Industry executives and experts share their predictions for 2019.  Read them in this 11th annual VMblog.com series exclusive.

Contributed by Oussama El-Hilali, VP of products at Arcserve

Wish You had a Magic Ball to Predict IT Disasters? Signs Point to AI

When unexpected disasters strike, it can cause some serious issues for the IT team and end up costing a pretty penny. Gartner estimates that downtime can cost an organization upwards of $5,600 per minute and an average of $300,000 per hour. That can really put a dent in a company's budget, so it's critical to get up and running as soon as possible. It can also impact long-term customer loyalty. Companies must be able to deliver what their digital customers want, exactly when they want it. If they're unable to achieve the instant access that today's consumers are looking for, they may seek similar services elsewhere. Therefore, it's no surprise that data is becoming organizations' most important asset, as it's key to a company's success. 

A recent global survey of IT decision-makers conducted by Arcserve really drives home these points, as nearly half of the respondents reported that they have less than an hour to recover from an outage before it starts impacting their bottom line. While there are certainly business continuity and disaster recovery (BCDR) technologies that help mitigate the impact of IT interruptions, there will be new disaster recovery solutions that will tap artificial intelligence (AI) and predictive analytics to avert disasters entirely. 

Tap Your Psychic Powers With AI

Today, AI and predictive analytics are largely used to imitate simple human behavior, like predicting the next word in a sentence a human may type in a word processor . But, soon, this technology will be built into solutions to take on much more advanced functions that will help modernize the IT function from cost center to business enabler. For instance, these AI algorithms can be used to identify when a system might fail before it even happens, when malicious hackers or ransomware actors might attack an organization, and even when a serious natural disaster - like an earthquake - will occur.

How can this be done? To provide these forecasts, algorithms pull data from both internal and external sources. Companies can collect data on the impact of viruses and other forms of malware or external data on severe weather, which can allow them to predict (with a certain level accuracy) these operations-halting events before they occur. With this insight, organizations can make sure their backups are automatically updated and systems are patched to protect themselves from cybercriminals. In the case of extreme weather, they can automatically replicate their data, workloads and applications to the cloud to prevent data loss from damaged hardware. Having advance notice of these potential catastrophes can save a company hundreds of thousands of dollars in financial damages and can also alleviate the IT team of unnecessary stress during already challenging times. 

Predict the Future of Your Storage Needs and Disaster Recovery Strategies

Not only will AI and predictive analytics be able to forecast events before they happen, the technology will also be able to unveil patterns of behavior within a company, allowing IT decision-makers to make more informed decisions about their storage needs and future disaster recovery strategies. Predictive analytics could be used to predict how fast data volumes will grow based on an organization's current consumption, which means IT can more accurately allocate their budget for future storage investments.

These algorithms can also potentially keep tabs on how often employees are accessing data, which can help IT teams better determine which information is mission-critical versus business-critical. Having insight into this information can be extremely beneficial when putting together or updating a BCDR plan, as the IT team will be able to collaborate more effectively with the lines-of-business teams to prioritize which systems and applications need to be recovered first. It also eliminates the possibility of human biases playing a role in these critical business decisions.

Beyond helping companies better inform their BCDR planning and storage needs, organizations will also be able to use AI to more intelligently test different disaster recovery scenarios. Testing is often an overlooked part of the planning process, as it can be incredibly challenging and time consuming for IT teams. However, it's a critical part of the process. Without testing the plan, how can you know it really works? How can you be sure it will protect data against inclement weather or emerging cyberattacks? You can't. So, AI will play an important role in making sure companies are investigating and testing every possible situation so they can swiftly dodge close calls. 

How Far Out Are We From Getting Our Hands on These Tools?

The magic ball is coming through a little fuzzy on this one, but we should anticipate that these solutions will be introduced into the market within the next couple of years, as there's already a growing interest in these solutions. Arcserve's recent survey also uncovered that 74 percent of IT decision-makers are aware of the potential for "intelligent" recovery solutions. Further, 87 percent of IT decision-makers (and the C-Suite, especially) are very or somewhat likely to consider employing backup and recovery solutions that incorporate AI-powered solutions.

However, despite a clear interest in these tools, there's also a little caution around them, as the survey  uncovered that trust in these solutions is soft at this point (with only one in three IT decision-makers having ‘a great deal' of faith in them). IT teams want to make sure they can rely on these tools before they deploy them, so vendors will take the necessary time needed to make sure new tools being introduced to the market are solving the challenges actually facing IT teams.

There's certainly a lot of potential for this technology to disrupt the data protection industry, and when it does become available, it will certainly save a lot of organizations from sticky situations and data loss. While the next year will present a lot of changes across the whole industry, predicting and averting outages altogether will become the new goal for many businesses who simply won't be able to afford downtime as customers' tolerance for outages diminishes.

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About the Author

Oussama El-Hilali, VP of products at Arcserve

Oussama joined Arcserve as Vice President of Products in January 2016, assuming a key role in managing the development and product management teams at Arcserve.

He has nearly 25 years of IT and R&D experience driving and achieving product strategy and roadmaps, acquisition of new technology, and developing strategic business partnerships in both Fortune 100 and emerging companies.

Previously, he held senior executive positions at EMC, Carbonite and Symantec where he led global engineering organizations and accelerated growth through harnessing innovative ideas, technology, and organic and inorganic product portfolio enhancements. In addition, Oussama has extensively consulted with software companies to help them develop and acquire the right technologies.