Organizations resisting the migration from traditional to more-automated data backup/recovery and DR plans should consider the factors described here
AI is revolutionizing modern backup and disaster recovery (DR) strategies. However, does this mean traditional backup and disaster recovery (DR) methods are no longer important?
Consider this scenario: many organizations follow strict daily backup protocols. Yet, when disaster strikes, they discover their backups are useless because malware had infiltrated their systems long before the threat was detected.
Malware can lie dormant for weeks or even months, infecting backup files unnoticed, only to resurface when compromised data is restored during recovery.
Therefore, regularly backing up data is no longer enough: we need to ensure that all backups are secure, clean, and recoverable. This is where AI can be used to perform real-time malware scans before any data is backed up.
Shifting from reactive to proactive DR
AI is now being used to shift DR plans from reactive to proactive.
Traditionally, organizations would only test their DR plans sporadically, often after a disaster had already occurred. With AI, continuous monitoring becomes a reality, allowing organizations to identify vulnerabilities before they escalate into larger issues.
For example, AI-powered solutions can constantly monitor systems for suspicious activity, flagging and containing risks before they can spread. This real-time capability is crucial as cyberattacks are becoming ever more sophisticated. In the event of an attack, AI can also accelerate response times, significantly reducing downtime and minimizing business disruptions.
AI vs AI
As AI becomes more pervasive in DR solutions, new challenges arise, particularly around ethics and governance.
The race between cybercriminals and defenders is intensifying, as bad actors also adopt AI to bolster their attacks. To stay ahead, businesses should implement ethical guidelines for AI usage in their DR strategies, to ensure transparency, accountability, and minimization of risks, since sensitive customer data is involved.
However, AI is only as effective as the humans managing it. Regular staff training on cyber threats and data protection remains crucial. Employees are integral to the AI learning model: the more they understand about risks and how to mitigate them, the stronger the organization’s security posture becomes.
Embracing AI beyond backups and DR
Some business leaders may still view AI as a complex and expensive tool rather than a useful partner in safeguarding their organization’s data. Others have likened cybersecurity to a game of cat-and-mouse, where cybercriminals constantly evolve, and solution providers and enforcement agencies are perpetually trying to catch up.
However, as the amount of data being collected and processed surges due to digitalization, the need for sophisticated data protection and recovery methods will continue to grow.
Experts predict that by 2050, AI will be fully integrated into most business operations, so, regardless of any organization’s reluctance or ignorance over AI, cybercriminals are already utilizing it to launch more complex and effective attacks.
As a way forward, hesitant organizations should consider deploying AI-enabled defenses while implementing strong Responsible AI/governance frameworks and ethical structures to ensure that the technology AI acts in the every stakeholder’s best interests.
With AI, organizations can not only ensure their data is backed up but that it remains secure and recoverable in the face of evolving cyber threats and disasters. However, adapting AI requires a proactive approach: implementing ethical frameworks, training staff, and embracing AI as the critical business partner it is.
