When it comes to infrastructure management, artificial intelligence (AI) has tremendous potential to lead a revolution that will completely transform and gradually design infrastructure in a way that isn’t just cognitive or self-driven but also equally flawless.
From managing data access to simplifying complex data patterns, AI has the potential to solve integral problems effortlessly. As a result, digital-first enterprises strongly believe that IT infrastructure services could significantly benefit by leveraging the hidden potential of AI.
Soon enough, the disruption caused by AI will be significant enough to be seen as an inevitable part of infrastructure management, primarily due to the growth of companies and data centers with exponential amounts of data.
We have curated a list for you if you’re curious to learn how AI can impact IT infrastructure management.
Demanding Greater Resources
AI’s most significant impact on infrastructure management is increasing the demand for greater resources. AI systems require greater computing power, which is why organizations will turn to cloud computing servers having access to CPUs and GPUs with multiple cores. AI mandates enormous data, directly translating into an increased need for storage and computing capacity. As a result, there will also be a need for networking resources for adequate support.
Offering Intelligent Insights & Reducing Human Resources Dependency
AI infrastructure management solutions have full-stack systems and network monitoring capabilities that can offer real-time intelligence on maintaining consistency in customer experience and satisfaction.
Having complete visibility through all process interdependencies and relations for enterprise infrastructure systems in cloud and on-premises, AI has the power to reduce the complexities of various business processes while cutting down costs where the augmentation of softer human capabilities can be deployed. Not only will it leave human intelligence for more complex tasks, but it will facilitate better decision-making.
Supporting Data Security
Cyber-attacks have become pretty common in recent times. As enterprises have more data to protect than ever, security measures cannot be taken lightly. Fortunately, AI systems can help spot unusual patterns to predict any possible breaches. AI monitors the organization’s devices, networks, and systems closely, and if a problem arises, it is tackled preemptively. Such a predictive firefighting capability helps solve issues quickly, reduce downtime, and save money and resources simultaneously.
One of the reasons why systems crash is the failure to identify problems at an early stage. Several reasons could be behind a system failure, and humans haven’t yet reached the level where they can identify every minute issues that can become a big issue in the near future.
Fortunately, AI algorithms can help recognize and associate data with predicting storage, power, or network failures much more quickly and accurately than humans. It could be beneficial in preventive maintenance for avoiding system crashes, allowing organizations to stay more productive and deliver faster results.
Similarly, when multiple failures occur, AI can take an investigative approach to find the root cause that humans lack by themselves. Unfortunately, humans have limitations in analyzing information, which could end up in a stalemate or increase downtime. Because AI can quickly analyze any amount of information, it has a much better turnaround time.
Understanding the underlying causes of failures is vital information that could aid the efforts of preventive maintenance to ensure they do not occur again.
Establishing Smart Storage Management
AI has the potential to alter the dynamics of storage management completely. Because the technology can learn data lifecycles and IO patterns, it can optimize storage intelligently. AI can even go one step ahead by warning the user of a storage system failure, giving them enough time to conduct data backups and replace hardware within time.
When it comes to all software service providers, IT support is an absolute necessity that cannot be ignored. When software comes with help desk functionality, it can take over some menial human tasks, freeing time for individuals to work on complex issues within the organization.
AI-based support software is an integral IMS tool that helps resolve service issues or requests efficiently. In addition, recommendation systems leave room for continuous improvement, making service desks more customer friendly.
Transforming End-to-End Enterprise Architecture
An AI-defined infrastructure is equipped to plan, build, run, and maintain the infrastructure without human intervention. AI can contribute to all aspects of infrastructure management, from analyzing trends to deploying resources according to the workload to hazard prevention. AI could offer the highest level of automation in IT infrastructure management.
Besides, there is much room to improve the existing systems and technologies. And it can be easily fulfilled by connecting existing technologies or systems with AI systems to transfer learning and optimize knowledge according to business objectives and goals.
Implementing AI-Based Infrastructure
It may sound easy to adopt an AI-based infrastructure, but the reality is no way close to it. Data scientists must choose the suitable machine learning algorithm to curate deep neural networks that deploy the technology to keep it running.
AI systems tend to be error prone because their modus operandi is to learn from past data. New data defying their model logic could easily lead to accuracy failure. Therefore, organizations will have to consider it carefully and combine it with apt technical knowledge before planning to implement AI to upgrade their infrastructure.
Depending on the nature of AI’s interaction with newer transformational technologies, we can expect to witness a shift in infrastructure management’s machine and human capabilities.
In today’s economy, giant corporations are the biggest threat to small and mid-sized enterprises. The only way there is a chance for small players to compete with the big players, AI adoption is integral. Whether we like it or not, AI is here to stay, and organizations have no choice but to adapt to it or risk becoming redundant.