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Why AI Alone Can't Defend Your Business And What The Middle East Should Do About It
(MENAFN- Mid-East Info) WHY AI ALONE CAN'T DEFEND YOUR BUSINESS – AND WHAT THE MIDDLE EAST SHOULD DO ABOUT IT
Mark Morland, VP Sales MENA at Obrela As businesses across the Middle East accelerate their digital transformation efforts, the region's cyber threat landscape is becoming increasingly complex. From hyper-connected smart cities to rapidly expanding fintech ecosystems, cybercriminals now have more entry points than ever before. Among the many solutions being considered, artificial intelligence (AI) is emerging as a powerful force in cybersecurity. AI brings speed, scalability, pattern recognition and predictive insights to security operations. However, AI alone is not enough. The most effective approach to cybersecurity is a hybrid model – pairing AI's computational power with human intelligence. Machines process vast volumes of data, while human experts can provide the necessary context, judgment, and strategic oversight. This fusion enhances Security Operations Centres (SOCs), ensuring a more resilient and adaptive defence strategy. AI Is a tool, not a solution Security teams manage an overwhelming volume of data from various sources, including endpoints, cloud environments and complex network architectures. AI can rapidly triage this data, detect anomalies and classify threats at speeds far beyond human capability. Deep learning enables AI to sift through historical datasets to identify unusual behaviours, such as unexpected access patterns or system anomalies. Machine learning then prioritises this data, allowing security analysts to focus on high-risk threats while filtering out false positives. Meanwhile, generative AI is beginning to automate incident reports and documentation, streamlining operations so analysts can concentrate on strategic work. Yet, AI is only part of the equation. Left unchecked, AI may misinterpret context or act on outdated information. Threat landscapes evolve constantly, necessitating continuous tuning of AI models and the regular update of training data. Without human oversight, AI-driven security measures could lead to misguided decisions at critical moments. The value of human context in the Middle East Context is particularly important in regions like the Middle East, where geopolitical considerations, regulatory compliance and cross-border complexities add layers of nuance. As an example, AI can detect a spike in data exfiltration, but a skilled analyst is needed to determine whether it's a legitimate internal transfer or a critical breach attempt. This is especially vital in sensitive sectors like energy, finance and government, where trust, accuracy, and risk management are paramount. Human analysts are also uniquely positioned to assess the broader implications of cyber threats. They can differentiate between false positives and actual security breaches, coordinate response strategies across departments, and tailor risk mitigation approaches to an organisation's specific infrastructure and regulatory landscape. For example, in the GCC region, data sovereignty and local cloud requirements create additional complexities that demand a human-led, region-specific cybersecurity strategy. Why a hybrid SOC model is the future The most effective SOC model integrates AI at every layer while keeping human expertise at its core. AI can automate repetitive tasks, like scanning for known malware, analysing behavioural deviations, and performing initial triage on security alerts. But cybersecurity professionals must make the final decisions, refine AI tools, and continuously train security systems with real-world feedback. This collaborative approach offers multiple benefits, in that it:
Mark Morland, VP Sales MENA at Obrela As businesses across the Middle East accelerate their digital transformation efforts, the region's cyber threat landscape is becoming increasingly complex. From hyper-connected smart cities to rapidly expanding fintech ecosystems, cybercriminals now have more entry points than ever before. Among the many solutions being considered, artificial intelligence (AI) is emerging as a powerful force in cybersecurity. AI brings speed, scalability, pattern recognition and predictive insights to security operations. However, AI alone is not enough. The most effective approach to cybersecurity is a hybrid model – pairing AI's computational power with human intelligence. Machines process vast volumes of data, while human experts can provide the necessary context, judgment, and strategic oversight. This fusion enhances Security Operations Centres (SOCs), ensuring a more resilient and adaptive defence strategy. AI Is a tool, not a solution Security teams manage an overwhelming volume of data from various sources, including endpoints, cloud environments and complex network architectures. AI can rapidly triage this data, detect anomalies and classify threats at speeds far beyond human capability. Deep learning enables AI to sift through historical datasets to identify unusual behaviours, such as unexpected access patterns or system anomalies. Machine learning then prioritises this data, allowing security analysts to focus on high-risk threats while filtering out false positives. Meanwhile, generative AI is beginning to automate incident reports and documentation, streamlining operations so analysts can concentrate on strategic work. Yet, AI is only part of the equation. Left unchecked, AI may misinterpret context or act on outdated information. Threat landscapes evolve constantly, necessitating continuous tuning of AI models and the regular update of training data. Without human oversight, AI-driven security measures could lead to misguided decisions at critical moments. The value of human context in the Middle East Context is particularly important in regions like the Middle East, where geopolitical considerations, regulatory compliance and cross-border complexities add layers of nuance. As an example, AI can detect a spike in data exfiltration, but a skilled analyst is needed to determine whether it's a legitimate internal transfer or a critical breach attempt. This is especially vital in sensitive sectors like energy, finance and government, where trust, accuracy, and risk management are paramount. Human analysts are also uniquely positioned to assess the broader implications of cyber threats. They can differentiate between false positives and actual security breaches, coordinate response strategies across departments, and tailor risk mitigation approaches to an organisation's specific infrastructure and regulatory landscape. For example, in the GCC region, data sovereignty and local cloud requirements create additional complexities that demand a human-led, region-specific cybersecurity strategy. Why a hybrid SOC model is the future The most effective SOC model integrates AI at every layer while keeping human expertise at its core. AI can automate repetitive tasks, like scanning for known malware, analysing behavioural deviations, and performing initial triage on security alerts. But cybersecurity professionals must make the final decisions, refine AI tools, and continuously train security systems with real-world feedback. This collaborative approach offers multiple benefits, in that it:
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Reduces alert fatigue by prioritising actionable threats.
Enhances response times through automation while ensuring reactions are proportionate and informed.
Improves analyst efficiency and well-being by removing repetitive tasks, enabling professionals to focus on high-value investigative work.
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