Introduction to ChatBot :
A chatbot system replicates a conversation (or a chat) with a user using messaging services, websites, mobile apps, or the phone by utilizing conversational AI (artificial intelligence) technology which allows people to have a dialogue with computers to ask questions or troubleshoot problems, etc. It performs live chat operations in response to user interactions using rule-based language applications (A program that is composed of a set of rules that are used for making decisions). Why must there be a need to build these chatbots? The answer to it is very simple to communicate with customers directly, via SMS, Facebook Messenger, Kik, Slack, and Amazon Echo so that there is no need for humans to be active 24/7 waiting for user's dialogue.
However, when they were first developed, bots lacked the capability for sophisticated interactions. The development of chatbots has advanced significantly in recent years. The past and future of chatbots are both fascinating. Let's go over everything that chatbots have been, can be, and will be in the future.
History- When and where did it start?
The term "chatbot" means a conversation that is made possible by bots. As a result, this term has two parts: chat, which denotes conversation, and bot, which denotes the "computational" component.
One of the early examples of chatbots in action was the computer program ELIZA, which was created in 1964. ELIZA was able to identify keywords and key phrases (inputs) by using Natural Language Processing, a technology that enables computers to comprehend human language. It was implemented with simple pattern-matching techniques such that if it was told that "My sister hates me" then the response to it was "who else in your family hates you?". ELIZA was soon succeeded by an 'intelligent' version. This one was smarter in the sense that if ELIZA could comprehend human input, PARRY, a newer intelligent version of ELIZA could impersonate a human! PARRY, created by Psychiatrist Kenneth Colby, was able to imitate a patient with schizophrenia.
More innovations continued to emerge in order to outperform older, outdated chatbots. And the world quickly moved on to a time when chatterbots could be freely used by the general public. A.L.I.C.E (Artificial Linguistic Internet Computer Entity) or Alice is the first and most well-known of these chatbots. It was the most powerful NLP chatbot of its period, receiving the Loebner Prize three times!
interesting fact: If you've seen the Oscar-winning film "Her," it's fascinating to know that A.L.I.C.E served as inspiration for the screenplay.
Present- where we are right now:
Businesses from a variety of sectors were now using bots on a global scale. chatbots are now more intelligent and capable of deep and individualized discussions. Now, based on their interactions with humans, Chatbots could adapt and learn. They could now quickly handle large amounts of data, retrieve information, process information, and quickly provide the correct output or response. In a consumer environment, more people are using messaging apps, which has increased chatbot adoption. Consumers now mainly depend on a chatbot to communicate with and interact with their favorite brands, solve simple problems, buy highly personalized products based on their preferences, and stay up to date on the newest sales and discounts on their favorite products!
Business Insider claims that in 2018-19, messaging applications replaced social media sites. See the accompanying graph for statistics and data on worldwide monthly active users.
Average time spent per day on mobile messaging apps by adults in the USA.
This was published by L. Ceci. In 2019, U.S. adults spent an average of 20 minutes per day with mobile messaging apps. This engagement is projected to increase to 24 daily minutes in 2020.
Today's businesses use chatbots for several purposes, and the applications vary from sector to sector and job to job. Additionally, chatbots have many advantages, such as improving customer experience, increasing employee productivity, automating repetitive duties, cutting expenses, and streamlining administrative processes. As I have already mentioned use cases of chatbots in my previous blog "Chatbots and their recent Trends", here are a few more use cases:
Chatbots in today’s enterprises:-
Today's Enterprise Organizations use chatbots for a wide range of purposes, and the applications vary from sector to sector and function to function. Additionally, chatbots have many advantages, such as improving customer experience, increasing employee productivity, automating repetitive duties, cutting expenses, and streamlining administrative processes. Nowadays, businesses use chatbot builder platforms to efficiently create, deploy, manage, and teach AI chatbots.
IT Helpdesk Chatbots:-
Many businesses are using IT helpdesk chatbots to speed up reaction times, increase productivity among support staff, automate IT workflows, and provide on-demand access to service-related information. By making the entire process less labor-intensive, complex, highly interactive, and expensive, the use of chatbots can help with your IT help center challenges. Your IT help desk staff can concentrate on more difficult and important tasks if you have a chatbot available to address basic questions asked by your employees in real time. For example, MyGov Corona Helpdesk is an official Government of India chatbot developed with the intention to access reliable information about coronavirus.
Using chatbots in HR:-
One of the most widely used applications for chatbots is human resources. Chatbots for HR automate processes for the entire employee life cycle. Employees can use bots to perform duties like requesting leave or giving an appraisal, as well as to ask simple or complex HR questions. Chatbots have effectively decreased HR expenses in all phases of the employee life-cycle and streamlined the entire process, regardless of the task at hand, such as talent management, onboarding, employee engagement, or offboarding. Phia chatbot by peopleHum Built on the Engati platform comes with its API (application programming interface - rules that enable different applications to communicate with each other) integration module, which makes it easy to hook into the employee information system.
Statistics On the Adoption Of Chatbots :
In 2019, there were over 40 million active businesses messaging people across the globe, exchanging over 20 billion messages each month. (Messenger News)
Chatbots are expected to cut business costs by $8 billion in 2022 – (Juniper Research)
In 2021, conversational AI-first was adopted by the majority of enterprise IT – (Gartner)
in 2021, 50% of enterprises have spent higher on chatbot creation than on mobile app development. – (Gartner)
Future: Where we are going:-
The future of bots is intriguing as chatbot technology develops further. Here are some significant patterns to keep an eye out for:
Chatbot-RPA integration:
By merging the strength of automation from RPA(robotics process automation) which mimics tasks of human workers like extracting data, filling in forms, and moving files, and cognitive intelligence (generating knowledge through existing information) from chatbots, businesses are elevating the experiences of their customers and employees. Chatbots can reach legacy business systems without modern APIs. Bots have the ability to instruct RPA robots to carry out complicated tasks without routing to a human agent, which boosts output. In 2021, the RPA market was valued at $1.89 billion, according to a Grand View Research report, and is forecasted to increase by more than 38 percent year over year until 2030.
Voice bots:
According to Gartner, voice interactions will account for 25% of all staff interactions with applications by 2023, which was just 3% in 2019. Chatbots won't just have text-based user interactions in the future. Voice bots will be used for a variety of business applications, including conversational BI(conversational business intelligence), IT helpdesk, meeting scheduling, etc., as AI-powered speech-to-text and text-to-speech hosted services have come up. An example of a voice chatbot is amazon echo well known as Alexa which responds to the user when the user says "Alexa...", AI timely, etc
Chatbots will behave more like people:
As important chatbot components are like NLP(natural language processing), Machine Learning(the technique that teaches computers to learn from experiences), sentiment analysis which means understanding the emotions of the user from incoming messages, etc., when they progress, chatbots will be able to have much more complicated conversations, just like people do.
Perhaps in the near future, your chatbot may remind you of the planned sales meeting for the day. Soon, a smart speaker may be used to place your order at an eatery. Future scenarios might involve machines conversing with one another. Next, what? We are left to speculate.