Cyber threats have become an undeniable reality for businesses worldwide, but for telecom providers, the stakes are even higher.
These companies manage vast infrastructure, oversee sensitive data and facilitate critical communications networks, making them prime targets for cybercriminals.
The industry’s reliance on interconnected networks, cloud-based services and 5G connectivity has exponentially increased its exposure to cyber threats.
Any breach can have cascading effects, impacting millions of users, disrupting essential services and compromising critical data.
Traditional security models were built when threats were static and more predictable. Given the scale and complexity of advanced telecom networks, conventional rule-based systems are struggling to keep up with the speed and sophistication of modern attacks.
According to a recent EY report, in the first half of 2024, the telecommunications sector faced 57 per cent of all distributed denial-of-service attacks. These numbers make one thing clear—telecom providers can’t afford to rely on outdated security models.
To tackle the scale of modern cyber threats, telecom companies need an approach that’s dynamic, adaptive, and built into the very core of their operations. This is exactly why telecom organisations are turning to AI to bolster their cyber defences. A 2024 industry assessment by Statista reveals that more than half of global telecom providers have now integrated AI-driven security measures into their operations.
Moving to proactive security
One of AI’s key strengths in cyber defence lies in its ability to analyse vast datasets in real time, detecting anomalous network traffic and SIM cloning activities. Unlike traditional systems that often struggle to effectively manage the vast scale of telecom infrastructure, AI uses machine learning models to identify abnormal behaviours such as unauthorised access to core networks or sudden spikes in VoIP traffic — which could signal an impending attack.
Another crucial application is AI-powered predictive intelligence, which analyses historical attack patterns and cross-references multiple data sources to forecast threats. AI can identify fraudulent activities by detecting anomalies in call records, messaging traffic and endpoint behaviour, preventing sophisticated cyber schemes before they impact revenue streams and customer trust.
Telecom providers are increasingly turning to AI to enhance their threat detection capabilities, ensuring security measures are not only responsive, but also anticipatory. With a deep understanding of cloud-native technologies, network optimisation and AI models, Persistent helps organisations quickly identify and address threats at scale.
We have noticed organisations that have adopted AI-driven security solutions report significant improvements in threat detection accuracy and response time. By shifting from a reactive stance to an anticipatory security model, businesses gain a competitive edge in mitigating cyber risks before they escalate into full-blown breaches.
AI-driven automation
Proactive threat mitigation is only one part of the equation. Rapid incident response is equally critical in the telecommunication industry. The longer an attack goes undetected, the greater the damage. AI-driven automation is revolutionising incident response by significantly reducing the time between threat detection and network mitigation. A 2024 report from BCG found that AI-enabled security operations centres reduced incident response times by 85 per cent, significantly reducing the impact of cyberattacks.
Beyond speeding responses, AI strengthens security through immediate, automated action. Telecom networks can now use AI to instantly detect and isolate compromised devices, block malicious IPs targeting 5G core infrastructure and quarantine rogue SIM profiles — actions that previously required extensive manual intervention. This rapid response capability is essential in countering advanced persistent threats, which infiltrate telecom networks, disrupt services and exploit vulnerabilities in roaming protocols.
AI is also playing a pivotal role in combating phishing and social engineering attacks. Natural language processing algorithms can analyse email communications, detect phishing attempts and flag malicious messages before they reach their intended targets. Given that phishing remains the most common attack vector — responsible for 83 per cent of breaches in the UK, according to the Cyber Security Breaches Survey 2024 — AI-driven defences are no longer optional; they are essential.
On a broader level, AI is also enhancing telecom’s ability to secure customer communications. AI-powered encryption, anomaly detection in real-time messaging and automated security patches ensure that telecom operators maintain trust while securing voice, data and messaging channels. With telecom serving as the backbone of digital communication, ensuring the integrity of these networks is critical.
Convergence of human and machine intelligence
Despite AI’s advancements in cybersecurity, adversarial AI — where cybercriminals use AI to automate attacks — remains a growing concern. From crafting sophisticated malware targeting 5G networks to executing large-scale SMS fraud, malicious actors are using AI to outmanoeuvre traditional security defences. To stay ahead, telecom providers must continuously evolve their AI-driven security measures.
Another challenge that could jeopardise cybersecurity is over-reliance on AI without human oversight. AI, while powerful, is not infallible. False positives can mistakenly flag legitimate traffic as malicious, while false negatives may allow genuine threats to slip through. It’s important that cybersecurity professionals trust AI for insights and, at the same time, validate threat detections through human judgment to refine the threat detection process.
As AI evolves, its role will extend beyond threat detection and incident response. Future innovations will focus on three vital areas – protecting critical infrastructure, preventing automated misinformation and ensuring compliance with stricter regulations. AI will also continue to safeguard enterprise messaging, email security and encrypted voice transmissions, ensuring seamless and secure communications for telecom providers and their customers.
The future of telecom security and communications will be defined by those who embrace AI’s full potential — proactively securing networks, integrating AI-driven automation and continuously refining security strategies. Telecom leaders must ensure AI is not just an add-on, but an integral component of their cybersecurity framework. As the industry moves towards hyper-connected, AI-powered communications, telecom providers that prioritise AI-driven security will build the foundation for a more resilient, secure and trusted digital ecosystem.