Last updated on June 28, 2019
In the realm of infrastructure management, artificial intelligence (AI) has the potential to bring about a transformation and eventually design infrastructure that is not only self-driven or cognitive but also flawless. What began in the form of research on chess-playing computers in the 1950s, is now solving problems spanning from data access management, pipelining of products, model development and simplifying complex data patterns.
Digital-first enterprises believe that their infrastructure services have tremendous scope to tap the incredible potential of AI. Eventually, AI will be inevitable to the function of infrastructure management, owing to the scale and growth of organisations and huge data centres with exponentially increasing data. Let’s understand how AI will specifically impact infrastructure management and bring in significant business benefits.
Cyber-attacks have been rampant in recent times. From WannaCry to the notorious Cambridge Analytica scandal, more than 4.5B records were compromised by unauthorized parties. The amount of data curated by software security is massive and it is out of human bounds as yet to manage & point out chinks in the data armour. AI systems can spot unusual patterns quickly to predict possible breaches by studying the organisation’s systems, devices and networks. The problems can then be tackled pre-emptively. This predictive firefighting capability ensures prompt resolution of issues, reducing downtime and saving resources as well as money
AI solutions come with full-stack monitoring capabilities of networks and systems to provide real-time intelligence into how you can maintain consistency in customer satisfaction. With complete visibility into all process relations & interdependencies for enterprise infrastructure systems both on premise and in cloud , AI reduces complexities of business processes and cuts down costs which augment softer human capabilities, thereby ensuring better decision making
AI is believed to revolutionise storage management. The technology is capable of learning IO patterns and data lifecycles, thereby optimising storage intelligently. One could go so far as to say that AI could pre-emptively warn the user about a storage system failure, thus giving the users enough time to back-up important data and replace hardware well within time
For any software service, round the clock IT support is a necessary function. Add to it software with helpdesk functionality to take sover menial human tasks, you free up individuals to focus better on their core KRAs within their organisations. AI based support software is a key tool for IMS and play an important role in resolving the service requests and issues effectively. Recommendation systems along with continuous improvement through feedback make service desks customer-friendly.
It is believed that at some stage, AI will be able to actively manage and maintain the entire system by studying demand trends, predict requirements and deploying resources as and when required. This is what one could call ‘the highest level of automation in infrastructure management’.
Transformation of end-to-end enterprise architecture
AI defined infrastructure sans human intervention is capable of planning, building, running and maintaining the infrastructure. Everything from and in between analysing trends to predicting infrastructure requirements to deploying resources as per workload to prevention & firefighting is something AI can do for infrastructure management! However, there is much scope of improvement within the existing technologies and systems. This scope can be fulfilled by exercising best practices, connecting existing systems with other AI systems by transferring learning and optimising knowledge as per business goals & priorities.
Implementing AI based infrastructure
As easy as it sounds, implementation of AI based infrastructure is no easy feat! Data scientists need to choose the appropriate machine learning algorithm or design deep neural networks to deploy the technology and keep it running. AI systems are error prone since they operate on learnings from past data. Any new data that defies their model logic may cause accuracy failure, which is why due consideration and apt technical knowledge is a prerequisite to implementing any advanced infrastructure.
The next step
Depending on its interaction with other transformational technologies, AI is pushing the frontier of the capabilities of humans and machines in infrastructure management. The next big thing in automation is opined to be robotics guided by AI with the hands and feet capability for operations. However, in order to get a bang for their buck with AI, businesses need to address the entirety of service management strategy and not just from an operations perspective.
The reality is that AI is here to stay and evolve and organisations need to adopt to adapt or they run a risk of being rendered redundant!
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