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Artificial Intelligence in Business

Feb.26.2020

 

As the contemporary society is propelled towards the information era, the telecommunication service faces rapid and profound transformations. New tech such as artificial intelligence (AI) will be essential to achieve these transformations, along with the Internet of Things (IoT) and 5G, AI it is one of the most talked about topics in the industry. 

 

What Is Artificial Intelligence?

 

AI is the basis for mimicking human intelligence processes through the creation and application of algorithms built into a dynamic computing environment.source: NETAPP Stated simply, AI is trying to make computers think and act like humansthe more humanlike the desired outcome, the more data and processing power required. Achieving this end requires three key components as follows:

•Computational systems

•Data and data management

•Advanced AI algorithms (code)

 

 

 

Why Is Artificial Intelligence Important in telecom?

 

Today, the amount of data that is generated, by both humans and machines, far outpaces humans’ ability to absorb, interpret, and make complex decisions based on that data. Artificial intelligence forms the basis for all computer learning and is the future of all complex decision making.

 

ABI research illustrates that Artificial Intelligence and Machine Learning are the new hot topic in telco networks and for a good reason: They are sitting on a massive pyramid of diverse customer and network data where Artificial Intelligence (AI) can be used to understand, optimize, and improve business and network capabilities. It could play a significant role in customer Management, Cybersecurity, and Network automation where that can prove to be very effective to telecom operators.

 

Artificial Intelligence Use Cases

 

Applications of AI can be seen in everyday scenarios such as financial services fraud detection, online customer support interactions and mobile service stores. Here are just a few examples:

 

Fraud detection: The financial service uses artificial intelligence in two ways. Initial scoring of applications for credit uses AI to understand creditworthiness. More advanced AI engines are employed to monitor and detect fraudulent payment card transactions in real time.

 

Virtual customer assistance (VCA): Mobile services for subscribers use VCA to predict and respond to customer daily requirements through human interaction. Voice recognition, face validation, fingerprint authentication, are the typical points of interaction in the mobile customer service industry. Higher-level daily requirements to improve the efficiency are rely on the advanced algorithm, which approaches the necessity for AI in telecommunications


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