Cyberthreats have escalated in frequency and sophistication in recent years. Incidents like the large-scale distributed denial-of-service (DDoS) attack on Russia’s Foreign Ministry at the recent BRICS summit spotlight the disruptive potential of ransomware attacks and AI-powered phishing campaigns today.
This follows a broader trend of high-profile cyberattacks that increasingly leverage and exploit AI and automation for targeted disruptions. At a time when organisations are increasingly reliant on interconnected networks, the threat and consequences of an attack have never been higher. With the expanded threat surface, a single vulnerability on a network endpoint can easily compromise an entire critical infrastructure to devastating effect. Indeed, in 2024, the cost of cybercrime has soared past US$2.2 trillion globally, with AI named as an aggravating factor.
On the other hand, with the global cybersecurity talent gap projected to reach 85 million workers by 2030, the critical shortage of cybersecurity professionals is leaving organisations vulnerable. This issue is especially acute in Asia-Pacific (APAC), which accounts for over half of the global cybersecurity talent gap. Organisations have been struggling to fill positions, with some even resorting to paying premiums to hire skilled talent. How can APAC organisations bridge this talent gap while simultaneously strengthening their defences?
Leveraging AI to bridge the security talent gap
The rapid development of AI-powered tools in recent years offers a promising solution to the talent shortage faced by the cybersecurity industry today. AI’s ability to assist in research, content creation, and analysis of large data sets has improved productivity while making advanced insights more accessible across industries. In cybersecurity, tools such as AI copilots help address talent shortages by driving productivity and enabling junior analysts and security teams to handle complex cases with guided responses and insights.
AI copilots automate routine work, freeing security teams from time-consuming, manual tasks to focus on delivering strategic impact. By streamlining workflows, AI copilots reduce the reliance on highly experienced talent, as junior analysts are equipped with accessible insights to handle higher-level tasks. As a result, the security industry can better manage its human resources, which are already in short supply in APAC.
Natural language processing (NLP) empowers security professionals who use AI copilots to easily create advanced search queries without requiring programming knowledge. By synthesising real-time security data into actionable intelligence, the need for manual escalations is significantly reduced, boosting productivity and accelerating threat investigation and response times by up to two to three times.
Additionally, the conversational capabilities of large language models (LLMs) allow analysts to ask questions in natural language, quickly grasp threat contexts, and follow step-by-step guidance to mitigate cybersecurity threats. This shift towards conversational AI minimises training time for new analysts by equipping them with immediate knowledge. The use of AI copilots makes advanced cybersecurity roles more accessible, enabling organisations to fill such roles more easily while maintaining rigorous threat response standards.
Enhanced visibility and threat detection through AI-driven analysis
As organisations shift towards multi-cloud infrastructures and adopt hybrid models, the complexity of monitoring and securing digital assets has skyrocketed. Traditional security tools have limited capabilities, as they lack the flexibility and coverage to provide comprehensive insights across diverse platforms, leaving critical blind spots that bad actors can exploit. Security teams struggle to detect, respond, and mitigate potential vulnerabilities without a real-time view of their infrastructure. Specifically in APAC, organisations are only able to monitor about 62% of their IT environments, according to research in Exabeam’s “The State of Threat Detection, Investigation, and Response 2023” report, making real-time threat visibility a challenge.
AI copilots significantly enhance the visibility of an organization’s threat landscape through LLMs which are equipped to integrate multiple data sources. Their enhanced ability to integrate anomaly detection, threat scores, and historical baselines, provides analysts with contextualized data to identify risks faster. For instance, AI tools combining machine learning with LLM capabilities enable proactive threat detection and management, addressing issues from insider risks to compromised credentials.
AI as an ally in the fight against cyberthreats
AI copilots are poised to bridge the gap between rising cybersecurity demands and talent shortages, boosting the scalability and resilience of security operations. As AI technology advances, these copilots will become more refined in tandem, empowering analysts to tackle cyberthreats effectively. We envision a future where AI becomes a trusted ally in the fight against ever-evolving digital threats, allowing AI and human analysts to work closely together to redefine cybersecurity defense strategies in the modern world.
