desired choice. A testament to the growing trend towards a hybrid, multi-cloud application development is the finding in the same survey that 1 out of 10 respondents uses all three major cloud providers for some part of their data infrastructure (Google Cloud Platform, AWS and Microsoft Azure).