Transforming Telco: AI in Telecommunications

However, telcos also look set to become one of the biggest beneficiaries of nascent agentic AI technology, with customer service support just one of many AI-related use cases for the sector.

This new era of AI promises a wide range of benefits for telcos – including significant reductions in operating costs and increases in issue resolution efficiency. 

The vast majority of telcos—84%–leveraging generative AI have already cut costs in their customer service operations, according to McKinsey data.

Comparison of AI use cases in Telco

Here at Neurons Lab, based on our previous work with telcos and our research, we have identified many impactful AI-led use cases. The following diagram plots these use cases from low to high potential business impact, alongside the level of complexity involved in implementing such a solution:

In this article, we’ll explore how AI can support these different telco use cases and the benefits, in order of projected business impact.

Agentic AI for customer service

Automating a portion of customer interactions can significantly improve customer satisfaction and reduce operational costs, through:

• High-quality service 24/7
• Providing immediate support
• Anticipating customer issues and proactively offering solutions
• Reducing wait times
• Resolving problems before they escalate

There remains a human-in-the-loop to oversee processes, but there is a big opportunity to increase revenue by offering more self-service. 

AI agents are the most cutting-edge technological solution available to achieve these goals. Compared to standard chatbots, AI agents can make rational decisions based on perceptions and data to complete self-determined tasks in the most effective way:

1. The difference between traditional chatbots and AI-powered chatbots:

Classical chatbots operate on rigid, rule-based logic, which works well for simple FAQs but fails in nuanced situations. Traditional chatbots use decision trees or keyword matching to respond, which limits flexibility in handling complex queries.

AI chatbots, enriched with natural language understanding and emotional intelligence, interpret user intent and context dynamically, enabling smoother, context-aware conversations that enhance customer satisfaction and retention. 

2. Agentic AI Systems are more advanced than AI-powered chatbots/AI Assistants:

While AI chatbots excel at engaging in conversation and answering queries, they lack the ability to take action.

• An agentic AI System combines conversational AI with process automation, enabling them to execute workflows, integrate with backend systems, and resolve issues autonomously, offering a full-service capability.
• The end-to-end process would include understanding customer needs and executing actions, such as updating account details, placing orders, or processing refunds, making interactions more seamless and efficient.
• An AI agent operates within narrowly defined parameters, executing tasks through explicit instructions and integrations.
• Agentic AI Systems are designed with autonomy and adaptability, leveraging advanced reasoning, contextual understanding, and multi-modal learning to handle evolving challenges and self-improve over time. This makes them capable of managing broader, less predictable tasks.

For a detailed case study, check out our guide to using multi-agentic workflows including a telecom scenario:

Bespoke agentic AI solutions can engage customers with human-like understanding and emotional intelligence far beyond the capabilities of traditional chatbots. Many companies’ chatbots lack empathy, proactivity, contextually accurate support, and the intelligence to handle complex queries.

LLM-powered AI agents can tailor support to individual customer profiles and preferences, anticipating their needs then guiding them proactively towards an efficient issue resolution.

AI agents can provide 24/7 multilingual operations support with minimal intervention, handling complex problems but also seamlessly escalating cases to customer service representatives when necessary.

They offer consistent service quality, reduced wait times, and automated handling of routine queries as part of a scalable customer support infrastructure. This is due to their access to user data, conversation history, purchase history, and so on.

With technologies like chatbots and virtual assistants already well-established, AI agentic implementation is relatively straightforward as opposed to starting from scratch.

Projected benefits of leveraging agentic AI for customer service include:

• 80% reduction in operational costs and response times

• 30% increase in successful cross-sells and upsells

• Increased customer satisfaction and loyalty, improving lifetime value

Learn more about our Agentic AI for Customer Service offering.

Other high impact Telco business use cases

Moving on from customer service, these use cases could achieve a similar impact in other areas of telco business operations:

We have divided these use cases into industry-specific and cross-functional ones. The latter are applicable across different departments and functions.

Industry-specific use cases:

Network operation center (NOC) support

• Enhancing an NOC with agentic AI can lead to more efficient monitoring and quicker incident resolution with 24/7 operations support requiring minimal intervention.
• Projected* benefits include a 53% reduction in operational costs, a 65% reduction in escalations, and a 55% improvement in first-time resolution rates.

• Agentic AI can automatically diagnose incidents and recommend solutions, lowering the mean time to repair (MTTR) from 4-8 hours to 15-30 minutes on average.

Our agentic AI for NOC solution offers incident diagnosis, resolution recommendations, and performance optimization through:

• Intuitive conversation-based interface replacing complex GUIs
• Unified way to access and correlate data from multiple sources simultaneously with real-time data processing
• Automated ticketing and escalation
• Detailed explanations bridging the gap between senior and junior experts
• Real-time monitoring, alerts, and resolution path recommendations with vendor-specific resolution procedures

Learn more about our Agentic AI for NOC offering.

* These projections are based on estimations and forecasts, not previous examples

Network traffic analysis, management, and optimization

• AI-driven planning models can simulate and predict demand, helping telcos make data-driven decisions on infrastructure placement, upgrades, and expansions.
• This leads to reduced CAPEX through better resource allocation, optimized bandwidth utilization, future-proof network planning, and a potential competitive advantage.
• Operational benefits include real-time traffic optimization, predictive capacity planning, and automated load balancing.

Cross-functional use cases:

Churn prevention

• AI can provide early warning systems for lapsing customers, targeted intervention strategies, and personalized retention programs.
• It can identify churning customers by different parameters, segmenting them into groups and suggesting plans to retain them
• Predictive models can significantly improve customer retention strategies, directly improving revenue.
• This in turn reduces customer acquisition costs and increases the lifetime value by improving loyalty 

Medium impact Telco business use cases

These use cases have the potential for considerable business impact, also requiring varying amounts of time and effort to achieve.

Cross-functional use cases:

Tailored marketing

• GenAI-supported marketing can provide several operational benefits including automated campaign generation, real-time optimization, and personalized content creation.
• More personalized and relevant marketing provides a better customer experience, which tends to increase engagement and conversion rates. For example, it can more accurately recommend similar products to something a customer has bought recently.
• Leveraging your existing current marketing and customer data, GenAI can help decrease the time required on new marketing campaigns, improving ROI.

Employee onboarding, training, and assistance

• Handling routine and fixed onboarding processes, GenAI can standardize the knowledge transfer process and ensure consistency.
• GenAI can provide personalized learning paths and scalable training programs, tailored for individuals to improve their personal skills development.
• Saving time for HR to focus on more strategic initiatives, such technology can also handle routine ad hoc queries and requests from employees.

Software development and testing

• Serving as a coding copilot, GenAI can automate code generation as well as predict software bugs and provide continuous testing.
• It leads to faster software development cycles, reduced testing costs, and higher code quality.

This improves time-to-market, software reliability, and innovation capabilities. For more details, check out this case study on streamlining blockchain code development with a unique agentic AI copilot:

Industry-specific use cases:

Network security, planning, and design

• Involving complex modeling and data analysis, GenAI has the potential to optimize infrastructure investment. Also, reduce planning costs, and provide better ROI on network deployments. 
• Strategic value includes improving network security and market coverage. Operational benefits include faster deployment planning and optimized resource allocation.

Cell tower site selection

• Leveraging complex geographical data analysis techniques, informing site selection using GenAI can improve network coverage. It can also enhance service quality, and reduce deployment costs.
• Operational benefits include automated site analysis, optimal configuration planning, and regulatory compliance checking.
• However, here GenAI is reliant on other specialized tools for geographical data analysis.

Lower impact Telco business use cases

While these GenAI use cases for telco currently have a relatively lower business impact compared to the others mentioned above, they are still valuable. 

They range from quicker, more tactical tasks to other use cases with the potential to deliver greater business impact in the future with more evidence.

Reports automation

• This saves time, reduces manual effort, and decreases operational costs – technologies for automated reporting processes led by GenAI are already widespread
• This approach can also automate updates, reduce manual error, standardize reporting, and improve transparency – leading to better decision support processes
• However, this use case may not directly drive revenue in Telco

Market segmentation

• More insightful customer segmentation allows for more targeted marketing, increasing outreach efficiency – improving market understanding, customer targeting, and product positioning.
• Operational benefits include automated segment identification, dynamic updates, and suggestions for personalized targeting strategies – potentially leading to higher conversion rates.
• However, it requires a level of customer insights and behavior analysis capabilities that some organizations may need to develop further before incorporating GenAI.

Product development innovation

• Driven by GenAI’s ability to analyze and summarize information quickly and in vast quantities, this could lead to new revenue streams and competitive advantages.

For now, more evidence is required before we can say for sure that this approach will lead to high business impact product development innovations, but it is certainly one to watch.

Final Thoughts – AI Use Cases in Telco

While every industry can benefit from adopting GenAI, telcos are particularly well-placed to capitalize.

Rapid developments in agentic AI promise significant potential to optimize telco customer service operations.

According to a further McKinsey projection, telcos could achieve a 13% increase in operating profit margin on average, among the most lucrative of the industry forecasts:

GenAI in general supports wide-ranging telco use cases in other areas too. The ever-improving technology can enhance business practices – from state-of-the-art network security, to marketing and HR activities, and almost everything in between.

To discuss in more detail how GenAI-powered solutions can support telco business operations, please get in touch.

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About us: Neurons Lab

Neurons Lab is an enterprise AI consultancy that provides full-cycle AI transformation—from identifying high-impact AI applications to integrating and scaling the technology.

As an AWS Advanced Tier Services Partner and Generative AI Services Competency holder, the team has successfully delivered tailored AI solutions to over 100 clients, including Fortune 500 companies and governmental organizations.