When benchmarking cybersecurity solutions, evaluate their detection speed, the quality of LLM integration, and the depth of automation they offer. Testing the solution’ s ability to identify and neutralise AI-generated threats is crucial, as is ensuring that the tools simplify workflows, integrate with existing infrastructure, and provide actionable insights.

Resilience and recovery measures that CIOs and CISOs should consider now include self-healing systems, where AI autonomously rolls back malicious changes and restores compromised endpoints. Immutable backups integrate with ransomware detection to safeguard data.

Behavioural analytics using machine learning identifies anomalies in user and system behaviour, while predictive intelligence anticipates emerging threats by analysing historical and real-time data, enabling proactive defences. access rules based on real-time risk assessments. Advanced phishing detection capabilities utilise Generative AI to detect and analyse sophisticated, AIgenerated phishing attacks.

Threat deception and simulation tactics have also evolved. AI-generated decoys create realistic traps to confuse attackers and gather intelligence, while simulated AI-driven attacks test organisational

defences against adversarial AI-driven strategies.

Cloud-native security solutions feature container and serverless monitoring, securing dynamic environments

Generative AI and LLMs are transforming cybersecurity by enhancing threat analysis.

Generative AI and LLMs are transforming cybersecurity by enhancing threat analysis. LLMs summarise complex threat data and provide actionable insights. They also strengthen incident communication by crafting clear, context-aware incident reports to help stakeholders act swiftly. Furthermore, LLMs recommend fixes for vulnerabilities based on global knowledge bases.

Platform solutions offer cross-domain visibility by combining data from endpoints, identities, and networks, enabling holistic monitoring. LLM-powered playbooks automate response actions using natural language inputs. AI and LLMs power Zero Trust and identity protection strategies, dynamically adjusting with AI-driven anomaly detection. LLM-enhanced compliance checks automate the identification of misconfigurations and regulatory risks in cloud systems.

Incident response and automation are supported by autonomous SOC operations, where AI provides enriched context and automated insights for security analysts. SOAR solutions integrated with LLMs streamline workflows and reduce response times by automating repetitive tasks, improving overall efficiency.

Enhanced user education is also essential. Generative AI customises employee awareness programs to address specific risks while providing real-time guidance during potential phishing attempts or policy violations.

Intelligent CIO Middle East Issue 113 | Page 33