For more than three decades, mobile network operators (MNOs) have been channeling their research and development efforts into five key areas: messaging, roaming, policy, signaling, and clearing. Given the vast quantities of data processed through these systems, it’s only natural that MNOs are increasingly focusing on leveraging artificial intelligence (AI) to enhance features, maximize resource efficiency, and safeguard customer data, all while fulfilling their service commitments.
Think of an MNO, in part, as a massive data bus business — it serves, transports, analyzes, and protects data within its walls and among operators, enterprises, and end users around the world. Here are some of the most compelling examples of how MNOs are using AI in these five areas — and how they are poised to do so — to streamline their processes and maximize value.
Messaging fraud prevention
AI takes center stage in thwarting attempts by criminals to communicate with end users. AI models can classify 99% of messages, with the remaining 1% managed through manual regular expression policies and static blocks. Moreover, AI can analyze sender intent, which is crucial to assessing distribution and other costs associated with delivering legitimate content.
Although generative AI has empowered criminals to craft more sophisticated fraudulent schemes, particularly in languages that are not native to them, telecom operators are using AI to fight back. This “Defensive AI” technology is now evolving to detect nuanced scams like spear phishing and pig butchering, where fraudulent intent unfolds gradually over multiple exchanges.
Global policy governance
When MNOs facilitate international roaming, they must comply with the local regulatory frameworks concerning messaging and content. AI is increasingly being utilized to analyze, monitor, and enforce these policies in real time — not just to shield operators from international legal issues but also to potentially safeguard users from legal repercussions. For instance, engaging in marketing activities like online gambling might be permissible in one country but prohibited in another, such as the U.S. Similarly, topics like marijuana sales might be legal in some U.S. states yet remain federally prohibited. MNOs have a responsibility to shield roamers from receiving those types of messages where they’re banned.
However, with the adoption of RCS (Rich Communication Services) messaging, which largely shifts control over the messaging protocol to tech giants like Google and Apple, MNOs face a dilemma. This shift may compromise their ability to enforce content policies effectively, introducing new risks. It remains uncertain how MNOs will maintain compliance and protect their customers and their own interests as RCS becomes more prevalent.
5G signaling, IoT, and roaming
5G technology presents substantial opportunities for AI integration, particularly for MNOs that wish to provide unique enterprise solutions beyond their traditional services. Take, for instance, the realm of supply chain logistics, where IoT devices and sensors are increasingly used for tracking and visibility. With 5G enabling accurate, cell-based geolocation, MNOs can develop systems that monitor shipping containers throughout their journeys — from production facilities to warehouses, through various checkpoints, and to destinations, utilizing their networks and those of international roaming partners.
AI’s role in this scenario is pivotal. It can continuously analyze data streams from these sensors and promptly alert any anomalies that might suggest theft, adverse weather conditions, or civil unrest. Such predictive analytics help reduce shipping costs, detect potential criminal activities, and enhance customer service by providing real-time updates and insights. This integration of AI and 5G by MNOs showcases their potential to become key players in the enterprise solutions market by offering services far beyond conventional telecom offerings.
General AI/ML stacks
While MNOs stand to benefit directly from their implementation of AI processes, their investments in next-generation technology will also help organizations maximize AI’s potential.
As mobile operators roll out 5G, they’re poised to provide cloud services directly from cell towers and enable businesses to execute their AI/ML models and standard containerized applications in closer proximity to mobile users. This approach leverages the benefits of low latency and high performance inherent in 5G by extending computing capabilities from centralized regional clouds to the edge.
This approach positions operators to create a new market segment by integrating their existing infrastructure — cell towers — with a network of micro-distributed computing resources. Furthermore, operators could venture into offering graphics processing unit (GPU) offloading services to these local compute-enabled towers, thereby diminishing the processing power required by individual devices. This strategy could drop device costs dramatically, make high-performance smartphones accessible to a larger audience, and free up resources to accelerate global 5G adoption and AI-powered innovation.
MNOs are at a pivotal juncture where they can evolve by expanding their utility role to significant players in the enterprise software and services market. Historically, their strength has been in “the network,” but by integrating AI with their network capabilities, MNOs can secure their relevance and success well into the future. This fusion of network and AI will enhance their service offerings while positioning them as indispensable partners for businesses seeking advanced tech solutions.
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