AI in DR: Acronyms are here to save the day. 


Artificial intelligence (AI) has the versatility required to transform disaster recovery (DR) and relief. According to NextGov, generative AI can potentially reduce the impact of billion-dollar disasters as it can streamline information sharing, access and recovery alongside boosting decision-making and enhancing early warning systems. On both the natural and business disaster scale, these capabilities can fundamentally change the impact of a disaster on human life, infrastructure and critical business functions. Texas A&M University echoes this sentiment, pointing out that there are projects underway designed to improve disaster resilience through the development of different types of AI models capable of providing insights and foresights that can change response, recovery and preparedness. 

One of the most important contributions the technology can make is in its ability to predict a potential disaster. This can be any kind of situation from an extreme weather event to ransomware attacks to the imminent collapse of a datacentre. The applications for predictive AI models within DR are quite broad, and by definition should remain that way. AI can introduce automated responses that don’t rely on the human element to alert the relevant people in the event of a disaster – it can react instantly to specific variables and notify the right people at a speed that can noticeably reduce the impact of the event.  

When shifting the gaze towards the business and disaster recovery on, when compared to global events, the micro-level, AI can automatically implement fail-over so systems adapt to the situation and continue operating, thereby reducing the amount of downtime and the financial impact on the organisation. In the retail sector, for example, AI can be used to ensure that resources and systems are aligned when there are major events such as Black Friday to ensure that everything operates effectively and that there is enough capacity. It can be used to prevent system crashes and detect vulnerabilities or threats that often affect the sector during the high season.  

The automation benefits introduced by AI don’t stop at DR, however.  

AI automation will optimise and improve operations while providing decision-makers with insights that allow for predictive maintenance and management. When the right people can predict failure before it happens, it changes the entire dynamic. When management teams, facilities managers, C-suite executives and other essential decision-makers have granular visibility into their infrastructure and its performance, they can predict when to update storage, tighten security, undertake maintenance and so much more. And every step towards a more agile, predictive maintenance approach is one step further away from an unexpected disaster. 

AI can consistently improve decision-making going forward as it continuously interrogates the data and provides reliable insights at speed that help people to make faster and more relevant choices. These choices extend beyond predictive maintenance and into the realms of resource allocation, medical supplies, remote and rural area access to critical materials, and rapid response to unexpected emergencies. AI can even be used to manage telehealth solutions designed to mitigate the impact of a natural disaster, an outbreak and other disasters that usually isolate those affected.  

Artificial intelligence is so much more than a transcription service or an app that writes average content. It can be part of a comprehensive disaster recovery plan designed to leverage the speed, agility, intelligence and data analytic capabilities of AI to transform how disasters are managed, approached and resolved. By taking on the burden of analysis and providing alerts at a speed unheard of before, AI is the catalyst that can change the narrative from disaster recovery to disaster prevention.  

Ellouise Langeveld, senior specialist: Solutions at Altron Karabina.