AI IN CYBERSECURITY: AN OPPORTUNITY AND A RISK
Artificial Intelligence (AI) is often described as both an opportunity and a risk—an apt metaphor rather than an exaggeration. While AI presents impressive advantages such as increased productivity, smarter decision-making, and seamless automation, it also raises significant concerns. These include job displacement, privacy breaches, bias, and regulatory challenges. In more extreme scenarios, advanced AI may contribute to disinformation campaigns or even power autonomous weapons. Although total annihilation by AI seems unlikely, its existential risk is taken seriously even by tech leaders. AI’s potential impact on cybersecurity—both as a threat and as a safeguard—is particularly noteworthy.
A POWERFUL CYBERSECURITY TOOL
In cybersecurity, AI holds immense promise as a high-speed, multi-functional ally. Its ability to analyse massive data sets in real time allows for the rapid identification of behavioural patterns and anomalies. Machine learning (ML), a subset of AI, continuously evolves, improving its accuracy with every data point processed. For example, generative AI helps contextualise threat analysis by transforming complex information into accessible formats like natural language or visual summaries. Human input remains vital, but AI significantly enhances the speed and effectiveness of threat detection. As Sridhar Muppidi, CTO of IBM Security, notes, leading organisations are now leveraging AI-powered automation to improve insights, productivity, and scalability in threat management.
PHISHING DETECTION AND INCIDENT RESPONSE
AI excels at detecting phishing attempts—one of the most common attack vectors. It can scan emails and sender metadata instantly, identifying threats that traditional systems might miss. In incident response, AI can automate containment processes such as isolating infected systems and blocking malicious IPs. This reduces damage and accelerates recovery times, helping protect sensitive data.
AI IN CYBERSECURITY: ENDPOINT DETECTION AND MDR
AI also plays a central role in Endpoint Detection and Response (EDR) and its advanced form, Managed Detection and Response (MDR). These tools offer around-the-clock monitoring and combine human oversight with AI’s analytical capabilities. AI identifies and secures endpoints across a network and ensures they are updated and patched. AI-enhanced detection engineering further improves the accuracy of threat identification, while managed Security Information and Event Management (SIEM) platforms benefit from AI’s capacity to ingest, correlate, and interpret vast log data. AI also enables sentiment analysis and sub-human reaction times—far beyond human capability, giving cybersecurity teams a critical edge.
THE CLOUD AND AI: A SYNERGISTIC RELATIONSHIP
Cloud computing, used by over 96% of global companies, relies heavily on AI for security. Cloud Security Posture Management (CSPM) uses AI to detect and fix misconfigurations. Cloud Workload Protection (CWP) monitors workloads and detects malware and unauthorised access. Given the scale of cloud infrastructure today, AI is indispensable in managing security risks across multiple cloud environments. It offers the visibility and responsiveness required to protect personal and organisational data.
AUGMENTING SECURITY TEAMS AND PROCESSES
AI significantly improves the speed and precision of identifying real threats by sifting through thousands of logs from tools like SIEM and MDR. It enhances threat reporting and simplifies communication for cybersecurity professionals. Generative AI assists by translating technical threat data into natural language, making insights accessible and actionable. AI also identifies unknown devices, outdated systems, and weak spots in networks, allowing organisations to prioritise their responses. Fortinet encapsulates AI’s contribution by stating that AI revolutionises threat detection, automates response, and strengthens vulnerability management.
AI INTEGRATION IN SECURITY SYSTEMS
Modern cybersecurity tools increasingly incorporate AI. Next-generation firewalls, for instance, use AI to process threat intelligence, helping them adapt to new threats. AI-based endpoint solutions detect malware, highlight outdated systems, and contain breaches. AI-powered Intrusion Detection and Prevention Systems (IDPS) monitor network traffic to identify and block suspicious activity. As Internet of Things (IoT) devices grow, projected to reach 40 billion by 2030, AI will be critical in monitoring these often poorly secured endpoints.
THE FUTURE OF CYBERSECURITY JOBS
While AI may automate certain cybersecurity tasks, it also creates demand for roles in AI governance, risk management, and analytics. Cybersecurity professionals must upskill to work in synergy with AI, not fear replacement. Human judgment, intuition, and context remain irreplaceable assets in cybersecurity. As data analyst Eric Weisburg observes, job security depends more on one’s ability to adapt AI tools than on the tools themselves.
THE DARK SIDE OF AI
Unfortunately, cybercriminals are also adopting AI to elevate their attacks. AI-powered malware, phishing, and ransomware are growing in sophistication, making them harder to detect. The UK’s National Cyber Security Centre (NCSC) warns that AI enables criminals to analyse stolen data more efficiently, train malicious models, and execute advanced campaigns. AI also lowers the barrier to entry for inexperienced hackers, making ransomware more accessible. With payments skyrocketing to an average of $2 million in 2024 (up from $400,000 in 2023), attacks are becoming increasingly costly.
AI EXPLOITING AI SYSTEMS
A concerning development is the use of AI to attack AI-powered security systems. Automated tools can exploit vulnerabilities at scale without human input. Large Language Models (LLMs), like ChatGPT, are vulnerable to prompt injection attacks. In these cases, hackers manipulate prompts to override developer instructions, forcing systems to act against their intended programming. Currently, there is no foolproof solution to this challenge.
PHISHING, SOCIAL ENGINEERING, AND DEEPFAKES
AI-generated content is also fuelling social engineering. Convincing emails, messages, and even phone calls can now be crafted at scale using AI-generated text and voice. Some campaigns incorporate real-time data, making them seem even more credible. AI can replicate legitimate websites almost perfectly, making it difficult for users to detect fraud. Deepfakes, once a source of online amusement, now represent a serious threat. They can be used for impersonation, harassment, and spreading misinformation. Fortunately, AI can also help detect and mitigate deepfake fraud, but it requires constant vigilance and technological countermeasures.
THREATS TO CRITICAL INFRASTRUCTURE AND DEMOCRACY
AI’s impact goes beyond the corporate world. It poses risks to national infrastructure, such as healthcare systems, power grids, and financial institutions. Nation-states could exploit AI to conduct large-scale disinformation campaigns and even digital warfare. The UK Parliament warns that AI-generated disinformation could provoke confusion, deepen political division, and undermine democracy.
A CALL TO ACTION: EMBRACING AI RESPONSIBLY
Despite the dangers, the benefits of AI outweigh the risks. AI should be seen as a support mechanism, not a replacement. To prepare for future challenges, organisations should implement zero-trust models enhanced by AI and adopt AI-driven strategies for continuous threat detection and response. Ultimately, AI is set to transform cybersecurity. While it introduces new avenues for attacks, it also offers unparalleled tools to defend against them. By combining human expertise with AI’s capabilities, we can build safer digital environments for individuals, businesses, and societies alike.
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