AI & Digital Assistants: Telco Propositions & Revenues
|発行||Mobile Market Development Ltd||商品コード||818042|
|出版日||ページ情報||英文 34 Pages
|AI・デジタルアシスタント：Telcoの提案と収益 AI & Digital Assistants: Telco Propositions & Revenues|
|出版日: 2019年04月03日||ページ情報: 英文 34 Pages||
Network operators have been using AI powered chatbots that allow customers to seek answers to a range of fairly straightforward queries for several years. More recently, digital assistants capable of recognising voice commands have been introduced by several operators, but it is the success of Amazon's Echo and other smart speakers that have drawn attention to the technology and the convenience it provides in controlling equipment, ordering goods or services and finding answers to questions.
The main reason for their popularity is convenience. With a simple voice command, users can enable a wide range of actions, such as playing music, setting thermostat temperatures or booking restaurants, without having to break away from what they are doing to deal with the task, or at a minimum, pick up a smartphone and navigate the apps and menus. Although smartphones have transformed users' ability to access information and carry out numerous tasks, questions and commands using speech are even easier, and fit better with most people's lifestyles. Voice-based AI is appealing because it offers people the ability to communicate in a way that is natural to humans, without the need to type or swipe. However, developing and implementing a system that can interpret free-form speech with a high degree of accuracy provides considerable technical challenges, given the range of variations in wording, phrasing and pronunciation that they must be able to handle.
Nevertheless, significant advances in natural language generation (NLG) and natural language processing (NLP) have allowed dramatic growth in the availability and uptake of intelligent digital assistants such as Amazon's Alexa. The technologies that power digital assistants require large amounts of data which feeds artificial intelligence platforms including machine learning, natural language processing and speech recognition platforms. As the user interacts with the virtual digital assistant, AI programming uses sophisticated algorithms to learn from data input and become better at predicting the user's needs.
Currently digital assistants are usually limited to relatively simple tasks such as adding tasks to a calendar, providing information that would normally be searched for in a web browser, or controlling and checking the status of internet connected devices, including lights, cameras and thermostats, but their ability to handle more complex tasks is increasing.
Their use can save considerable amounts of time for both operators and their customers. Calls can be answered almost immediately, without the need to wait for an agent to be available, and straightforward queries can be answered more rapidly than with human operators. An operator's agents can then be redeployed to handle the more difficult queries. This combination of digital assistants and human agents has been shown to improve customer satisfaction with services. The use of voice further improves customer perceptions. In addition the number of agents required usually falls, providing opportunities for cost savings by operators.
Network operators have increased use of AI to support customer service in recent years. Over the past two years major network operators - including Deutsche Telekom, Orange, SK Telecom, Telefónica and Vodafone - have started to introduce their own smart speakers. Most recently Vodafone has been using digital assistants to handle sales of prepay services, with some success in terms of increasing sales. Many of the network operator systems also interwork with Alexa and Google Assistant, and some are available as skills to work on Alexa.
This report provides an overview of developments and provides examples of the activities of major operators in the field.
This report consists of six sections. Following the Overview and Introduction they comprise the following sections: