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Chatbots Driving Enterprise Value in 2018

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Chatbots Driving Enterprise Value in 2018

Enterprises, being massive organizations, need chatbots. Read on to learn more about how chatbots can drive value to enterprises.

· AI Zone ·
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There has been a lot of buzz around chatbots and how they help businesses — especially eCommerce websites. But little has been spoken about how chatbots can help enterprises.


What Is an AI-Powered Chatbot?

A chatbot, or simply a bot, is a computer program that converses via textual or auditory methods. Chatbots can hold intelligent conversations between people, internet-enabled things (IoT devices), and digital systems.

Chatbots converse within a coherent structure using a dialog system. This system can be used for many practical purposes, which include information acquisition and customer service.

An AI-powered chatbot is a smarter version of a conventional chatbot. These smart chatbots use NLP (natural language processing) and ML (machine learning) to understand context as well as intent and provide a near human level communication or more natural feeling answers.

An AI-powered chatbot is:

1. Trainable

2. Dependable

3. Scalable

4. On-brand

Chatbots ease the communication and collaboration experience by combining person-to-system and person-to-person communication. They do this by completely removing the system interface that we are so used to. Chatbots replace our incongruent interactions with conversations, which is more natural.

In this digital era, chatbots allow for systems that may be written in various programming languages to connect with each other.

Chatbots simplify workflows. They do this by automatically initiating and/or completing action items in the workflow, items which otherwise would require human intervention — meaning manual exchanging of data between various systems. As chatbots can initiate processes by themselves, they have laid the foundations for a seamless human-to-machine collaboration. This collaboration is so simple that we humans can have a dialog with chatbots now.

Humans, from the moment they are born, start learning to understand language, intent, and emotions. These are the three basic elements that make our conversations interesting. Traditionally, bots could only understand language.

But, with the advancements in technology —specifically, NLP — AI-powered chatbots are now able to understand both language and intent. Emotions may take a few more years.

One the main challenges that chatbots face is trying to understand the several ways in which humans express themselves using natural language. In addition to that, we use slang, acronyms, etc. to converse with others. Some of us even use images to communicate with others!

Given that there are so many components deeply rooted in expressing ourselves, how could a chatbot (more specifically a piece of software) decode what we are expressing?

Natural language processing (NLP) is an essential input component that helps chatbots understand what we express. Using NLP, chatbots can translate what users are saying and present the answer in their (users') preference.

To explain, if a user asks a chatbot about the weather, it immediately analyses the question for keywords, which in this case is "weather," and responds with the current temperate. NLP allows chatbots bot to process syntax, semantics, and grammar from a request and turn it into a system command.

Key Characteristics of an NLP Engine

Programming code is specific. The way we communicate or converse with each other is wide-ranging. This disparity generates the need for NLP engines to better understand human speech. Here are a few key features that NLP engines possess, which enable them to provide a satisfactory conversation with users:

  • Input analyzes: As mentioned earlier, chatbots search for keywords. Regardless of the placement of the keyword, the NLP engine understands subject-verb-object.
  • Synonyms: Humans have a wide range of words in their vocabulary. The NLP engine maps keywords with their corresponding synonyms, which triggers intent recognition.
  • Interactiveness: The NLP engine is proficient in responding interactively with the user.

The Rise of AI-Powered Chatbots

We live in a digital age!

We currently exist in an era that is overwhelmed with information. Almost everything we do is either tracked or stored digitally. No, we are not talking about governments spying on us, but the notion that we generate more data than we consume.

With so much information, accessing crucial data points to ease our lives has become a challenge. There are so many systems available that can draw up data from the far corners of the world (or enterprise) but none of them can provide us with insights that would be useful to us to make informed decisions.

Although most of these systems are robust and complex, we humans need to adapt to their style of functioning — meaning we need to learn new commands to get the information we need. Herein lies a technological paradox, which is only amplified by digital complexity.

Due to the digital complexity and overload of information, businesses and enterprises are struggling to connect with their users and/or customer base. Employees are having to work harder and longer to create that extra value for customers.

How Does this Complexity Affect Enterprises?

Challenge #1: Customer Engagement

Customer engagement (CE) is the emotional connection between a brand and a customer. Customers that are properly engaged tend to promote more, buy more, and demonstrate more loyalty. For enterprises, providing a high-quality CE is crucial for survival in this digital age. CE should be a key factor in any enterprise's customer engagement strategy.

Lately, however, there has been a void in CE and customer experience (CX) from brands that are run by enterprises. Smaller organizations are doing a fantastic job of CX, as their efforts are much more focused. Enterprises, being large entities, cannot and often do not provide great CX.

Today's customers and users want services and products to be found, purchased, delivered, and supported easily. They want to digitally communicate with their brands in the same way they do with a human.

Challenge #2: Employee Productivity

It is no secret that enterprise applications are complex. They often considered a hindrance in terms of productivity.

Usually, an enterprise will have close to 12-15 applications that do specific functions. Sifting information from these applications can be vexing for many employees. This often creates a start-stop work environment. Additionally, due to this start-stop environment, employees tend to stop using the applications, which only worsens the situation.

Challenge #3: System-to-System Integration

Enterprises devote a large chunk of their budget, time, and resource towards integrating and connecting disparate systems.

Most enterprises across industries usually rely on makeshift solutions to connect these disparate systems. These systems only increase the discomfort mentioned in the above challenge.

For enterprises, system-to-system integration is essential. They need to a solution that enables systems to communicate with each other to help employee productivity.

How Do Chatbots Integrate Within an Enterprise System?

A chatbot can be integrated using APIs to websites, back-end enterprise systems, and Internet-enabled things. Chatbots can request and send data from these elements — websites, enterprise systems, web applications, RSS, etc.

Chatbots can be connected to cloud-based systems or can be deployed to on-premise systems to coordinate interactions between users, systems, etc.

Real-World Applications of Chatbots

AI has many applications in the real world. They have their application for both end customers and employees alike. They are convenient for driving revenue and cutting costs.

To adapt to the digital age, enterprises want to streamline their business operations to make it easier for their partners and employees. Enterprises need to go through this sort of digital transformation to get high-impact work done. AI-powered chatbots make this possible by simplifying complex people-to-system tasks. They do this by converting these tasks into conversational workflows. These workflows can happen in any of the modern communication channels such as Skype, Spark, SMS, Messenger, email, enterprise internal portals, websites, apps, etc.

A few examples of enterprise-level chatbot applications are:

  • Sales
  • IT help
  • Customer support
  • HR/HCM

Chatbots for Enterprises

  • Finance bot
  • HR bots can find help employees find information about their colleagues, pull up travel expense policies, enroll an employee in the best-suited benefit plan, etc.
  • Sales bots can help pull up top opportunities, make changes to leads on the go, provide key statistical insights, etc.

Chatbots in Our Day-to-Day Life

  • IT help bots can help employees reset their password, bring up documentation of BYOB policies, etc.
  • Travel bot to help individuals book a hotel or flight, pull up information regarding the upcoming travel, provide alerts about any new offers or promotions, etc.
  • Banking bots help in searching for specific transactions through a simple speech command, pay outstanding bills, etc.
  • Chatbots connect people, systems, and things.
  • Healthcare bots alert doctors or healthcare providers if a patient or individual needs urgent care, help keeping track of their lifestyle, etc.

Chatbots For Consumers

  • 63% of people would prefer an online chatbot to interact with a business or a brand.
  • Facebook has over 100,000 chatbots on its Messenger.
  • Over 60% of millennials and 65% of Gen Xers have used a chatbot in a messaging app.
  • In the US, chatbots have a higher retention rate over top-performing apps.
  • Over 55% of end-customers prefer businesses or brands that have an online chatbot.

Chatbots For Employees

  • 77% of employees believe that AI-powered chatbots will improve their lives at the workplace.
  • While using an AI-powered chatbot, enterprises have seen over a 70% decrease in cost per hire.
  • 34% of executives say that chatbots have freed their time, which they now spend on deep thinking.
  • 81% of enterprise employees say that chatbots improve their productivity.


ai ,chatbot ,bot development

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