AI in disaster response: protection or peril for your business?

The very technology that promises to revolutionise business operations is simultaneously creating entirely new categories of disaster scenarios. Australian organisations are now facing a complex reality: AI is both the accelerant behind increasingly sophisticated cyber threats and the most powerful tool available for disaster response and recovery.

Recent data from the Australian Cyber Security Centre reveals that cybercrime reports reached over 87,400 in FY24, with a report logged every six minutes. Meanwhile, Australian businesses lost over $8 million to AI-powered scam operations in 2023, with deepfake technology making these attacks increasingly convincing and difficult to detect.

The question is: can AI in disaster response help your organisation stay one step ahead, leveraging its defensive power faster than malicious actors exploit its offensive potential?

The AI threat landscape: when intelligence turns hostile

The sophistication of AI-driven attacks has fundamentally changed the disaster response equation. Unlike traditional cyber threats that follow predictable patterns, AI-powered attacks adapt, learn and evolve in real-time.

Deepfake extortion: the new face of fraud

Australian authorities are witnessing an alarming rise in deepfake-enabled scams. The Australian Competition and Consumer Commission (ACCC) reported that scammers are creating convincing deepfake videos of celebrities and public figures to promote fake investment platforms. In one documented case, an Australian man lost $80,000 in cryptocurrency after viewing a deepfake video of Elon Musk on social media.

These incidents are part of a larger pattern. 36% of Australian consumers and 20% of businesses were targeted by deepfakes in the past 12 months alone, with 22% of targets admitting to falling for the deception. However, many Australian businesses impacted by scams do not report incidents, meaning the real numbers are likely higher than official figures suggest.

AI-accelerated ransomware attacks

Traditional ransomware already costs Australian organisations millions annually. Now, cybercriminals are using AI to identify network vulnerabilities faster, automate phishing campaigns at unprecedented scale, and personalise ransom demands based on extracted business intelligence. 

What makes AI-enhanced ransomware particularly dangerous is its ability to adapt attack vectors in real-time. Traditional security measures that rely on signature-based detection become ineffective against malware that can rewrite itself to avoid detection.

Supply chain compromise at machine speed

AI enables attackers to infiltrate supply chains with unprecedented efficiency. Automated tools can scan thousands of vendor networks simultaneously, identifying the weakest link in complex business relationships. For Australian businesses with extensive partner ecosystems, this represents a multiplied attack surface that traditional security perimeters cannot adequately protect.

AI in disaster response: intelligence as your strongest ally

While AI amplifies certain threats, it simultaneously offers the most advanced disaster response capabilities ever available to Australian businesses. The key lies in implementing AI-driven defences faster and more comprehensively than attackers can deploy AI-powered offences.

Predictive threat detection and early warning systems

Modern AI systems can analyse network traffic patterns, user behaviour and system performance metrics to identify potential failures or attacks hours or even days before they manifest as outages. Unlike traditional monitoring systems that react to problems after they occur, ensuring your AI in disaster response can predict and prevent many disasters entirely.

IDC research indicates that AI-powered disaster recovery systems will soon offer built-in intelligence that identifies issues and mitigates or remediates them, allowing businesses to run with minimal human intervention.

Automated incident response and containment

When disasters do strike, AI-enabled systems can execute complex response protocols automatically. This includes isolating affected systems, rerouting network traffic, spinning up backup infrastructure and even coordinating with external recovery services, all within minutes of detection.

Recent advances in AI-enabled runbooks now allow organisations to create dynamic recovery procedures that adapt based on the specific nature and scope of each incident, moving beyond static disaster recovery plans.

Intelligent resource allocation during crisis

AI excels at optimising resource allocation when systems are under stress. During a disaster, AI can determine which systems need immediate attention, which can be temporarily deprioritised and how to most efficiently distribute available computing power, bandwidth and personnel to minimise business impact.

Enhanced business continuity through machine learning

AI systems learn from each incident, building institutional knowledge that improves response times and success rates over time. This continuous learning approach means your disaster response capabilities become more sophisticated with each event, rather than relying solely on human memory and documentation.

Strategic implementation: balancing AI risks and rewards

Successfully leveraging AI in disaster response while protecting against AI-powered threats requires a carefully balanced approach that addresses both defensive and offensive AI capabilities.

Establish AI-aware governance frameworks

Your disaster response strategy must account for AI-specific risks and capabilities. This means updating traditional business continuity plans to include:

• AI system dependencies: Document which critical business functions rely on AI systems and ensure backup processes exist
• AI threat vectors: Include deepfake detection, AI-powered social engineering and automated attacks in your threat models
• AI recovery protocols: Develop procedures for restoring AI-dependent systems and validating their integrity post-incident

Implement layered AI defences

Effective protection against AI-powered attacks requires multiple complementary technologies:

• Behavioural analytics: Deploy AI systems that establish baseline user and system behaviours, flagging anomalies that could indicate compromise
• Deepfake detection tools: Implement automated systems that can identify synthetic media in communications
• AI-powered email security: Use machine learning to detect sophisticated phishing attempts that traditional filters miss

Develop AI incident response capabilities

Train your teams to recognise and respond to AI-specific attacks. This includes educating them to understand how deepfakes are created and distributed, recognising the signs of AI-enhanced social engineering and knowing when to escalate AI-related security incidents.

Partner with AI-capable disaster recovery providers

Not every organisation needs to build AI capabilities in-house. Forward-thinking disaster recovery service  increasingly offer AI-enhanced features, including automated failover, intelligent backup scheduling and predictive maintenance capabilities.

The path forward: preparing for an AI-integrated future

As AI continues to evolve, the gap between organisations that successfully integrate AI into their disaster response strategies and those that don't will widen dramatically. Early adopters will benefit from more sophisticated defences, faster recovery times and lower total costs of business disruption.

The key to success lies in starting with pilot implementations that demonstrate clear value while building the expertise and confidence needed for broader deployment. This might begin with AI-enhanced monitoring for non-critical systems, automated backup verification, or intelligent log analysis.

What matters most is beginning the journey now, while the technology is still developing and before AI-powered threats become even more sophisticated and widespread.

Ready to strengthen your disaster response strategy with AI? Contact us to discover how Huon IT can help you harness artificial intelligence for business resilience while protecting against AI-powered threats.