Artificial intelligence (AI) is no longer science fiction in 2018. The potential of artificial intelligence is clearly understood by early adopters as their business is able to see the impact of AI through increased manpower productivity, and ROI.
By 2021, 40% of new enterprise applications implemented by service providers will include AI technologies-Gartner
Businesses now have become more data-centric and AI is the perfect technology to perform data analytics. The gathered massive information from sources such as social media, is helping enterprises to utilize information to find appropriate business value. This is why artificial intelligence, especially NLP/NLU and machine learning, is integrated with various other technologies such as chatbots and cognitive services to help organizations become more efficient, information-driven, and consistent.
Adding intelligence quotient to chatbot
AI-driven chatbots offer a personalized customer experience, as it gives the power to think and respond like humans. Machine learning and natural language processing are the subsets of AI that makes your chatbot smarter in delivering content that is contextually aware.
Also, a chatbot powered by artificial intelligence is scalable, trainable, reliable, understands the intent of the human better, and as already mentioned, offers a more personalized human-like communication.
An intelligent chatbot integrated with AI (ML and NLP)
- Understand both language and commands.
- Constantly learn from customer interactions to become better at predicting their needs.
- Chat in a similar lke human would do.
- Store information properly and categorize it accordingly on each interaction.
- Analyze information to identify whether it is valuable or not.
How these technologies contribute towards the development of an intelligent chatbot
Chatbot along with Machine Learning can automate the process of learning.
Machine learning is an algorithm which is useful to make a chatbot to read data, learn about it and then decide what to do with it. To put it plainly, if you are integrating ML in a chatbot, you are building a chatbot that has the capability to think and determine from previous experiences.
Chatbot along with Natural Language Processing can understand human language.
Natural language processing is the way for a computer program to interact with people in a language and format that people understand. Using NLP your chatbot can understand what customers are saying, respond to customers in a logical manner and have the ability to perform sentiment analysis (understanding customer's tone and intent). Basically, NLP helps chatbot to interpret human language from various lingo, understand the intent of the customer, and respond to customers, just like humans do.
If you are building a chatbot for your E-Commerce store using machine learning (ML), it will only give your chatbot the ability to think and determine a response based on previous experience. Once your chatbot is powered by artificial intelligence, it will be able to recommend products to your customers based on their previous shopping patterns, and also let your chatbot learn from the history of customers. So, in this way, you are training your chatbot to learn from algorithms. Also, with the help of NLP, your chatbot will be able to understand the customer's language and respond in text format.
Create smart applications with cognitive services
Cognitive services are a collection of AI-enabled APIs. These APIs when integrated with your application will offer smart features like sentiment detection, speech and vision recognition, emotion, knowledge, search and language understanding into their application. To bring AI to every developer and every organization, big brands like IBM, Microsoft, Google and more have introduced this enterprise AI solution. Cognitive Services APIs enable enterprises to quickly add intelligence to their apps, website and, bots and harness the power of AI in solving various business problems.
AI can undoubtedly become the powerful force for disruption as it has delivered substantial value to early adopters. So, adopt AI-enabled chatbots and develop apps using AI-enabled cognitive APIs to drastically improve operational performance, increase customer satisfaction, and save a lot of time as well as money.