10. Training and Development
According to a survey by digital infrastructure company Equinix, 62% of global IT decision makers see a shortage of IT skilled talent as one of the main threats to their business.
Emerging AI technologies are one of the most widely cited solutions to the current talent crisis, with pioneering talent specialists around the world leveraging AI to help their clients achieve more efficient, supportive and intuitive approaches to both onboarding and talent retention.
“In terms of workforce support, AI can be extremely effective as a tool to support augmented reality training scenarios and provide efficient real-time operational analytics, as well as to attract talent by demonstrating how companies are leveraging new technologies to offer employees more interesting and promising roles,” says Mick Lane, global technology solutions manager at CBRE.
9. Infrastructure Management
In our Top 10 5G Infrastructure Companies, we reviewed the leading 5G infrastructure companies that are committed to providing better connectivity for all. Qualcomm has been working consistently on 5G development for many years. Our 5G Advanced Services will support new devices, services, spectrum, and deployments. We also believe that 5G and AI are complementary and will advance together, mutually benefiting in terms of performance and efficiency.
8. Data processing and storage
AI supports data processing and storage in data centers in a number of ways: AI can continuously monitor and adjust system parameters to optimize processing performance, so that processing tasks are performed efficiently.
Data can be automatically moved between different storage tiers (SSD, HDD, cloud storage, etc.) based on usage patterns, so that the most frequently accessed data is stored on faster, more expensive media and less frequently accessed data is moved to cheaper, slower media. AI can also analyze and identify redundant data and suggest compression or deduplication techniques to save storage space.
7. Smart cooling
AI and high performance computing are driving up power demands in data centers. As a result, data centers need to find ways to cool themselves, leading to the development of smart cooling solutions. To borrow a phrase from Plato, necessity is the mother of invention.
Unlike traditional air and liquid cooling, which rely on predefined settings and manual adjustments, smart cooling uses AI and machine learning to adjust cooling parameters.
Smart cooling optimizes energy usage by predicting conditions and responding in real time, and can automatically adapt to changes in server workloads and environmental conditions, whereas traditional systems are less adaptable.
6. Power Management
AI supports data center power management in a number of ways: AI algorithms allocate computing tasks based on power availability, ensuring that power usage is balanced across the data center. AI can also predict power usage and move non-critical tasks to off-peak hours to avoid excessive energy consumption and reduce costs. Data on energy consumption patterns can be collected and analyzed by AI, providing insights into how power is being used and where efficiencies can be achieved.
It helps compare the energy performance of different parts of a data center to identify areas for improvement and set energy efficiency benchmarks.
5. Predictive maintenance
Predictive maintenance is a more preventative approach to data center operations that uses AI technology to forecast where repairs will be needed. According to Deloitte, predictive maintenance can help companies improve productivity by 25%, reduce breakdowns by 70%, and cut maintenance costs by 25% compared to reactive maintenance.
“AI requires vast amounts of data to learn and evolve, so as data centers grow, so does the data available to AI,” said Flora Cabinato, director of global services product portfolio at Vertiv. “Predictive maintenance is a natural scaler: the greater the density and variety of data, the better the data trends, pattern recognition, insight learning and predictions.”
