Get your AI balance right on future public cloud, on-premise, and hybrid deployments

As AI adoption accelerates across industries, organizations are reevaluating their infrastructure strategies, weighing the benefits of public cloud, on-premise, and hybrid deployments. In a recent interview with iTNews Asia, Anand Chakravarthy, Vice President of Advanced Solutions at Tech Data APJ, highlighted how enterprises are increasingly embracing hybrid models to balance scalability, security, and cost-efficiency in their AI initiatives. 

Public cloud remains popular for AI workloads due to its scalability and low upfront capital expenditure. Companies can access storage, GPUs, and server capacity on-demand, allowing them to respond dynamically to evolving business needs. However, this model becomes costly over the long term and poses challenges for industries dealing with sensitive data or requiring low-latency performance. 

In contrast, on-premise AI deployments offer enhanced security, regulatory compliance, and real-time processing capabilities. Sectors such as banking, healthcare, and insurance are prioritizing on-premise infrastructure to maintain data sovereignty and comply with local data protection laws. Customization and control are also key drivers behind this approach, with on-premise environments better suited for complex, mission-critical AI applications. 

Anand advocates for hybrid infrastructure as the most strategic model going forward. Hybrid AI solutions allow businesses to harness the elasticity of public cloud for non-sensitive workloads, while maintaining control over critical operations in secure data centers. This is especially beneficial for multinational organizations navigating varying regulatory environments across APAC. 

While hybrid offers a best-of-both-worlds approach, it also introduces complexities, particularly around data synchronization and system integration. To mitigate these challenges, enterprises are turning to experienced technology partners to ensure seamless orchestration between platforms. 

Looking ahead, Anand predicts increased cloud migration over the next 3–5 years, but emphasizes that hybrid infrastructure will remain essential for enterprises scaling sophisticated AI deployments. Aligning infrastructure with business needs will be critical in driving long-term AI success. 

Source: 

https://www.itnews.asia/news/get-your-ai-balance-right-on-future-public-cloud-on-premise-and-hybrid-deployments-615639