Why Operators Can’t Wait - The Urgent Need to Accelerate AI Adoption

As we head into 2025, AI has become a mainstay of how we live, learn and work. And that is no different for us, the telecom sector. With 65% of operators reporting that they have implemented an AI strategy, according to GSMA Intelligence1, we are firmly in the ‘how soon’ not ‘if’ stage of AI adoption. But moving from strategy to implementation requires real investment to achieve the productivity, efficiency and cost-saving benefits that operators anticipate. The adoption of AI in the telco sector has been slow so far. According to the earlier mentioned GSMA Intelligence report:

22% of survey respondents said they allocated less than 5% of their digital budgets to AI
4% allocated more than 25% of their digital budgets to AI.

The industry’s current level of spending on AI is being outpaced by other sectors, such as financial services, software and information services and retail. According to IDC2, these three sectors alone will account for approximately 45% of all AI spending over the next five years. For Communications Service Providers (CSPs) to transform their focus from connectivity to enabling intelligent digital ecosystems, the telecom sector needs to act now.

At Mobileum, we believe that AI provides telcos a unique opportunity to transform. Here are our top five reasons why telcos need to accelerate their AI investments now so that they are not left behind in the AI-powered era.

OPTIMIZING PERFORMANCE AND ENHANCING CUSTOMER EXPERIENCE

McKinsey3 projects that the telecom sector could experience 2.3-3.7% revenue and productivity gains with GenAI, equivalent to $60-100 billion globally. Combining GenAI and predictive analytics can deliver powerful insights to optimize network performance and enhance customer experience. For example, by utilizing unstructured data from customer interactions, such as conversations with customer service representatives or social media comments, CSPs can add a new layer of precision to their network investment, planning, and design decisions.

ENSURING HIGH-QUALITY SERVICES ANYTIME, ANYWHERE

As 5G adoption reaches a tipping point, the rollout of low-latency, high bandwidth services will accelerate. In this rapidly evolving landscape, CSPs must gain deep insights into both the service and its usage context to achieve faster time-to-market and ensure consistent service quality post- launch. GenAI will play a pivotal role in this transformation by enabling the creation of synthetic data that accurately mimics real customer usage patterns for testing and development. Additionally, GenAI can accelerate testing cycles and enhance service delivery through AI-driven automation, ensuring seamless user experiences.

RISING SECURITY AND FRAUD THREATS

According to the GSMA Intelligence Operator survey, nearly 50% of operators consider cybersecurity concerns to be the biggest barrier to achieving their AI goals. Among these threats, phishing/smishing ranks highest, with 88% of operators identifying it as the primary concern.

Machine Learning, AI and GenAI are both allies and adversaries for those in charge of protecting telecom networks from security breaches and fraud attacks. On the one hand, there is a real risk that AI can be used for data poisoning – where attackers manipulate inputs to mislead models – or for synthetic identity fraud and deepfake scams. On the other hand, AI and GenAI offer powerful tools to combat these evolving threats. By leveraging GenAI, CSPs can stay ahead of malicious actors by simulating potential security threats and attack scenarios, enabling their systems and teams to proactively learn and adapt.

This approach helps network security teams to prepare for the challenges of an AI-driven threat landscape while strengthening security and trust mechanisms with AI-powered, real-time threat detection and mitigation. For example, GenAI-powered fraud prevention systems can identify and block synthetic content, such as deepfake images and voice clones, ensuring greater protection against fraudulent activities. As telecom fraud continues to rise and regulatory scrutiny intensifies, leveraging AI to safeguard networks and maintain compliance is more critical than ever.

CAPTURING NEW REVENUE STREAMS

Beyond the productivity and efficiency gains AI offers, creating AI-driven revenue streams and enhancing customer services are top priorities for CSPs when defining their AI strategies. However, for GenAI to uncover smarter monetization opportunities, CSPs must integrate unstructured data from sources beyond traditional OSS/BSS systems with structured data within the telco domain.

By doing so, GenAI can deliver real- time network insights and generate contextual triggers that drive new revenue. For example, operators can leverage GenAI to provide personalized travel recommendations for customer segments at key points in their journey and lifecycle, enhancing engagement and boosting revenue. At the enterprise level, GenAI can be instrumental in designing tailored 5G network solutions that address unique business needs across industries such as IoT, smart factories, and AR/VR. This enables CSPs to offer highly customized connectivity solutions that drive innovation and business growth for enterprise customers.

ENSURING REGULATORY COMPLIANCE

AI raises many regulatory questions about the responsible and ethical use of AI when it comes to deploying AI systems and protecting customer data. The rise of AI Agents to oversee and pilot important business processes, with minimal human oversight, is leading to exponential productivity gains and high-impact business outcomes. This is particularly true for AI Agents that are designed to help CSPs meet their regulatory reporting requirements. With AI Agents tailored for telecom industry frameworks, CSPs not only can save time by automating traditional processes but ensure error-free reporting with greater transparency and traceability.

Ultimately, AI and GenAI are revolutionizing how CSPs optimize network performance, enhance service quality, unlock new revenue opportunities, improve customer experiences, and strengthen security and regulatory compliance.

Embracing these innovations is no longer optional – it’s essential for staying competitive in an AI-driven landscape.