As Artificial Intelligence (AI) and machine learning are ubiquitous, we will soon be struggling to avoid using the benefits that any industry can offer them. Telecommunications is one of the fastest-growing industries, as well as using artificial intelligence and machine learning in many aspects of their business, ranging from improving the customer experience to improving operational reliability. The world’s largest telecoms rely on artificial intelligence and machine learning in many ways. Here are some of the most common applications.
Customer service and customer satisfaction
Almost every telecom major uses artificial intelligence and machine learning to improve its customer service by using virtual assistants and chatbots. Telecoms receive a large number of support requests for installation, installation, troubleshooting, and maintenance. Virtual Assistants automate and scale responses to these support requests, which dramatically reduces business costs and improves customer satisfaction. In one example, customer satisfaction improved by 68 percent after Vodafone introduced its chatbot TOBi.
As a gatekeeper, chatbots analyze requests, learn to guide and raise customer queries if needed, identify sales opportunities and alert the customer to other products and services that are of interest to them, and manage most of them without human intervention. AT&T, Verizon, Comcast, and every other large-scale telco uses AI for better customer service.
Thanks to artificial intelligence and machine learning, the ability to provide speech and voice services such as chatbots is available. Not only is it used in chatbots, but it also extends service offerings such as Comcast’s XI Talking Guide, which “speaks” network names/time slots, shows titles and helps users navigate through their television options. The company’s voice is useful for people with remote disabilities and those who “want to search” by their voice rather than pressing buttons on the remote.
AI can help identify and respond to telecom issues and propose the right service based on analyzing customer data. This helps Intel develop knowledge of historical information and ways for personalized service companies to develop better products and services and market them to customers when they want them.
Improve Predictive Maintenance and Network Optimization
The most important way to give customers what they want is to avoid disruptions to telecoms. Improves customer satisfaction despite the behind-the-scenes use of AI and machine learning. Data-driven insights help companies to monitor equipment, learn from historical information, ate equipment failure, and fix it in advance.
Another important aspect that helps with AI is network optimization. The Self Organizing Network (SON), fueled by Artificial Intelligence, helps networks adapt and rebuild networks based on current needs. It is also useful in designing new networks. Because AI-enabled networks can self-diagnose and self-optimize, they are more efficient at providing consistent services.
Robotic Process Automation (RPA)
Considering the size of the customers, any individual telecom company deals with on a daily basis, every step of every interaction opens the door to human error. By automating business processes through robotic process automation, repetitive and rule-based operations can be more efficient; they are more accurate. In a survey by Deloitte, telecom, tech and media executives confirmed significant investments in cognitive technology, with 40 percent saying they enjoyed “substantial” benefits, and three-quarters of them believe that cognitive computing can “significantly change” their organizations.
Fraud detection
Machine learning algorithms are crucial in detecting fraudulent activities such as theft or duplicate profiles, illegal access, and more. These algorithms know what “normal” functionality looks like, so anomalies can be detected from data sets larger than human analysts to provide an almost real-time response to the activity that needs to be investigated.
Data-driven business decisions: Predictive analytics
Telecom has immense data from customers. With the use of AI and machine learning, telecoms can gather meaningful business insights from this data so they can make faster and better business decisions. Crunching data through AI helps customer segmentation, customer churn prevention, customer life expectancy-value, product development, improving margins, cost optimization and more.
Ultimately, Artificial Intelligence and Machine Learning have enabled the telecommunications industry to gather insights from their vast data sets, solve problems, manage day-to-day business more efficiently, and provide better customer service and satisfaction. The industry provides us with a great example of how adopting AI and machine learning is not beneficial for business; It is essential to the survival of each company and its ability to compete with competitors.
The future of retail looks dire, as more brick-and-mortar stores close their doors.
U.S. retailers have announced 8,558 store closures so far this year, with total U.S. store closures reaching 12,000 by the end of 2019, Cordite Research reported Friday.While the Internet and automation are usually responsible for these closures, the same technology could be a solution for physical store locations, said Paul Winsor, general manager at Data Robot.“If retailers want to stay open at the current stores they operate in, my recommendation to them is: Do they understand the changing habits of those customers, and how are they shopping with them, in those places?” Said Winsor.“To survive in a tough, tough retail market, you have to start your business and make predictions based on learning from your historical data,” he says.
Technology is around to help companies understand their business from a data perspective,” says Winsor.
“Data is not as personal and accurate as machine learning can help you.”To make predictions in the past, retailers look at daily and weekly transaction data and draw conclusions from it, Winsor said.As technology has evolved and convenience has become a priority, online stores have become the primary way to shop.
If retailers refuse to grow and adapt to emerging retail infrastructure, they will inevitably fall behind.AI helps retailers in three ways“With AI, we are dealing with machines that can simulate intelligent behavior or simulate intelligent human behavior, that is, sense, reason, action, and adaptation,” said Altimeter lead analyst Brian Solis.
“One of the most popular ways that leading brands use AI today is machine learning.”“The difference is that with machine learning, systems can differentiate models from pure data sets, and with the right management, learn from those data to predict and predict results and improve performance over time,” Solis says.
In 2016, the calculable worth additional by the agriculture business was calculable at but one percent people GDP.
Factors like global climate change, increase and food security considerations have pushed the business to hunt a lot of innovative approaches to safeguard and improve crop yields.
As a result, AI is bit by bit evolving as a part of the technology evolution of the business.In this article we have a tendency to explore the applications of computer science to know current and rising trends for business leaders, and gift representative samples of common applications.Artificial Intelligence within the Agricultural business - Insights Before:Based on our analysis, the foremost common applications of AI in agriculture make up 3 main categories:Agricultural robots: - corporation’s area unit developing autonomous robots to perform the required agricultural tasks, like harvest crops and fast quicker than human labor.
Crop and Soil observation: - corporation’s area unit developing laptop vision and deep learning algorithms to method knowledge compiled by drones and / or software-based technology to watch crop and soil health.Predictive Analytics: - Machine learning models area unit being developed to find out and predict numerous environmental impacts on crop yields like global climate change.Blue watercourse Technology - Weed management:The ability to regulate weeds may be a high priority for farmers associate degreed an in progress challenge as weed killer resistance becomes a lot of common.
per a quest study conducted by the Weed Science Society of America on the impact of uncontrolled weeds on corn and soybean crops, annual losses to farmers area unit calculable at $ forty three billion.
Companies’ area unit exploitation automation and artificial intelligence to assist farmers realize a lot of economical ways in which to safeguard their crops from weeds.
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In recent years, the top, Artificial intelligence companies in Bangalore such as Naspers, KDC and IBM have been expanding their R labs in India, China, Japan and Europe.
Companies like IBM and Yana are rapidly expanding into India and are providing a wide range of artificial intelligent solutions across a wide range of industries including financial services, transportation, consumer protection, energy, government and manufacturing to name a few.
The best companies in the world such as IBM, Cisco and others are also opening offices in the Asian region to further increase their presence in India and Asia.
As the technology becomes more developed and is made available to more consumers, then demand for this software will increase exponentially.
Companies that specialize in artificial intelligence research and development now have a global customer base.
Many top colleges and universities in India are also churning out software engineers, computer science professionals, and robotic engineers who are eager to find a job in the United States or Canada.
Not all heroes wear capes, well, as far as I know, Artificial Intelligence can't!
AI has the power to tackle some of the world's social problems too (the real heroes are the masterminds who thought of AI in the first place).
For example: helping the blind by directing them, diagnosing cancer and many many more.
People are just learning to use AI and the possibilities are vast.
Which is why interest in AI has dramatically increased in the past few years.
And Google has taken this social initiative naming it “AI for Social Good”First of all, what is AI?
