Rapid technology changes are influencing every aspect of the business; IT infrastructure of a firm is no different. Technologies like Big data, IoT, Mobile, while enabling firms with various business capabilities and creating tremendous value also are over straining the firm’s IT Infrastructure. Today’s IT infrastructure appears to have reached an inflection point and the existing infrastructure capabilities are not designed to keep up with today’s business needs.
In a survey done by Forrester, nearly 86% of respondents say that their organizations IT infrastructure is not up for the task.
This is where Artificial intelligence platforms can help solve the problem. Artificial Intelligence (AI) platforms for Infrastructure Management upon which organizations can build intelligent applications that are predictive, self-healing and that requires minimal human intervention.
IDC estimates global spending on cognitive systems will reach $31.3B by 2019 and more than 40% of all cognitive system spend will go to software which includes cognitive applications and Cognitive software platforms. These platforms are increasingly finding adoption in IT services firms to solve problems in the context of their business model and drive differentiation in their core markets.
Upon analyzing use cases, it becomes clear that majority of examples on application of AI platforms is in Infrastructure management services area. It is also worth noting that running and maintaining infrastructure for applications is currently the least automated part of IT capabilities. This presents an interesting opportunity with great potential.
Here are the basic features of an Intelligent IT infrastructure:
Predictive – Predictive analytics in IT Infrastructure enables it to anticipate the needs beforehand and help provision for contingencies. For example, spike in the firm’s website activity, and subsequent load on the server due to holiday season shopping
Self-Healing – Without manual intervention an Intelligent Infrastructure automatically configures itself after predicting the problem. For example, in case of the failure of the server due to increased workload, Intelligent infrastructure will find another server of same capability and shifts the workload without interruption of business processes
Self-Optimizing – Intelligent infrastructure continuously analyzes and monitors the performance of various applications and service quality. It proactively alerts the team of options of moving applications to other provider that provides a better price point at a given service level
Self-Protect – Intelligent infrastructure continuously analyzes and alerts of security threats
Given that today’s IT Infrastructure is strained by new age technologies like IoT, Mobility, Big Data, the need for Intelligent Infrastructure is evident more than ever and presents itself an ideal candidate for harnessing the power of AI platforms.