How AI Moves Businesses From Damage Control to Near-Instant Recovery After a Data Crisis

When it came to enterprise IT across organizations, there was hardly any other practice set in stone than the nightly backups. For decades, the standard data backup paradigm relied on backups taken every night when a snapshot of all data in the systems was taken and stored onto a disk or tape and kept aside.

While considered effective for its balanced approach to conserving resources and ensuring data security, it always left organizations vulnerable to data loss. For example, a debilitating server crash on Monday evening could compromise thousands of critical records that were stored during your busiest day of the week.

Now with AI at our disposal, the need to bear the risk of a non-recoverable window has been greatly reduced. AI-powered data protection solutions can make data backups a near continuous process through a mix of intelligent prediction and tiering.

Why nightly backups were always an Achilles’ heel for organizations

To be fair, most organizations did not necessarily choose nightly backups because they were foolproof. They likely chose them because they offered a cost-effective solution for backing up data when there was the least volume of workload on their systems. Snapshots were taken at leisure and duly backed up by IT teams initially on tape and later on disks as technology moved ahead. Anything between the last backup and a data loss event was taken as a qualified risk.

However, this strategy started unravelling in the last two decades, with organizations working across time zones becoming the norm. Critical data from overseas operations routinely became the first victims of any data loss event. Add to that, in recent years, ransomware attacks started to exploit the vulnerability and tried to compromise the largest amount of data since the last backup to force companies to pay up.

To complicate matters, the modern economy based on ecommerce, which can notch up thousands of orders in minutes and ever ongoing social and digital content generation, is forcing organizations to rethink their reliance on nightly backups.

Understanding the concept of continuous protection

The idea of enabling continuous data protection (CDP) is fairly old and has been used for many years by organizations for specialized applications like CRM systems. Essentially, it involves preserving every change as it happens in real time rather than in a batch mode, which is the case with nightly backups.

However, except for certain specialized applications in some companies, the concept never gained widespread adoption. The costs associated with organization-wide implementation of CDP were astronomical, to say the least. Storing every change needed massive investment in storage media and compute power, especially at scale, where enterprises typically operated.

But with the advent of AI, the situation has changed dramatically. AI-powered backup solutions can make intelligent decisions and choose what data to capture in real time and ignore I/O actions where nothing really is getting changed. It can keep a discerning eye on the data it’s watching and prioritize the critical data.

In real-world terms, it is now possible to have a continuous backup of your data without burning up a fortune.

Early detection — the ace up AI’s sleeve

Traditional backup systems have always been passive in nature. Nightly backups were taken and kept in the background, only to be called in if a data incident occurs. In contrast, AI-powered backup systems are active in nature. They continuously watch over the production systems, gain a very good idea of what is normal and can quickly notice an anomaly. For example, in the event of a ransomware attack, it can notice files getting suddenly encrypted or mass deletions happening and raise an alert immediately.

The real-world implications of AI in threat detection and backup are immense. Instead of waiting for a ransomware attack to go through, it can immediately isolate the threat vector and keep a clean snapshot before the moment it is affected.

The same scenario can play out in case of logical errors or server crashes, with the AI backing things up until the last moment and shifting production to a different node automatically. With AI in place, the conversation in the organization shifts from how much data we lost to how early we were able to resolve the situation.

Without a shred of doubt, we can safely say that AI will redefine how organizations go about backing up their data in the near future. The gap between production and recovery can now be nearly eliminated. In the event of a data loss scenario, backup systems that are synchronized with production systems can take over immediately without the need to involve a team of experts.

Business leaders need to quickly consider the gains from enabling continuous data protection through AI-powered systems. Not only would their business continuity plans become robust, it can also help them remain compliant with stringent data compliance rules currently in vogue.