How Artificial Intelligence will help your business Success

Virtual customer assistants (VCAs) is one of the widely accepted use cases of Artificial Intelligence.

Virtual assistants are used to engage with the customers 24/7, across various communication channels like web chat, email, IVR or messaging. You can also look at different types of management software options that can enable a business to easily manage their customer relationships from one software package, for example, look into the likes of what is crm to see how businesses are trying to maintain 100% customer satisfaction by smartly recording and managing customer interactions.

Chatbots are one of the finest examples of virtual assistants being used today. Gone are the days when you interact with a live chat service and get vague responses, clearly indicating that it’s a machine responding to the questions.

Today’s chatbots are smarter and more responsive.

Machine Learning is used for providing personalised user experiences. You must have experienced this in the form of “people you may know” in Facebook and “products you may like” in e-commerce websites.

Basically, it works on the basis of learning with past experiences, very similar to human brain. However, unlike humans, machines can analyse large and complex data. They analyse data, understand behaviour of users through past activities, and then predict the most effective solution to a specific user.

Machine Learning and its algorithms are all about data. In spite of working on so much data, it serves every user personally.

Business applications which require audio inputs for processing can make the most out of speech recognition applications.

Voice response interactive systems like Alexa, Google Translate (mobile app) are good examples of integrating speech recognition into business applications.

Users just don’t want to wait. Speed is one of the crucial elements to deliver a superior user experience. Ever wondered how fast and smart the e-commerce search boxes are to make the customers connect with products on their mind. That is how Machine Learning is improving the user experience, by making the search faster and smarter.

Online and mobile payments are a hot trend in the fintech industry. Moreover, with more companies selling software online than ever before, it is vital that eCommerce platforms have the necessary tools in place to facilitate these sales. Accordingly, you can read more about how this type of software is operated by taking a look at some of the resources on the FastSpring website. However, these payment transfers bring security challenges along with them. Machine Learning models can be trained to detect fraudulent activities, so that monetary transactions can be safeguarded.

Awareness on health and fitness is growing in leaps and bounds. Wearables connected with mobile apps are used by individuals for keeping a record of health issues at regular time intervals. Machine Learning can customise the app functionality in accordance to the data, user’s physical state, and previous health records. Depending upon the results, the app will give recommendations.

In order to develop AI enabled solutions, companies should set up an AI infrastructure and develop their own algorithms to develop applications. However, as a more convenient option, there are many off-the-shelf AI solutions available which you can embed into your business applications.

Off-the-shelf AI solutions, also known as ‘Artificial Intelligence as a Service’ (AIaaS) offer pre-trained algorithms that reduce costs and require less intellect resources. Tech giants like Amazon (Machine Learning at AWS), Microsoft (Cognitive Services), Google (Cloud AI), are already delivering off-the-shelf AI solutions.