Cyber Risk
Securing 5G Private Networks: The Opportunities and Risks of AI
Demand for private 5G networks is skyrocketing, with the market expected to reach nearly $161 billion by 2033
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Demand for private 5G networks is skyrocketing, with the market expected to reach nearly $161 billion by 2033. Enterprises see the benefits of faster, more reliable, and customisable networks, but security concerns remain. While private 5G networks offer more control, they are not inherently secure. AI-powered security presents both an opportunity and a challenge.
To understand the risks, Trend Micro and CTOne commissioned Sapio Research to survey IT and cybersecurity decision-makers across seven countries. The findings reveal a mix of awareness and gaps in protection. Companies worry about supply chain vulnerabilities, insider threats, and the sheer attack surface of connected devices. While 62% already use AI for security, adoption challenges include high costs, false positives, and a lack of expertise. AI itself can also introduce risks, making robust security measures essential.
Another major issue is the shortage of dedicated expertise. Only 20% of organisations have a team focused on securing communications technology, and security budgets for private 5G remain disproportionately low at just 18%. Compliance gaps further expose businesses, with many failing to encrypt data, deploy access controls, or ensure regulatory adherence. Without the necessary investments, organisations leave themselves vulnerable to data breaches, ransomware attacks, and unauthorised access to critical infrastructure.
To strengthen private 5G security, enterprises need a proactive approach. Partnering with experienced security providers, integrating Zero Trust principles, consolidating security platforms, and leveraging AI responsibly are key strategies. Organisations must also prioritize real-time threat intelligence, continuous authentication, and self-healing networks to stay ahead of evolving cyber threats. Managed security services and generative AI can help bridge skills gaps, reduce operational burdens, and enhance overall threat detection and response capabilities.
Businesses should also consider extending their security frameworks to cover the entire 5G ecosystem. This includes protecting base stations, edge computing environments, and network slicing technologies, which are critical for ensuring network segmentation and performance. AI-driven solutions can help automate anomaly detection, predict potential security incidents, and respond faster to threats before they escalate. Furthermore, enterprises must ensure AI models themselves are secured against adversarial attacks, where threat actors manipulate AI algorithms to bypass security controls or generate false positives.
As the regulatory landscape evolves, businesses must also align their security strategies with global compliance requirements such as GDPR, NIST, and industry-specific guidelines. This includes conducting regular risk assessments, encrypting data at rest and in transit, and implementing strict access controls for AI-driven security tools. Additionally, security teams should invest in continuous training programs to equip employees with the necessary skills to manage and respond to emerging threats effectively.
Ultimately, the enterprises that prioritise proactive AI-powered security, robust compliance strategies, and skilled security personnel will be best positioned to reap the benefits of private 5G without exposing themselves to unnecessary risks. By taking a holistic approach to cybersecurity, organisations can not only safeguard their networks but also drive innovation, optimise efficiency, and enhance operational resilience.
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