Artificial Intelligence

How AI Augmentation is Revolutionizing The Telecommunications Industry

The Telecommunications Industry has moved far beyond merely providing simple voice and data services to adopting AI and AI Augmentation at a rapid rate.

The Telecommunications Industry has moved far beyond merely providing simple voice and data services. The sector is adopting AI and AI Augmentation at a rapid rate as it comes under increasing pressure to provide higher quality services and enhanced customer experiences.

AI Augmentation differs from traditional AI as it does not seek to replace human cognition. It instead uses similar tools and technology to AI but as an enhancement and not as a substitute for traditional understanding.

This synergistic approach has proved invaluable to Communication Service Providers (CSPs) in several ways.

 

AI for Network Optimization

AI-driven technologies have become crucial to the development and optimization of networks in the Telecommunication Industry. Network planning and connectivity benefit from deploying these new tools as CSPs seek to compete in a rapidly changing environment.

AI assists CSPs to deploy networks that are self-optimizing. They utilize advanced algorithms that identify problems within the network. The AI then proactively rectifies these deficiencies with no outside assistance.

Network optimization can be broadly defined in 4 ways:

  1. Network Performance
  2. Quality of Service
  3. Security
  4. Energy Consumption.

AI technology and Augmented AI can assist with all 4, providing CSPs with invaluable tools and insights that allow them to better serve their customers.

This is achieved by the creation of self-optimized networks. These networks are not only self-healing but also greatly improve the customer experience, leading to increased efficiency and customer satisfaction.

 

RPA for Telecommunications

Robotic Process Automation (RPA) is a type of business automation that is based on AI. RPA seeks to relieve the pressure on CSPs by automating the large amount of repetitive, labor-intensive tasks they need to perform.

CSPs often deal with a high number of clients. Their internal processes can be prejudiced by the sheer number of transactions that are completed on their networks. There is also the factor of human error to consider.

RPA can be deployed to allow staff members at CSPs to use their skills in areas where they can add more value and avoid being bogged down in an avalanche of time-consuming and repetitive tasks. RPA can be effectively utilized within a CSP to assist with billing, data capture, fulfillment, and even HR.

RPA, when implemented correctly, not only increases workforce productivity but can also dramatically improve the overall customer experience.

 

Personalized Customer Experience

While it is necessary for CSPs to provide a stable and competitive service, it is becoming increasingly important to provide their customers with a highly personalized experience. Today’s customers are presented with a plethora of options when it comes to choosing a CSP. In order to remain competitive, it is vital that CSPs take their individual customer needs into account.

Slow and inaccurate internal processes often lead to deficiencies in many key areas that can negatively impact the customer experience. CSPs need to make sure that the resources they have at their disposal are deployed effectively and efficiently. AI can help individually assess what a customer requires from the interaction they are having with the CSP that is based on their individual profile.

Some customers may be happy with an explanation while others may require an incentive. An automated system that provides an accurate recommendation can be invaluable.

ModuleQ has developed patented People-Facing AI technology that surfaces personalized customer-centric insights, directly in your existing collaboration platform. This allows for a "white-glove" customer experience that drives growth and customer retention through relationship building. In an article from the Harvard Buisness Review Callie Field, the executive vice president of customer care at T-Mobile said, “If all you ask people to do is bring down their handle time, they can do that. But if you empower them to do more—to think like a small-business owner who is focused on the customer’s happiness and the strategic management of their P&L—they can do that too. And they’ll do it really well if you give them the tools and get out of their way.”

 

Improved Customer Satisfaction/Retention

Customer retention is one of the most important factors to consider when CSPs design and implement their networks and processes. The acquisition of a new client can often be an expensive and time-consuming objective for a CSP. That's why increasing the levels of customer satisfaction is crucial.

Technologies that assist them to do this more effectively have become invaluable as they seek to strengthen their offerings and remain competitive. AI and AI augmentation can be a great way to improve customer satisfaction.

A great example of this is an intelligent virtual agent that is driven by AI.

A system such as this allows a CSP to respond to its customer's requests for assistance more effectively and efficiently. This not only relieves the pressure on the individual staff members at the CSP but also provides the customer with a more agile and responsive service, leading to a dramatic increase in overall customer satisfaction.

This can be combined with speech, emotion, and image recognition to further enhance the customer experience.

ModuleQ has the technology and expertise to design and implement the AI-based technologies a CSP requires to remain competitive in the fast-moving telecommunications environment. They can assist in gaining insight into individual customer needs without requiring manual intervention of any kind.

This improves overall customer satisfaction while maintaining efficiency within the CSP.

 

Fraud Detection

Fraud is a major headache for the Telecommunications Industry. Before the advent of AI Technologies, CSPs had to deal with fraud manually. This was not only inefficient but also led to many fraudulent activities going unnoticed.

By deploying AI-based fraud detection technology, CSPs can not only limit the time it takes to discover fraud, but they can also decrease the overall scale of the problem.

AI makes it easier to identify changes in known fraud patterns through the use of machine learning.

This allows a CSP to create new processes for fraud detection and to adapt existing systems more effectively as changes in fraudulent behavior occur over time.

The detection and mitigation of fraud is vital to the continued success of a CSP. Implementing the appropriate AI-based tools and solutions to combat this has become irreplaceable as fraud continues to increase in severity and frequency.

 

In Conclusion

It is vitally important for CSPs to embrace the changes in technology that are occurring within the Telecommunications Industry. If they do not, they run the real risk of being left behind and unable to meet the evolving needs of their clients.

AI and AI technologies offer some of the best solutions for them to achieve these goals.

The implementation of these technologies can present significant challenges to any business, and it is best to proceed with caution when considering which technology to implement and in which part of the business to do it.

These are not only technological changes but also human ones.

Businesses should consider the abilities and the skills of the people in their organizations to work with these innovative technologies before implementing them.

An implementation plan and skills gap analysis are vital to this.

It is certain that AI and Augmented AI Technologies will become increasingly prevalent across all sectors of the Telecommunications Industry.

CSPs that fail to adapt and implement these new practices are guaranteed to fall behind and become increasingly irrelevant as these technologies mature and grow with time.

 

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