Artificial Intelligence (AI) Will Enable Comeback Of Value Added Services
With AI and big data implementation, telecom companies will know customer much more than anyone else and the more you know, the bigger pie you can take in the business. It's not surprising to see chatbots and voice interfaces as among the most popular use-cases of artificial intelligence in this sector. Companies with huge B2C operations (millions or tens of millions of customers) are most suited to benefit from both text and voice applications, for a number of reasons:
Customer service is a massive expense for any company with over a million customers, and chatbots hold a promise of significantly improving efficiencies.
Companies with massive volumes of incoming customer support requests have the most data available to train chatbot of speech recognition systems, allowing them to "drink in" the huge wave of support and use it as fuel for better interfaces with customers.
DISH Network`s Artificial Intelligence Applications
Over the past year, DISH Network has become the first TV provider to collaborate with Amazon. Looking to improve customer service through the integration of AI technology, DISH has designed a DVR system that is compatible with Amazon's Alexa products.
With the voice based services becoming more prevalent and the day is not far when the phones will be designed to interact with the local application which will control the phone and do everything as per your instruction
To enable functioning, users connect their DISH Hopper DVR system to Amazon's Echo or Echo Dot Alexa devices and adjust settings through on-screen navigation tools. The joint venture allows DISH to provide users with voice-enabled television navigation at no additional charge. Alexa is designed to perceive and process spoken commands with natural phrasing. Examples of typical commands include: "Go to ESPN," or "Find The Voice".
ITU Building a focused group around AI/ML
The International Telecommunication Union (ITU) recently announced the formation of a new focus group to bring more standardization while implementing machine learning and to bring more automation and intelligence to ICT net-work design and management. The objective of this program was to help operators make smarter network with the use of machine learning algorithms and to use network-generated data effectively. These algorithms enable ICT networks and their components to adapt their behavior autonomously and bring more efficiency, security and optimal user experience.
API will be the key for future transaction
With the voice based services becoming more prevalent and the day is not far when the phones will be designed to interact with the local application which will control the phone and do everything as per your instruction. For example, book a ticket, send an email, remind you for various services and you will have similar expectations from your phone or the service provider.
This will enable a number of changes in the applications and services domain and more API based services will be offered by Internet companies instead of web browser based experience.
Operator Network optimization prospective
AI will help operators in moving from old model of operation to a Predictive maintenance and a self-optimized network. AI can also be designed to help reducing the security risks and prevent attackers from attacking the network. It may also offer intelligence and optimal net-work quality by way of automation.