Private 5G networks face growing cybersecurity threats as AI adoption accelerates

Private 5G networks are being rapidly deployed across industries as enterprises seek greater control, lower latency, and enhanced security compared to public mobile networks. These networks are becoming integral to critical sectors, including energy, healthcare, logistics, and smart manufacturing. However, new research from cybersecurity firm Trend Micro and its subsidiary CTOne suggests that despite widespread reliance on AI security tools, private 5G networks face significant vulnerabilities due to a lack of specialized communications technology (CT) security expertise.

As organizations embrace AI-powered cybersecurity solutions to protect their networks, they may be overlooking fundamental security measures, leaving their systems exposed to cyberattacks. The research highlights a crucial gap between the rapid expansion of private 5G networks and the ability of enterprises to secure them effectively.

AI Security Alone Fails to Close Private 5G Vulnerabilities

Private 5G networks are positioned as a game-changer for industries requiring fast, reliable, and secure wireless communications. However, the integration of AI into network security has created a false sense of protection. While AI security tools enhance detection and response capabilities, they cannot fully replace human expertise or proactive security strategies.

Cybersecurity analysts warn that enterprises must go beyond AI-driven monitoring and invest in comprehensive risk management strategies tailored to private 5G networks. The research found that nearly all IT and cybersecurity professionals acknowledge the importance of AI security tools, with 62% already using them and another 35% planning to adopt them. The most commonly deployed AI-driven capabilities include predictive threat intelligence, continuous adaptive authentication, zero-trust enforcement, and self-healing networks with automation.

Despite these advancements, experts caution that organizations cannot rely solely on AI to manage their cybersecurity risks. Without the necessary CT security expertise, enterprises may fail to implement essential safeguards, exposing their networks to potential cyberattacks. The rapid adoption of AI in network security must be accompanied by human oversight and a deeper understanding of attack surface management.

Limited In-House Expertise Weakens Private 5G Defenses

One of the most pressing concerns outlined in the research is the shortage of in-house expertise in private 5G security. The study reveals that only 20% of organizations have a dedicated team for securing their communications networks. Instead, the responsibility often falls on executives such as Chief Technology Officers or Chief Information Officers, many of whom lack specialized knowledge in CT security.

This skills gap has created a vulnerability that cybercriminals can exploit. Without proper security frameworks, private 5G networks remain susceptible to attacks targeting weak authentication mechanisms, unsecured APIs, and misconfigured network access controls. A lack of proactive attack surface management can result in undetected threats moving laterally within the network, increasing the risk of data breaches and service disruptions.

Cybersecurity specialists emphasize that enterprises need to adopt security solutions that provide full visibility across their network infrastructure. Without end-to-end monitoring, security teams may struggle to identify vulnerabilities before attackers exploit them. As private 5G networks expand to support more wireless applications, organizations must ensure their security operations centers are equipped to handle emerging threats.

Underfunded Security Budgets Leave Networks Exposed

Despite the growing reliance on private 5G networks for mission-critical operations, security budgets remain insufficient. The research found that on average, only 18% of organizations’ overall security budgets are allocated to securing private 5G deployments. This underinvestment is particularly concerning given the volume of sensitive data that flows through these networks.

Industries such as healthcare, energy, and smart manufacturing rely on private 5G networks to transmit confidential information, control industrial automation systems, and support real-time decision-making. Without robust cybersecurity measures, these networks become attractive targets for cybercriminals seeking to exploit vulnerabilities in AI security tools or gain unauthorized access to critical infrastructure.

Security experts warn that failing to allocate adequate resources to private 5G security could lead to severe financial and operational consequences. A successful cyberattack on an inadequately protected network could result in regulatory penalties, reputational damage, and disruption of essential services. As the adoption of private 5G networks continues to grow, enterprises must prioritize cybersecurity investments to protect their digital infrastructure.

Compliance Challenges Add Another Layer of Risk

Beyond cybersecurity threats, enterprises deploying AI-powered security for private 5G networks must also navigate complex regulatory and compliance challenges. The research found that many organizations lack proper safeguards when using AI for network monitoring and traffic analysis.

Approximately half of the surveyed organizations fail to ensure compliance with major data privacy regulations such as the General Data Protection Regulation (GDPR). Additionally, encryption practices remain inconsistent, with only 51% encrypting data at rest and in transit. Strict access controls for AI models are enforced by just half of respondents, while only 44% implement data anonymization techniques to protect sensitive information.

These shortcomings create significant legal and financial risks for enterprises operating private 5G networks. Non-compliance with data protection regulations can result in substantial fines and reputational harm. As AI security tools become more integrated into network operations, enterprises must establish clear policies to manage data privacy risks and ensure regulatory adherence.

The Urgent Need for a Holistic Private 5G Security Strategy

The rapid expansion of private 5G networks presents a major opportunity for businesses seeking enhanced connectivity, but security concerns must be addressed with urgency. AI security tools play a crucial role in modern cybersecurity strategies, but they cannot function effectively without human oversight and expertise in communications technology.

Enterprises must adopt a comprehensive security approach that includes proactive attack surface management, real-time threat intelligence, and end-to-end network visibility. Investing in CT security talent and allocating sufficient resources to private 5G security will be critical in preventing cyberattacks and maintaining compliance with evolving regulatory requirements.

With industries becoming increasingly reliant on private 5G networks to support digital transformation initiatives, the risks associated with inadequate security measures will only continue to grow. Organizations that fail to implement a holistic cybersecurity strategy may find themselves vulnerable to sophisticated cyber threats, jeopardizing their data integrity and operational stability.