AI is advancing by leaps and bounds. In data centers, AI workload will constitute 50 per cent of infrastructure by 2025. AI can process voluminous data in real time. It relies on advanced hardware — GPUs and TPUs. These accelerate training and inference processes

Traditional data centers are modified to handle the complexities of AI workloads. It involves adaptations in network architecture, storage systems and data transmission.

The challenge is not the storage of data. It is about how fast data can be processed, analyzed and used.

There should be integration of compute, storage and networking into a single system. It is a hyper-converged infrastructure. Then there is edge computing to allow processing of the data closer to the source.

If the computational power is enhanced, there is a great demand for energy. Then there are issues of cooling — say liquid cooling to dissipate heat generated by powerful hardware.

This is about how AI is driving the demand for data centers. AI also helps in the management of data centers. It optimizes operations. Routine tasks are automated. AI is used for traffic routing and load balancing. It helps in allocating resources. It prevents hardware failure through predictive maintenance.

In future, data centers will evolve further using advances in quantum computing, new cooling technologies and more integration of AI into data center operations.