The telecom industry is on a very interesting cusp/ transformation driven by artificial intelligence (AI) and generative AI technologies. MVNOs are giving a hard time to established Telco Tier 1s. As MVNOs (Mobile Virtual Network Operators) adopt an AI-first approach, every aspect of their operations, from customer service to marketing and sales, will evolve faster than any traditional Operator. In this blog, I will share how the life and journey of MVNOs change with the integration of AI and generative AI tools and applications, and side by side, I will try to highlight the significant ROI benefits of such a transformation for a hypothetical MVNO with 5 million subscribers.

Let me start with Customer service.

Using AI in Customer Service Transformation

Customer service in a traditional MVNO relies heavily on human agents handling inquiries manually. A customer service representative (CSR) starts their day logging into various systems Like Customer Management, Case Management, dealing with a backlog of customer queries. The process involves navigating multiple software interfaces supplied by various IT vendors, leading to longer resolution times and often frustrating customers. CSRs spend a significant portion of their day on such repetitive tasks, such as answering common questions and processing routine requests. Any MVNO/E’s balance sheet shows the maximum spent on Customer Service and Operations. Let's see how it changes when MEVOs adopt an AI-first approach.

In an AI-first MVNO, the role of a CSR is fundamentally different. The day begins by reviewing a real-time AI-generated dashboard. AI chatbots and virtual assistants based on pre-trained data and fine-tuned LLM have already handled standard inquiries and cases overnight, allowing CSRs to focus on complex issues requiring human empathy. AI tools provide integrated customer data and predictive insights, enabling proactive customer service. This reduces response times and enhances customer satisfaction. The AI-first model frees CSRs from repetitive tasks, allowing them to solve challenging problems and improve job satisfaction. AI-driven systems take over routine follow-ups, while CSRs review analytics to refine AI responses, ensuring continuous service improvement.

Monetary Benefits and ROI:

• Cost Reduction: Automation of routine tasks can reduce the number of required CSRs by up to 50% to 75%. Assuming a CSR costs $40,000 annually, savings for 5 million subscribers (requiring roughly 1,000 CSRs traditionally) could be a whooping $20 million per year.

• Customer Retention: Improved customer satisfaction could reduce churn by 2%. For a 5 million subscriber base, retaining an additional 100,000 subscribers annually (each worth $600 in revenue) adds $60 million in revenue.

• Productivity Increase: Enhanced CSR productivity can lead to better resource allocation, which is estimated to save another $5 million annually.

Using AI for HyperPersonalized Marketing and Sales

A marketing or sales professional in a traditional MVNO scenario begins their day by manually reviewing sales targets and customer feedback. They rely on basic demographic data to segment markets and draft generic marketing communications. This approach often results in untargeted and irrelevant messaging which are reason for unwanted spam calls. Follow-ups on communications are manual, and campaign adjustments are slow, leading to missed opportunities.

In an AI-first MVNO, marketing, and sales teams use AI-driven tools for real-time insights into customer behavior. Basic Sales support and pitch for plans are given by a Virtual AI Agent , Sales trained LLM which can understand the intent of a customer. For a salesperson, the day rather starts with reviewing an AI-generated dashboard that highlights customer preferences and engagement levels and basic sales done by virtual agents . AI tools automate and personalize communication, delivering tailored offers based on customer data. Generative AI can create personalized promotional materials on the spot. Real-time adjustments to campaigns ensure maximum effectiveness. The AI-first approach enables marketing and sales teams to focus on strategic tasks, enhancing their productivity and effectiveness.

Monetary Benefits and ROI:

• Increased Revenue: Personalized marketing can improve conversion rates by 20%. For a 5 million subscriber base, with an average revenue per user (ARPU) of $30, this could translate to an additional $30 million in revenue.

• Marketing Efficiency: Automating and optimizing marketing efforts could reduce marketing expenses by 30%, saving approximately $10 million annually on a typical $30 million marketing budget.

• Higher Engagement: Enhanced customer loyalty could further increase ARPU by 5%, adding another $15 million annually.

Using AI for Dealer Empowerment

Dealers in a traditional MVNO start their day by manually reviewing sales targets and inventory levels. They rely on standard communication channels from distributors for updates, which may not be timely or personalized at all . Customer interactions are based on intuition and experience, with limited support for personalized offers. Administrative tasks and manual adjustments to sales tactics dominate the day.

In an AI-first MVNO, dealers are equipped with AI-powered tools providing real-time insights into sales performance and inventory needs. The day begins with reviewing a dashboard that highlights trending products and personalized sales strategies. AI tools enhance customer interactions by providing real-time recommendations and dynamic pricing offers. Generative AI can simulate promotional materials tailored to individual customers. Continuous feedback loops enabled by AI analytics allow dealers to adjust strategies in real time. AI automates inventory management, freeing dealers to focus on customer engagement.

Monetary Benefits and ROI:

• Sales Increase: Real-time, personalized recommendations can boost sales by 15%. For a 5 million subscriber base, this equates to $45 million in additional revenue annually.

• Inventory Cost Reduction: Efficient inventory management could reduce costs by 20%, saving around $5 million annually.

• Dealer Productivity: Improved dealer productivity and reduced administrative tasks could save another $5 million annually.

Using AI in Network Optimization and Management

Network optimization in standard traditional MVNOs involves manual monitoring and adjustments. I remember those days when we used to analyze call flows and messages to optimize the network. Based on my findings and optimized flow I was able to file patents with improved optimization flows. To date, Network engineers spend a significant amount of time analyzing traffic patterns and making manual changes to optimize performance. This reactive approach often leads to inefficiencies and slower responses to network issues.

In an AI-first MVNO, AI algorithms continuously monitor network traffic and make real-time adjustments to optimize performance. AI tools predict network congestion and dynamically allocate resources to ensure optimal service quality. This proactive approach reduces downtime and improves overall network efficiency. AI also assists in predictive maintenance, identifying potential issues before they become critical. Gone are days when a bug or a process restart takes hours with multiple levels of approvals. An intelligent AI system will first fix the problem and then go around raising tickets etc if required.

Monetary Benefits and ROI:

• Operational Cost Savings: Efficient network management can reduce costs by 20%, potentially saving $10 million annually.

• Improved Uptime: Reducing downtime** can prevent revenue losses estimated at $5 million annually.**

• Predictive Maintenance: Identifying issues before they occur can save an additional $5 million annually in maintenance costs.

Using AI for Fraud Detection and Security in

Fraud detection in traditional MVNOs relies on manual monitoring and rule-based systems. Security teams spend a significant amount of time analyzing traffic patterns and investigating suspicious activities. This approach can be slow and reactive, allowing some fraudulent activities to go undetected. Frauds are a big challenge for Telecom Operators.

AI-first MVNOs use AI to monitor and analyze data traffic patterns in real time. AI systems can quickly identify anomalies and potential fraud, allowing for immediate action. Generative AI can simulate potential fraud scenarios to enhance detection systems even before a human develops. This proactive approach significantly reduces the risk of fraud and enhances overall security.

Monetary Benefits and ROI:

• Fraud Reduction: Improved fraud detection can reduce fraud losses by 50%, saving $10 million annually.

• Operational Efficiency: Automation of fraud detection tasks can save $3 million in operational costs annually.

• Enhanced Security: Better security can enhance customer trust, potentially reducing churn by 1%, and adding $30 million in retained revenue.

Using AI to Do Service Customization and Innovation

Service customization in traditional MVNOs is limited by manual processes and static data analysis. Creating new service offerings or customizing existing ones is a slow and labor-intensive process. This limits the ability to quickly respond to changing customer needs and market trends. The process of Ideation of Service or package to make it live is at times 3 to 6 months. In the current market, it is unacceptable that every 6 months the whole market changes.

AI-first MVNOs leverage generative AI to create new and unique services tailored to individual customer needs. AI tools analyze customer data to identify emerging trends and preferences, enabling the rapid development and configuration of customized offerings. Generative AI can simulate and test new service ideas before implementation, reducing time to market. A Telco TMF-trained LLM, It can also help business and marketing teams to develop and configure services in a simple interactive way.I wrote about this in my previous blog and am happy to see many organizations going this way.

Using Generative AI for Predictive Analytics for Business Decisions

Decision-making in traditional MVNOs or telecom Operators relies on historical data and manual analysis, but most often on Hierarchy. Predicting market trends, customer churn, and the success of new strategies is often slow and reactive. Hierarchy-based decisions are very dangerous for any organization as the Boss is always right attitude takes the team, the organization as well as the Boss down. This approach can lead to delayed responses to market changes, suboptimal business strategies, and missed opportunities for growth and customer retention.

AI-first MVNOs use predictive analytics to forecast market trends, customer behavior, and business outcomes. AI tools can analyze vast amounts of data in near real-time, providing actionable insights that inform strategic decisions. This proactive approach allows MVNOs to anticipate market shifts, optimize customer retention strategies, and implement new business initiatives with a higher likelihood of success. Predictive analytics enable data-driven decisions that minimize risks and maximize opportunities.

Moreover, as analysis comes from a machine, it leads to conductive debates and hence democratic data-based decisions rather than on Hierarchy.

Monetary Benefits and ROI:

• Revenue Optimization: Proactively addressing churn can reduce customer** loss by 3%.** For a 5 million subscriber base, this retention of 150,000 subscribers annually, each worth $600 in revenue, adds $90 million in retained revenue.

• Strategic Planning: Improved decision-making can lead to better investment choices and market strategies, potentially increasing overall revenue by 5%, equating to an additional $150 million annually.

• Cost Reduction: Efficient resource allocation and targeted business strategies can** reduce operational costs by 10%, saving approximately $10 million annually.**

AI for Enhancing the Supply Chain and Vendor Management

Supply chain and vendor management in traditional MVNOs involve manual monitoring and coordination and again biases in favor or against particular vendors. This can lead to inefficiencies, stockouts, and higher costs. Vendor performance analysis is often slow and reactive, making it challenging to maintain optimal inventory levels and negotiate favorable terms with suppliers.

AI-first MVNOs use AI to streamline supply chain operations and optimize vendor management. AI tools analyze vendor past performance and predict supply chain needs, enabling proactive management. AI tools also bring an unbiased view based on data as to what is best for the organization. This ensures timely delivery of products and services, reduces costs, and improves service quality. AI can also assist in negotiating better terms with suppliers based on performance data and market conditions.

Monetary Benefits and ROI:

• Inventory Cost Savings: Optimized supply chain management can reduce inventory costs by 20%, potentially saving $10 million annually.

• Vendor Efficiency: Improved vendor performance and negotiations can save an additional $5 million annually.

• Reduced Stockouts: Minimizing stockouts can prevent revenue losses estimated at $5 million annually, ensuring continuous product availability and customer satisfaction.

I see that the future will be of AI-first MNVOs and Product Vendors

Adopting an AI-first approach transforms every aspect of MVNO operations, from customer service to marketing, sales, network management, and beyond. By smartly deploying AI and generative AI technologies as virtual assisting agents , MVNOs can enhance operational efficiency, improve customer satisfaction, and drive revenue growth. The shift to AI-first operations boosts productivity and effectiveness and side by also positions MVNOs to thrive in an increasingly competitive and dynamic telecom landscape.

For an MVNO with 5 million subscribers, the ROI of implementing AI-first strategies is substantial. The benefits include significant cost savings, increased revenue, enhanced customer retention, and improved operational efficiency.

I am actively researching this topic and developing AI tools designed to enhance organizational productivity and efficiency. If you are interested in exploring how AI can benefit your organization, I invite you to book a complimentary 30-minute consultation session with me to discuss this compelling subject in more detail.