The hybrid multicloud strategy has proven to be a successful model for many companies because it is profitable and allows companies to quickly develop and deploy applications.
Bringing artificial intelligence (AI) and cloud together is a game changer for businesses, with old technology helping to dig up and connect hidden points in zettabytes of data. In recent years, companies have begun to become aware of AI’s capabilities to improve their business, particularly in today’s cloud paradigm, where AI tools can access and manage endless data in multiple areas.
For AI to evolve further and create exponential value for businesses, companies need to decouple AI tools and data from the compartments and silos that were unintentionally created as companies tried to create the cloud solution that best suited them. For this, a multi-cloud infrastructure built with AI at its core is the only answer.
Breaking the silos
When cloud computing radically changed the way companies viewed data storage and the amount of data they could exploit, many companies expected companies to choose between the public and private cloud. However, in practice, this is not what most companies have done, because the “one-cloud-fits-all” approach has been reduced to a mere theoretical exercise. The reality is more complex, which is why the business functions and IT branches of organizations have begun to choose a mix of data centers and private and public clouds from multiple vendors based on the needs of the company.
The hybrid multicloud strategy has proven to be a successful model for many companies because it is profitable, allows companies to quickly develop and deploy applications, but more importantly, to meet the unique requirements of various business needs or applications that are at different stages of maturity and solve security and governance problems. This has also prevented problems such as vendor lockdown. It’s no coincidence that more than 80% of companies already have a multi-cloud strategy.
This becomes even more relevant for the AI entering the image. A single cloud is itself a silo, which is why multi-cloud is the best habitat for AI, as it ensures that AI tools have access to a stock of different data sets given how companies use various clouds for specific purposes. AI thrives in such an environment. Artificial intelligence in a multi-cloud infrastructure also helps developers because they don’t need to create solutions from scratch, but rather take advantage of the basic elements of technology that exist in the respective cloud environments.
As an Ovum study shows, while 20% of business processes have migrated to the cloud, 80% of critical workloads and sensitive data still operate on-site due to performance and regulatory requirements. When applications migrate to the cloud, it’s important to make sure that AI tools aren’t compartmentalized. Businesses and IT departments realized that moving data and applications between different on-site and disparate cloud computing infrastructures was difficult and inefficient, so it was necessary to build bridges between the various software compartments or environments so that data could flow seamlessly and interact to unlock greater value.