Artificial Intelligence is the replication of human intelligence in computers, while Machine Learning refers to the ability of a machine to learn using large data sets instead of hard code rules.

We can say, ML is an application of artificial intelligence (AI) that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning (ML) focuses on the development of computer programs that can access data and use it to learn for themselves.

One area of business that stands to benefit from machine learning is Customer Service.

AI technology is giving companies the ability to build a deeper and more nuanced view of their customers. That deeper knowledge enables companies to offer a more useful and valuable service to individual customers at scale, and deliver customer experiences that are far smoother and more pleasant than was previously possible.  

Machine learning is making fundamental changes to how businesses and clients interact, with increasingly advanced artificial intelligence giving companies new options for offering customers support, information and assistance.

AI is not limited to companies we typically think of as having huge research-and-development budgets like Google, Facebook and Microsoft. In reality, machine learning is already helping thousands of companies run their business more efficiently.

How is Machine Learning (ML) changing customer service?


Eliminates Business Marketing Waste: 
 
Effective business marketing reaches its audience and creates conversions. Thanks to machine learning, computers are capable of tagging, bundling, identifying and recalling more complex pieces of information. Machine learning has the potential to reduce much of marketing's imprecise nature. Using behavioural data, marketers can target their audiences in an efficient way that greatly improves the likelihood of converting shoppers to customers.

 “The 7 Areas of Marketing Waste”
http://work911.com/planningmaster/planningarticles/7areasofmarketingwaste.htm
 
It opens the door to Marketing Forecasting:

By allowing your business to effectively analyse customer data, based on trends and consistent purchase patterns. Adopting AI for marketing purposes offers decision-makers something more concrete: the overwhelming possibility to give customers what they want before they know they want it. Thanks to machine learning developments, computers can analyse and predict customer behaviour, allowing you to anticipate and prepare for different problems and scenarios.

Machine learning enables your business to learn details about your customer on a micro-level based on macro-level data collection. This allows you to provide more thorough support, anticipate needs and questions and identify weaknesses in your customer service.
                             
ML use Sentiment Analyses to improve business:

Wikipedia defines “Sentiment analysis (sometimes known as opinion mining or emotion AI) as the use of natural language processing, text analysis, computational linguistics and biometrics to systematically identify, extract, quantify, and study affective states and subjective information.”

Machine Learning uses Sentiment Analyses, the process of training a computer to identify sentiment within content through Natural Language Processing (NLP),  to structure marketing content so marketers know what to say and how the audience is likely to react. A great example is Twitter, where marketers can monitor social chatter to see what’s resonating with a specific target audience. Brand specialists and copywriters then can tweak ads immediately in response to comments and trending replies. This brings the right message to the surface.

Reduces business costs: 
 
One of the outcomes of implementing AI is the freeing up of time for the human employees. This allows those employees, who have implemented AI systems, the time to train others, and thus help other departments implement similar AI technologies. These employees are changing from becoming the people who are running a particular process or undertaking particular activities to people who are now helping the rest of the organisation make use of AI technologies.

Machine learning can help reduce marketing expense as it requires far fewer people to be involved. Drastically cuts communication costs, as a majority of customers can be kept updated on offers via automatic emails, scheduled social-media posts and online ads or other content.

ML also allows a computer to predict what problems a customer will have based on data they input; help identify the problem more accurately and provide more customised, detailed advice on how to solve the problem. This gives customers greater freedom to solve problems themselves without needing a customer service representative.

Furthermore, customers prefer information to be accessible 24/7, rather than just during business hours and with AI and ML, 24/7 it’s never a problem.

There is no doubt ML reduces the amount of labour employees need to do and the amount of low-level tasks they have to take care of, making companies more efficient and customer services more streamlined, but overall, this kind of technology will save businesses a huge amount of money.


Although it is already in use in thousands of companies around the world, the biggest opportunities have not yet been tapped. The effects of AI will be magnified in the coming decade, as manufacturing, retailing, transportation, finance, healthcare, law, advertising, insurance, entertainment, education, and virtually every other industry transform their core processes and business models to take advantage of machine learning.
 
Would you like to know how Artificial Intelligence(AI) and Deep Learning(DL) works?
Here’s a quick guide for everyone.

https://medium.freecodecamp.org/want-to-know-how-deep-learning-works-heres-a-quick-guide-for-everyone-1aedeca88076

The Business of Artificial Intelligence.
https://hbr.org/cover-story/2017/07/the-business-of-artificial-intelligence