Cyber threats have become more frequent and more sophisticated in recent years. Incidents such as the large-scale distributed denial-of-service (DDoS) attack on the Russian Foreign Ministry during the recent BRICS summit highlight the disruptive potential of ransomware attacks and phishing campaigns based on AI.
This follows a broader trend of high-profile cyberattacks that increasingly harness and leverage AI and automation for targeted disruption. In an era where organizations increasingly rely on interconnected networks, the threat and consequences of an attack have never been higher. With the threat surface increasing, a single vulnerability on a network endpoint can easily compromise an entire critical infrastructure with devastating effect. Indeed, in 2024, the cost of cybercrime will exceed 2.2 trillion US dollars worldwideAI being cited as an aggravating factor.
On the other hand, with the global cybersecurity talent gap expected to reach 85 million workers by 2030The critical shortage of cybersecurity professionals leaves organizations vulnerable. This problem is particularly acute in Asia-Pacific (APAC), which represents more than half of the global cybersecurity talent gap. Organizations are struggling to fill positions, with some even resorting to bonuses to hire qualified talent. How can APAC organizations fill this talent gap while strengthening their defenses?
Leveraging AI to fill the security talent gap
The rapid development of AI-based tools in recent years offers a promising solution to the talent shortage facing the cybersecurity industry today. AI’s ability to facilitate search, content creation, and analysis of large data sets has improved productivity while making advanced insights more accessible across industries. In cybersecurity, tools like AI Copilots help address the talent shortage by increasing productivity and empowering junior analysts and security teams to tackle complex cases with answers and insights guided.
AI co-pilots automate routine work, freeing security teams from tedious manual tasks to focus on strategic impact. By streamlining workflows, AI co-pilots reduce the reliance on highly experienced talent because junior analysts have accessible information to handle higher-level tasks. As a result, the security sector can better manage its human resources, which are already scarce in the APAC region.
Natural language processing (NLP) allows security professionals using AI co-pilots to easily create advanced search queries without requiring programming knowledge. By synthesizing real-time security data into actionable intelligence, the need for manual escalations is significantly reduced, increasing productivity and speeding up threat investigation and response times by up to two to three times.
Additionally, the conversational capabilities of Large Language Models (LLM) enable analysts to ask questions in natural language, quickly grasp threat contexts, and follow step-by-step guidance to mitigate cybersecurity threats. This move toward conversational AI minimizes training time for new analysts by equipping them with immediate knowledge. The use of AI co-pilots makes advanced cybersecurity roles more accessible, allowing organizations to fulfill these roles more easily while maintaining rigorous threat response standards.
Improved visibility and threat detection with AI-driven analysis
As organizations shift to multi-cloud infrastructures and adopt hybrid models, the complexity of monitoring and securing digital assets has skyrocketed. Traditional security tools have limited capabilities because they lack the flexibility and coverage to provide comprehensive information across various platforms, leaving critical blind spots for malicious actors to exploit. Security teams struggle to detect, respond to, and mitigate potential vulnerabilities without a real-time view of their infrastructure. Specifically in the APAC region, organizations are only able to monitor approximately 62% of their IT environments, according to research from Exabeam’s “The State of Threat Detection, Investigation, and Response 2023” report, making Real-time threat visibility a challenge.
AI Copilots significantly improve visibility into an organization’s threat landscape with LLMs equipped to integrate multiple data sources. Their enhanced ability to integrate anomaly detection, threat scores, and historical benchmarks provides analysts with contextualized data to identify risks faster. For example, AI tools combining machine learning and LLM capabilities enable proactive threat detection and management, solving problems ranging from insider risks to compromised credentials.
AI as an ally in the fight against cyber threats
AI co-pilots are poised to bridge the gap between growing cybersecurity demands and talent shortages, strengthening the scalability and resilience of security operations. As AI technology advances, these co-pilots will become more sophisticated in tandem, allowing analysts to effectively combat cyber threats. We envision a future in which AI becomes a trusted ally in the fight against ever-evolving digital threats, enabling AI and human analysts to work closely together to redefine cybersecurity defense strategies in the modern world .
