![Preventing IT Downtime with AI Applications and Predictive Analysis](http://media.assettype.com/analyticsinsight%2Fimport%2Fwp-content%2Fuploads%2F2020%2F09%2FArtificial-Intelligence-16.jpg?w=480&auto=format%2Ccompress&fit=max)
Technology and digitisation have set the world into a fast running track. People are getting used to the age of Amazon and same-day delivery. The customer's demand and office employee's work, everything depends on the functioning IT system.
As technology grows, companies are switching to IT solutions and more of its functions are turning automatic. But the question here is, 'Can organisations afford to have IT downtime?' A report published in 2018 suggests that on average, IT downtime costs businesses US$1.55 million every year.
Downtime is a period during which a computer system, server or network is shut off or unavailable for use. Systems go through shut down for a variety of reasons including power or hardware failure, system crashes, hacker attacks, system reboots, operating system and software updates, and lack of network connectivity and more.
Technological mishaps can't be prevented as more and more companies, especially in the business sector embrace technology for better solutions. Reports unravel that almost 80% of the companies in the United States are in process of digitisation. A lot of companies are already on the automatic radar with IT systems to handle and execute various aspects of their work. Increasing usage means increasing revenues. The global digital market is estimated at US$261.9 billion in 2018, which is predicted to reach US$1.051 trillion by 2026 with a CAGR of 18.2%.
The COVID-19 pandemic has further fastened the digitisation speed with companies taking massive steps to depend more on IT systems and digital platform. The automation fills the gap of employee's remote working. At the same time, much of the office functioning is also being automated. A report by Deloitte found that at least 58% of organisations across the globe are somehow taking automation into their workforce. The automation being adopted by companies have more than doubled in recent years. It is absolutely a good sign that the business sector is changing its long-forgotten face towards technology. But one thing they should keep in mind is that technology comes with issues and the companies should be ready to tackle them in real-time.
The switch towards development has caused an exponential rise in opportunities for IT failures and downtime. Faults and breakdowns might arise as some sorts of processes are always put into computer systems and the algorithms work non-stop. The worst-case scenario is that employees being unaware of knowing to monitor the increasing automation. North American firms faced an estimated amount of US$700 billion was lost in 2016 due to downtime.
One of the major reasons that things regarding technology get out of hand is because of the wrong mentality. When an organisation is facing downtime issues, the first thing they do is use tools to detect IT problems. This might look fine primarily, but instead of waiting for problems to arise and then solving it, companies should use more technology in its IT house to rather predicting them in the first place.
The recent big IT downtime was acknowledged by the UK parliament's Treasury Committee which released a report in October complaining about the spate of IT bank failures that have been occurring in Britain over the last few years. The committee also mentioned how the issues left millions of customers locked out of their accounts as the institutions concerned struggled to restore their systems. Lloyds Bank faced an IT outrage in 2018 resulting in 1.9 million customers being locked out of their accounts for weeks. But the underlying technical problems took months to be repaired.
To encounter the increasing challenges, organisations that use IT technologies and digital sources should double-fold the use of AI-based predictive analytics which can root out problems before they even arise. Artificial Intelligence (AI) technologies act as a key to achieve downtime predictions. They can also focus on preventing problems from being materialising int eh first place.
AI-based detection platform for pre-diagnosis
Every company doesn't need to have a specialist or an AI application which could monitor its IT systems. There are AI-based detection platforms that function to monitor the companies IT cell and detect issues in real-time. These platforms check for early signs of potential failures. For example, Appnomic, an AI-based detection company has served its clients by handling 250,000 severe IT incidents from happening while saving 850,000 man-hours of work.
The feature provides recommendations like,
• Predicting which fault may occur next
• Providing real-time failure predictions
• Determining the most cost-efficient solutions to a client's current problem
• Providing estimates for part, skills and job duration
• Providing a step-by-step troubleshooting process
Seeking Machine Learning and Data Science for aid
Machine learning and data science are well known for their prediction making technology. By harnessing these AI applications, platforms can process previous data from the datasets to learn how problems arouse and developed previously. This will give an idea of how to block the ways where problems emerged in the past. Gartner coined the term 'artificial intelligence systems for IT operations' (AIOps) to describe this kind of AI-driven predictive analysis.
A report shows that only 5% of large enterprises are using AIOps currently. But it is estimated that the usage will grow by 30% in 2023.
AI application to reduce false alarms
Another major threat to a fast functioning firm is the false alarm on IT downtime or any other issues related to technology. It is quite easy to conclude that there was a technical issue in the system which will cost a loss for the organisation. AI applications can significantly reduce the scenario by gaining a reliable grasp of what actually leads to failures than previous technologies and human operators.
Companies facing IT downtime issues are normal, but the way they choose to harness the threat through early prediction using AI applications like Machine Learning and Data Science can help at critical times. As many more companies are embracing technology, it is good to have a backup system or a solution ready for real-time issues.
Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp
_____________
Disclaimer: Analytics Insight does not provide financial advice or guidance. Also note that the cryptocurrencies mentioned/listed on the website could potentially be scams, i.e. designed to induce you to invest financial resources that may be lost forever and not be recoverable once investments are made. You are responsible for conducting your own research (DYOR) before making any investments. Read more here.