Business leaders highlight the need for a hybrid cloud approach to unlock the power of generative AI

In 2023, organizations have confronted an unprecedented degree of stress to digitally rework with the rise of generative AI in addition to imperatives equivalent to sustainability, labor productiveness and safety. The “Cloud Transformation Report,” a brand new international survey from the IBM Institute for Enterprise Worth (IBV), discovered that many main enterprises share a standard basis to digital transformation—a transparent hybrid cloud technique.¹ These companies cite a number of key advantages to utilizing a hybrid cloud strategy to gasoline enterprise transformation, together with modernization, agility, safety, sustainability and the power unlock the facility of generative AI.

Right here’s a take a look at the important thing drivers that impacted cloud transformation over the previous 12 months and what they imply for firms on their cloud modernization journey:

Issues for adopting generative AI

This 12 months, generative AI captured the eye of enterprise leaders—however it additionally raised questions together with what’s the correct basis to speed up and scale impression? For a lot of organizations, the reply is a hybrid cloud strategy. The brand new examine discovered that 68% of hybrid cloud adopters have already established formal, organization-wide insurance policies to direct their strategy to generative AI.

With the rise of generative AI comes an inflow of knowledge. Whereas this may gasoline large enterprise improvements, it additionally requires strategic concerns. When executing an AI technique, enterprises want to think about their present compute capability, the place information resides—within the cloud, on premises, on the edge—how information is accessed, needed safety controls, and the way to use current know-how investments successfully. Along with serving to ship enhanced reliability and efficiency, a hybrid cloud strategy can allow elevated agility with the power to attach cloud and on-premises environments, eradicating obstacles to versatile AI workflows.

Addressing safety and compliance considerations

With regards to generative AI, enterprises are additionally involved in regards to the potential publicity of delicate information. For instance, 45% of cloud leaders cited considerations about cybersecurity or privateness and confidentiality of knowledge and data as the important thing impediment of their push to implement generative AI. The findings point out that extremely regulated industries are more and more weighing dangers, equivalent to safety, when contemplating the know-how. These organizations are much less more likely to have a proper strategy to AI than another industries, however they’re displaying progress: 57% of banks and monetary markets organizations, 54% of insurers and 54% of life sciences/pharma establishments have adopted a proper strategy to the know-how up to now.

For extremely regulated industries which might be tasked with safeguarding vital information, there’s so much on the road. To keep away from blind spots, a holistic safety technique that gives visibility throughout a complete hybrid cloud infrastructure is significant to mitigate threat. 

Overcoming abilities challenges

The report additionally reveals persistent obstacles to extra widespread cloud adoption — maybe none as nice as the continuing abilities hole. For instance, 58% of worldwide determination makers say that cloud abilities stay a substantial problem and 72% of organizations have created new positions to satisfy the necessity for cloud abilities. Inside particular person industries, this deficiency is even better: 79% in extremely regulated industries equivalent to banking and monetary markets, in addition to 81% in transportation and journey, and 79% in chemical substances and petroleum.

Placing sustainability initiatives within the highlight

Not too long ago, sustainability has been tied to broader enterprise objectives and grow to be a bigger precedence for know-how investments for organizations throughout industries. But as generative AI grows, the rise in information processing required for AI workloads does too. This may current new challenges for organizations that need to scale back their greenhouse fuel (GHG) emissions.