Private Cloud AI infrastructure: Requirements and Strategies for Telecoms Operators and other Enterprises

"Enterprises will increasingly opt for private cloud AI infrastructure, driven by cost, data privacy, and regulatory compliance considerations."

Enterprises, including telecoms operators, are increasingly interested in adopting private cloud AI infrastructure as an alternative to public cloud AI infrastructure. This report explores the drivers behind this trend and the strategies that enterprises can adopt when implementing private cloud AI infrastructure. This includes a discussion about the ways in which enterprises can deploy AI infrastructure on-premises and in co-location facilities and the hardware and software platforms that makes up this infrastructure.

In addition, the report analyses how different categories of ecosystem player can support enterprises with implementing and operating private cloud AI infrastructure, and sets out recommendations for enterprises to expediate the successful adoption of this infrastructure.

Questions answered:

• Why are enterprises finding public cloud AI infrastructure unsuitable for their purposes and what are the benefits of adopting private cloud AI infrastructure?
• What does the private cloud AI infrastructure stack look like?
• What are the different deployment models for private cloud AI infrastructure and how can enterprises approach the implementation of this infrastructure?
• How can the vendor ecosystem support enterprises in implementing private cloud AI infrastructure?