With businesses generating vast amounts of data daily, the challenge of effectively backing up and recovering this information is more difficult than ever. Lengthy downtimes and incomplete recovery are often the result. This is where artificial intelligence (AI) and machine learning (ML) technologies can help. More than a third (37%) of IT teams are incorporating AI into their tasks,1 and it’s increasingly used in backup and recovery solutions.
For instance, AI-powered systems can prioritize critical data, ensuring that the most vital information is backed up and recovered in case of a data loss event. Similarly, ML algorithms can optimize storage space through advanced deduplication and compression techniques, reducing the overall storage footprint.
At the same time, AI poses a threat to data protection efforts. Three-quarters of industry experts said cyberattacks increased in the past year, and 85% said AI was behind the escalation.2 As cybercriminals increasingly leverage AI to launch sophisticated attacks, data breaches and ransomware incidents become even more challenging to prevent and mitigate. Fortunately, AI and ML also offer a powerful defense against such threats.
How AI Improves Backup and Recovery Efforts
Al algorithms excel at processing massive datasets, identifying patterns, and making intelligent, data-driven decisions. They bring a level of automation and precision that is unparalleled by manual processes. Here are some of the areas where AI-powered solutions can help with data protection:
Monitoring Systems and Making Predictions
AI can determine the most likely scenarios to cause data loss. It can help predict hardware failures and the likelihood of a ransomware attack. ML is an application of AI that learns as it is used and can help analyze data, trends, and unusual activity.
Automating Tasks
One of the most useful features of AI is that it can take over manual work that IT and data employees find tedious. For example, AI-powered systems can automatically back up data based on priorities and objectives—like adjusting backup schedules to meet recovery point objectives (RPO).
Assessing Systems
An AI-powered backup and recovery solution can assess the integrity of systems to confirm processes are working correctly and to ensure compliance. AI can compare data sets against regulatory requirements and identify discrepancies. These solutions are also able to conduct continuous testing versus periodic manual tests. This provides better protection against data loss. AI can even simulate specific scenarios to test response effectiveness and reveal potential problems, so you can make sure your systems are working before you need them.
Checking Data Quality
AI can identify and notify teams of data corruption or errors, so you don’t waste time and space backing up bad data. It can also deduplicate data, as well as find and archive dormant data. These efforts not only optimize resources but speed up data recovery. Also, in the case of a ransomware attack, it can detect ransomware in your systems and backup data to protect against reinfection.
Identifying the Best Path Forward
AI tools can classify and prioritize data, make backup recommendations, and optimize storage. These tools can tell the difference between non-essential and business-critical data. AI can also establish the best steps to data recovery, as well as what needs to be recovered immediately versus what can wait. AI remembers past data recovery experiences and improves its recommendations over time.
Recovering More and Better Data
AI can react more quickly than a human can. Tools can recognize the last good backup, meaning it doesn’t contain corrupted or infected data. The use of AI may help improve and speed recovery efforts. When a data system fails, AI can immediately switch to a backup. It can also restore data in order of importance.
Tracking Unusual Activity
Today’s AI can monitor data systems for user behavior that is out of the ordinary. It can also detect other suspicious or unusual activities within your data storage and backups. Algorithms can determine a baseline of user behaviors and then send alerts when there is unusual activity. It can also recognize potential threats like accessing sensitive data, repeated failed login attempts, large data transfers, or attempts to access unauthorized data.
AI can also track unusual activity within backup systems, such as changes in frequency, schedules, or file modifications. You can also program AI-powered solutions to spot signatures or other identifiers of known cyberthreats.
What to Consider when Deploying AI
While AI can offer a host of benefits, it’s important to consider costs, complications, and risks that may be associated with using it in your backup and recovery efforts.
Measuring the Risks
As new AI capabilities emerge, many business leaders have concerns. In fact, 36% of executives and IT managers said AI is one of the top threats to their companies.3 One-third of those said they experienced actual damages from emerging technologies like AI.3 Although the biggest threat is likely to be AI’s use by bad actors, business leaders also worry that misuse of AI by employees puts them at risk for violating data privacy rules. There is also a risk that AI could be a failed investment, as 35% of IT buyers said their AI technologies did not work as expected.1
Creating guidelines for AI use within your company can help curb risk. It’s also important to train employees about its use and their role in protecting data. It’s possible to take advantage of AI capabilities while also minimizing risk. Choosing reputable and communicative AI vendors will help you keep up with the changing technology.
Evaluating Ease of Use
Determine whether an AI solution will easily integrate with your other IT systems. Evaluate how easy it is to implement, use, and optimize. Intuitive dashboards and integrated reporting can help simplify implementation and training.
There is also a learning curve for the technology itself. Algorithms improve as they process more data, so it can take time for machine learning tools to reach their potential. Though poised to take over a lot of data protection tasks, AI tools still require human management and oversight.
Analyze Cost Considerations
AI-powered data protection solutions are being incorporated into many existing solutions and may not have any additional costs associated with it. However, in instances where you are considering either replacing legacy technology or implementing new technology with AI-powered solutions, it helps to perform a comprehensive cost analysis.
Consider the expenses from initial investment to long-term operational expenses, including training, licensing, and ongoing management. Compare those costs with the savings you could see by improving process efficiency through automation and minimizing storage space through intelligent data compression and deduplication. Perhaps most importantly, consider the potential cost savings from reduced downtime and data loss in case of an incident.
AI does help maximize backup storage, so the benefits may outweigh any added costs. Additionally, 31% of organizations saw improved operational efficiency from their AI investments.1 It’s also important to consider the costs of managing the backup technologies yourself versus outsourcing the work to a managed service provider. Although you’re paying for a service, it can improve business efficiency, allow for predictable budgeting, and let IT teams work on projects that improve the business.
Moving Forward with AI
Without an AI-powered solution, you risk drowning in data and falling behind tech-savvy cyberattackers. With the help of the right AI tools, you can manage backups and recovery more efficiently, enhance system security, and maximize data protection. Training employees and performing a cost analysis will help minimize some of the risks and concerns associated with AI.
Connection’s cloud and data center services can help you choose the best backup and recovery solution for your organization. If you want to learn whether AI-powered solutions can help your organization, contact your Connection Account Team for more information.
Sources:
1 IDC Research, 2022, Insights on the State of AI
2 Deep Instinct, 2023, Generative AI Is Increasing Cyber Attacks
3 Veritas, 2023, New Veritas Research Reveals Nearly Half of Organizations Underestimate Their Level of Risk
Becky Lawlor
Becky Lawlor has been covering the convergence of business and technology for over a decade. Her writing focuses on emerging trends in big data, IoT, AI, mobility, cyber security, cloud computing, and more. She especially enjoys examining how these technologies are impacting critical business and public sectors such as healthcare, education, government, and retail. You can find more of her writing and insights on Twitter @lawlor_becky.
