Will incorporating Artificial Intelligence into software applications really boost your business?

Have you ever wondered how Google search clearly understands your query and provides quick results, or how shopping sites display products which you like? It’s not magic, but a set of codes which enable these applications to serve you like a human.

Modern software applications are built with techniques of ‘Artificial Intelligence’ and ‘Machine Learning’. These two are hot buzzwords in the software industry at this time.

Artificial Intelligence (AI) is the concept of machines being able to carry out tasks in a smart way. It emphasises on the creation of intelligent machines which work and react like humans. At the core, AI is training the systems to perform certain tasks, better and faster than humans. 

Machine Learning is a current application of AI based around the idea that we should just give machines access to data and let them learn for themselves. Machine Learning is an important part of AI that gives computer systems the ability to learn with data, without being explicitly programmed. It is the vital force driving the growth of Artificial Intelligence.

There are a number of businesses which have already embraced the power of AI into their applications. For example, face recognition in Facebook, product recommendations on e-commerce platforms like Amazon, etc.

Here are a few ways in which you can use AI technologies to add value to your business:

1. Virtual customer support agents

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.

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.

2. Recommendation and personalisation (Machine Learning)

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.

3.Speech recognition (audio to text conversion)

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.

4. Smart and fast search results

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.

5. Fraud detection and security

Online and mobile payments are a hot trend in the fintech industry. 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.

6. Healthcare and fitness

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.

Developing Artificial Intelligence driven applications

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.

Summing up:

From SIRI / Google Assistant to self-driving cars, AI is progressing rapidly. What AI can do is fascinating and users want it. Integrating AI into software applications and mobile apps is the need of the hour.

Business adopting it will climb the ladders of success and those who don’t will lag behind.

Aarti Chandela Aarti Chandela is a content writer at ESG. With over 3 years of experience in web content writing and blogging, she often writes about topics related to outsourcing, digital marketing, finance, etc. Aarti has interest in the areas of SEO and social media marketing. In her spare time, she loves to cook.