Artificial Intelligence (AI) is impacting the telecom industry and placing it at the center of the technological explosion. The driver of the growth of mobile and broadband services in the Internet of Things (IoT) era is AI. Artificial Intelligence’s communications service providers (CSPs) are facing growing demands for higher quality service and improved customer service. Telcos are making the most of the vast amounts of data collected over the years from extensive customer bases. The data comes from:
- Mobile apps
- Service usage
- Detailed customer profiles
- Billing information
Telecom companies are using the power of AI to analyze and process the massive volumes of Big Data so that actionable insights, better customer experiences, improved operations, and increased revenue by building new services and products.
Forward-Thinking CSPs Focused on Innovation over AI
Different approaches are considered when implementing AI:
AI is necessary for assisting CSPs as they build self-optimizing networks (SONS). Operators receive the ability to automatically optimize network quality based on regional and time zone traffic information by using advanced algorithms to find patterns within the data, which enables telcos to predict and detect network patterns and antipatterns. AI also allows them to anticipate problems before impacting customers negatively.
AI for Predictive Maintenance
Using AI for predictive analytics over existing historical information, telcos can anticipate future trends including failures and take preventive actions.
- Foresee general failures
- Proactively fix problems with communications hardware
- Anticipate failure on Set-top boxes in clients’ homes, reducing call center costs.
Robotic Process Automation (RPA) for Telecoms
RPA is a business process automation technology, a result of Artificial Intelligence. RPA can add value by:
- Enhance efficiency and reliability of telecommunications functions with legacy software replacing human-intensive labor.
- Allow telcos to manage their back offices more easily, along with the labor-intensive and time-consuming processes (e.g., billing, workforce management, order fulfillment, data entry, order fulfillment, etc.)
Virtual Assistants for Customer Support
Often called conversational AI platforms, virtual assistants have learned to automate and scale one-on-one conversations that business expenses can be cut by as much as $8 billion annually in 2022.
One Use Case. Preventive Maintenance to Serve Customers in Better Ways
A Dutch telco, KPN (Koninklijke N.V.) studies the notes produced by its contact center agents. The insight they accumulate helps them make changes to its interactive voice response system (IVR). KPN also analyzes and tracks customers’ at-home behavior (with permission from their customers), such as switching channels on their modem, signifying a Wi-Fi issue. When identifying the disruption is clear, KPN follows up, which drives tremendous success for technical teams.
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