How AI and predictive analytics get rid of expensive IT downtime

By Cuneyt Buyukbezci

Image credit score: Depositphotos

Increasing automation and digitization is inevitable. More corporations are transferring their operations to IT techniques, and extra of those operations are being automated.

However, what isn’t inevitable is the rise in IT failures and intervals of downtime that digitization and automation entail. Businesses are dropping billions of {dollars} per 12 months from IT downtime.

Fortunately, the growing use of AI-based predictive analytics can root out issues earlier than they even come up.

First, let’s simply get a agency deal with on the dimensions of the issue, and simply how a lot of the economic system is being digitized and automatic. Almost 80 percent of companies in the United States are within the strategy of digital transformation, that means that 80 p.c of American companies are turning more and more to IT techniques to deal with and execute varied features of their work. And they’re pumping a number of cash into this strategy of change: According to a recent study from Reports and Data, the worldwide digital transformation market was valued at $261.9 billion in 2018, whereas it’s estimated to succeed in $1.051 trillion by 2026.

In different phrases, large shifts are going down around the globe as companies come to rely extra on IT techniques and digital platforms. At the identical time, a lot of the functioning of those techniques and platforms is being automated. A report from Deloitte published this year discovered that 58 p.c of organizations globally have launched some type of automation into their work processes, whereas the variety of corporations implementing automation at scale has doubled during the last 12 months. This is one other monumental change, indicating that as corporations transfer to IT techniques, they’re additionally transferring in direction of automating a lot of what these techniques do.

This is all very thrilling, however sadly, this shift has precipitated an exponential rise in alternatives for IT failures and downtime. As extra processes are placed on some sort of pc system, and as extra of those processes are executed by algorithms, then inevitably extra possibilities for faults and breakdowns come up, notably as employees are ill-equipped to watch every part an more and more automated system does. Indeed, estimates of the prices of downtime in misplaced income went from $26.5 billion globally in 2011 to $700 billion in 2016 (and just for North American corporations).

Things are getting out of hand, and one of many essential explanation why many corporations haven’t been in a position to clear up this problem is as a result of they’ve approached it with the improper mentality. Generally, they’ve been growing and utilizing instruments to detect IT issues as and once they seem. This may sound effective at first look, however ready for issues to come up may be harmful, since they’ll typically take a very long time to resolve.

For occasion, the UK Parliament’s Treasury Committee released a report in October complaining in regards to the spate of IT financial institution failures that had been occurring in Britain over the previous couple of years, and about how these had left tens of millions of shoppers locked out of their accounts because the establishments involved struggled to revive their techniques. One of the worst examples of this occurred in 2018 when an IT outage affecting Lloyds Bank resulted in 1.9 million prospects being locked out of their accounts for weeks, with the underlying issues taking a number of months to utterly resolve.

To keep away from such disasters, companies ought to actually take a proactive method to their IT techniques. Specifically, they should concentrate on stopping issues from materializing within the first place, in order that they aren’t left with intervals of downtime that find yourself hurting their backside strains. Artificial intelligence is the important thing to reaching this.

AI-based detection platforms are able to monitoring IT techniques in real-time, checking for early indicators of potential failures. To take one instance, my firm Appnomic has managed to deal with 250,000 extreme IT incidents for our shoppers with AI, which equals greater than 850,000 man-hours of labor.

By harnessing machine learning, such platforms can use previous information to find out how issues usually develop, enabling an organization to step in earlier than something unlucky happens. In 2017, Gartner coined the time period “artificial intelligence systems for IT operations” (AIOps) to explain this type of AI-driven predictive evaluation, and the market analysis agency believes that using AIOps will develop significantly over the following few years. In 2018, only 5 percent of large enterprises are using AIOps, however the agency estimates that by 2023 this determine is about to rise to 30 p.c.

This progress will likely be pushed by the truth that a number of advantages come from the applying of machine studying and information science to IT techniques. Aside from detecting possible issues earlier than they happen, AI can considerably scale back false alarms, in that it may well achieve a extra dependable grasp of what really results in failures than earlier applied sciences and human operators. On prime of this, it may well detect anomalies that received’t essentially result in failures or downtime, however which may be making an IT system much less environment friendly.

This is why AI analytics will make IT techniques extra resilient and sturdy total. And as extra corporations migrate to AIOps and associated platforms they may create a snowball impact, forcing their rivals to both be a part of the race to keep away from pointless downtime or be left behind. And it makes excellent sense that, as automation in IT techniques will increase, there needs to be a parallel improve in automated predictive analytic techniques. Because as software program eats the world and we people turn out to be much less central to our personal jobs, it’s solely AI that may sustain with AI.

About the creator

Cuneyt BuyukbezciCuneyt Buyukbezci is the Chief Marketing Officer of Appnomic. Cuneyt has a historical past of working at massive enterprises operating advertising and marketing, product technique, and gross sales management at HP Software, Sun Microsystems, and CA Technologies. He’s at present serving to enterprises find out how they’ll undertake a preemptive method to IT administration, as a substitute of firefighting after techniques fail.


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