When we talk about the possibilities that Artificial Intelligence currently offers companies, we rarely mention the role that these developments are playing in one of the most critical areas for any organization: the management and optimization of the ICT infrastructure, with the aim of improve system availability, reduce downtime and increase operational efficiency.
Traditionally, companies concerned about the stability of their critical systems have implemented redundancy and high availability plans, as well as disaster recovery strategies, proactive infrastructure monitoring systems, load balancing and preventive maintenance actions.
Although all these actions continue to be necessary and recommended, AI is beginning to play a relevant role in this area. Probably, the first benefits of this integration have been seen in the monitoring and predictive analysis of the technological stack. For years, companies of all sizes have used AI solutions that, by analyzing large volumes of data generated by sensors and connected devices, identify patterns that could lead to future problems. Tools like Splunk, Datadog o IBM Watson AIOpswhich enter fully into the field of IT observabilityare some of the best known.
In addition to preventing and anticipating potential problems, AI is increasingly being used to manage these problems or failures once they occur, automating the response. In some data centers, for example, AI is used to balance workloads dynamically, so that resources are reconfigured in the event of failure, thus minimizing downtime.
In this same sense, platforms such as Swimlane, Palo Alto Networks o ServiceNow They implement AI to automate the management and resolution of security and operational incidents, applying automatic corrections such as restarting servers or activating backup resources. Similarly, companies like right o Veeam They allow you to automatically orchestrate data replication and the activation of backup sites when the primary node of the IT infrastructure fails.
On the other hand, there are specific sectors that especially benefit from this type of development. For example, companies that manage large telecommunications networks or distributed IT infrastructures, such as Internet service providers or large corporations, use intelligent algorithms to dynamically optimize network traffic paths. This improves your resilience and reduces the risk of disruptions. In large data centers, especially hyperscalar ones, AI has already become an essential ally to improve energy efficiency, monitoring and adjusting energy use in real time to keep systems running without interruptions. In the industrial field, companies use AI in the context of Industry 4.0 to reduce downtime in production plants. IoT sensors combined with AI make it possible to detect problems in machines before failures occur and trigger automatic responses or predictive maintenance.
Finally, we cannot forget the growing role that AI is playing in the world of technology. cybersecurity. Virtually all major manufacturers include algorithms machine learning in their solutions, which allow them to identify suspicious activities on business networks and respond automatically, thereby reducing the risk of disruptions caused by cyberattacks.
In short, AI is not only the future, but in many cases it is already an important part of the management of the technological infrastructure of any company. In a “silent” way and without the need to write any promptrelieves the workload of numerous systems technicians, eliminating routine tasks and allowing them to focus on higher value projects.