HomeArtificial IntelligenceArtificial Intelligence NewsImportance of sufficient AI infrastructure

Importance of sufficient AI infrastructure

Artificial intelligence brings new levels of automation to everything from automobiles and kiosks to utility grids and financial networks, but it’s easy to forget that a company needs to automate itself first before it can automate the world.

As with most complex systems, IT infrastructure management is ready for intelligent automation. As the data loads become larger and more complex, and the infrastructure itself extends beyond the data center into the cloud and the edge, the speed at which new environments are provisioned, optimized and optimized increases. The decommissioning will soon be beyond the capabilities of an army of human operators, meaning that ground level artificial intelligence will be needed to meet the demands of artificial intelligence initiatives higher up the IT stack.

AI begins with infrastructure

In a classic catch22, however, most companies struggle to implement AI in their infrastructure, mainly because they lack the tools to make meaningful use of the technology. A recent survey by Run: AI shows that few AI models are getting into production, less than 10% in some organizations, and many data scientists still rely on manual access to GPUs and other elements of data infrastructure to get projects to the finish line.

Another study by Global Surveys showed that only 17% of AI and IT professionals report high hardware resource utilization and 28% state that much of their infrastructure is idle for long periods of time. And this is after their organizations have poured millions of dollars into new hardware, software, and cloud resources, in large part to leverage AI.

If the company is to successfully transform traditional ways of operating to fully digitized ways of operating, AI will need to play a leading role. IT consulting firm Aarav Solutions stresses that AI is invaluable when it comes to automating infrastructure support, security, resource provisioning, and a host of other tasks. Its secret sauce is the ability to analyze huge data sets at high speed and with far greater precision than manual processes, giving decision makers a granular view of otherwise hidden forces affecting their operations.
A closer look at all of the interconnected functions that go into the day-to-day management of infrastructure raises the question of how the business has come this far without AI. XenonStack COO and CDS Jagreet Kaur Gill, recently highlighted the myriad of functions that can be launched at hyper speed with AI, from capacity planning and resource utilization to anomaly detection and real-time root cause analysis. With the ability to monitor and manage literally millions of events at once, AI will provide the foundation for the business to maintain the scalability, reliability and vibrancy of the digital economy.

Intelligence to the edge

With that kind of management stack in place, says Sandeep Singh, vice president of storage marketing at HPE, it’s not too early to start talking about AIOps-based frameworks and fully autonomous IT operations, in particular, in entirely new deployments at the edge and in the cloud. After all, this is where a lot of the storage and processing of IoT data will take place. But it also has a widely dispersed physical footprint, with small, interconnected nodes placed as close to user devices as possible. But by its very nature, the edge must therefore be autonomous. Using AIOps, organizations will be able to build real-time, autonomous analysis and decision-making capabilities, while ensuring maximum uptime and failover in the event of a failure at a given endpoint.

For the future, it is clear that an AI-enabled infrastructure will be more than a competitive advantage, but an operational necessity. Given the amount of data generated by an increasingly connected world and the rapidly changing nature of all the digital processes and services that go with it, there is simply no other way to manage these environments without AI.

Intelligence will be the driving force behind business operations for the decade, but like any other technology initiative, it needs to be implemented from scratch, and that process starts with infrastructure.

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