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by James G. Barr

Docid: 00021061

Publication Date: 2203

Report Type: TUTORIAL


A “chatbot” is simply a computer program or service that simulates human
conversation or, colloquially, human “chats.” While chatbots in the form
of intelligent personal assistants like Siri, Alexa, Cortana, and Google
Assistant are popular among the public, an even larger enterprise market
has emerged, facilitating what’s known as “conversational commerce,” and
furnishing enterprise employees with new tools for data assimilation.

Report Contents:

Executive Summary

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A “chatbot” is simply a computer program or service that simulates human
conversation or, colloquially, human “chats”.1

Intelligent Personal
Assistants Tutorial
Enterprise Uses for
Artificial Intelligence Market

While chatbots in the form of intelligent personal assistants like Siri,
Alexa, Cortana, and Google Assistant are popular among the public, an even
larger enterprise market has emerged, facilitating what’s known as
“conversational commerce,” and furnishing enterprise employees with new
tools for data assimilation.

Digital commerce has entered its third generation:

  • The first generation, electronic commerce, was
    marked by the development of websites – virtual storefronts in which
    products and services previously sold through hardcopy catalogs and
    “brick and mortar” stores could be acquired by anyone with access to a
    PC, a Web browser, and an Internet connection.
  • The second generation, mobile commerce, was spurred
    by the development of smartphones and tablets and featured “mobile apps”
    which, in addition to websites, could be used to conduct commercial
  • The third generation, conversational commerce,
    enabled by messaging platforms like Facebook and Twitter, permits users
    to communicate with businesses and other enterprise entities using
    natural language, either spoken via an audio interface or typed via text
    or other messaging app. The principal instrumentation of conversational
    commerce is the chatbot.

Chatbots have assumed greater relevance recently with the discovery that
mobile users increasingly prefer to operate within messaging apps rather
than social media sites. Likewise, they prefer to stay in messaging mode
rather than exiting the environment to invoke single-purpose mobile apps.

Amazon Alexa and Google Assistant

In the all-important digital assistant (DA) category, two chatbots stand

According to AI Multiple, “With 100+ million units sold, Amazon’s Alexa
is by far the most financially successful chatbot.”

Another prominent DA chatbot is Google Assistant. “Available in all
Android phones with the swipe of the screen, Google Assistant is a
holistic digital concierge. [Assistant] serves as a response suggestion
engine in Google’s messaging platforms.”2

The Face of the Enterprise

Increasingly, chatbots are featured as the face of the enterprise,
responsible for primary customer support and, thus, customer satisfaction
and retention. Chatbot performance is key since the window for making a
positive impression is narrow. As evidence, Forrester reminds us that “63
percent of customers will leave a company after just one poor experience,
and almost two-thirds will no longer wait more than 2 minutes for

The Chatbot Market

Not surprisingly, the chatbot market is booming. According to Mordor
Intelligence, the chatbot space will grow more than 34 percent during the
period from 2021 to 2026, reaching an anticipated $102 billion. Driving
that expansion are advances in natural language understanding (NLU), which
enable increasingly intelligent customer/enterprise interactions.3

Chatbot Basics

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A “chatbot” is simply a computer program or service that simulates human
conversation or, colloquially, human “chats.”4

A chatbot is designed to answers questions or perform actions based on
requests received via an audio, text, or other messaging interface,
communicating with users in the same way that people communicate with each

For example, instead of browsing an enterprise website in search of a
particular product, a user could simply engage the enterprise’s chatbot,
which would ask the user what she is looking for and, based on the user’s
response, recommend one or more products that satisfy her requirements.
The interaction is similar to what a user would experience if she visited
the enterprise’s retail store and engaged a store clerk.5

Chatbots have been around for a long time. According to analyst Michael
Yuan, “The very first chatbot, ELIZA, was developed [more than] 50 years
ago at the Massachusetts Institute of Technology. It simulated a Rogerian
psychotherapist, someone who just repeats the human user’s words back to
the human.

“In the following decades, chatbots were mostly of academic interest. But
in recent years, smartphone-based chatbots have gained wide interest from
the industry.”6

External and Internal Chatbots

There are two basic types of chatbots: external (customer-servicing) and
internal (employee-servicing). As described by analyst Bharathi Ramadass:

  • External

    chatbots are domain-specific: They are designed to
    answer questions targeted to a particular topic such as customer service
    or healthcare.

  • Internal

    chatbots are the opposite. Think of them as a digital
    personal assistant that
    needs to process a wide range of topics typical of any employee

How Chatbots Work

There are two basic types of chatbot operations: rule-based and AI-based.

  • A rule-based chatbot is programmed to recognize and respond to
    specific keywords based on a set of prescribed rules. It has limited
    utility in situations where a user is imprecise in terminology or
  • An AI-based chatbot utilizes machine learning to infer what a user
    actually means. “It understands language, not just commands.”8

AI-Based Chatbots

While rule-based chatbots offer automation, matching user questions with
programmed answers, AI-based chatbots are “trained to operate more or less
on [their] own, using a process known as natural language processing, or
NLP, combined with artificial intelligence and the annotation of human
data.” Importantly, AI-based chatbots “get smarter over time.”9

Once an AI-based chatbot determines (or, perhaps more accurately,
divines) a user’s intent, it fashions an appropriate answer, which,
according to EXPERT AI, is either:

  • “A generic and predefined text;
  • “A text retrieved from a knowledge base that contains different
  • “A contextualized piece of information based on data the user has
  • “Data stored in enterprise systems;
  • “The result of an action that the chatbot performed by interacting
    with one or more backend application; or,
  • “A disambiguating question that helps the chatbot to correctly
    understand the user’s request.”10

Chatbot Platforms

Supporting the chatbot industry are a wide range of chatbot platforms –
with an equally wide range of chatbot tools – to help enterprises develop
custom chatbots. As identified by Influencer MarketingHub, today’s top
three platforms are:

  • EBI.AI

    – “EBI.AI [creates] novel chat and voice experiences
    across all channels with AI assistants that go far beyond your basic FAQ

  • ProProfs Chat

    – “ProProfs Chat is designed specifically for
    businesses looking for real-time sales and support solutions for their

  • Chatfuel

    – “Chatfuel is [a] great, easy-to-use platform for
    building bots without coding but specifically for Facebook.”11

Enterprise Applications

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B2C to B2B and B2E

Enterprises have used chatbots for a number of years, usually to:

  • Assist – or replace – customer service representatives
  • Assist customers visiting enterprise websites

Beyond these business-to-consumer (B2C) applications, Deloitte analysts
David Schatsky and Peter Gratzke believe that chatbots will be
increasingly integrated into:

  • Business-to-business (B2B) operations, further automating
    transactions between enterprises and their suppliers and business
  • Business-to-employee (B2E) operations, enabling HR-related
    self-services, IT diagnosis and repair, and various procurement

Streamlining Internal Workflows

In addition to aiding individual employees, chatbots will be increasingly
deployed to smooth and accelerate enterprise workflows, such as:

  • Employee “onboarding”, helping familiarize new staff members with
    enterprise policies and protocols; and
  • Basic IT support, permitting senior technicians to focus on
    non-trivial problems.13

The Salesperson’s Assistant

By leveraging their frequent interactions with customers and potential
customers, enterprise chatbots can serve as critical repositories of
marketing intelligence, including customer likes, dislikes, product
preferences, and other data that can translate into all-important sales

As analyst Abhiraj Dayal points out, beyond their routine data-gathering,
“[chatbots] can be programmed to ask specific pre-qualification questions
and direct leads to the right team based on the responses for further
nurturing. This would help in automating the sales funnel and allow sales
reps to focus on more time-consuming tasks, such as closing deals!”14 

Personalizing the Experience

Various studies have shown that “personalization” leads to an enhanced
customer experience, which leads, of course, to greater customer
satisfaction and more repeat business, thereby increasing a customer’s
“lifetime value” – an especially relevant statistic given the generally
high cost of customer acquisition. In other words, keeping current
customers happy is normally more lucrative than gaining new customers.
That’s where chatbots offer unique value.

As analyst Dayal explains,”[personalized] bots are able to remember and
utilize information from prior conversations as this information is stored
in a knowledge base. Truly personalized bots enable businesses to have a
1-to-1 conversation with each user, and they go beyond just focusing on
demographics and product interests. By creating chatbots with personality
and characteristics, organizations can enhance the customer journey and
even increase conversion rates.

“Strong customer experiences are a necessity. Chatbot personalization is
also a major advantage for diverse businesses that function in multiple
verticals, as one chatbot can then have various personas for different
audience segments.”15

Three Innovative Chatbots

Seemingly, each day finds a new use case for chatbots. As observed by
analyst Dan Shewan, some of the more innovative – and public-minded –
chatbots are:

  • Endurance – A companion for Dementia Patients
  • UNICEF – Helping Marginalized Communities Be Heard
  • MedWhat – Making Medical Diagnoses Faster16

Take Endurance, for example. Developed by a Russian firm,
“the primary function of the Endurance chatbot is to be a virtual
companion: to speak with [seniors] on general topics, [such as] the
weather, nature, hobbies, movies, music, news, etc.”

The aim is to “complement” human-to-human communication,
which is frequently absent among our senior citizens. “The chatbot asks
questions, reacts to the answers, is able to speak on various topics, and
share interesting news and facts from Google.” In other words, it provides
the type of social and intellectual engagement that might retard the loss
of cognitive function, and extend quality of life for the elderly.

Usage Concerns

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Inappropriate Language

In a recent scholarly paper entitled, “On the Dangers of Stochastic
Parrots: Can Language Models Be Too Big,”17 the authors argue
that “[the] tendency of training data ingested from the Internet to encode
hegemonic worldviews, the tendency of LMs [language models] to amplify
biases and other issues in the training data, and the tendency of
researchers and other people to mistake LM-driven performance gains for
actual natural language understanding – present real-world risks of harm,
as these technologies are deployed.”

In an article called, “The Chatbot Problem,” analyst Stephen Marche
contends that chatbots trained on large Internet data sets, can
unknowingly adopt – and, more distressingly, express – the same biases and
prejudices as many Internet users, leading to “unintended forms of
racialized and gendered othering” speech.18

The lesson is: Watch what your chatbot is saying, and the language it is


All forms of information technology – including chatbots – are vulnerable
to cyber attacks and security exposures. To help mitigate the risk,
analyst Mike Baker suggests that:

  • Chatbot communication should be encrypted, and
    chatbots should be deployed only on encrypted channels.”
  • Chatbot data should be properly protected. “Where
    this information is stored, how long it’s stored, how it’s used, and who
    has access to it must be addressed.”
  • Enterprises should be on the lookout for criminal chatbots.
    “As chatbots become better at imitating humans, the technology will be
    used by hackers in phishing schemes and other social engineering hacks.”19

Personal Privacy

Audio chatbots, most commonly intelligent personal assistants (IPAs), are
always listening. As analyst Deborah Matthews Phillips points out, this
always-on aspect is potentially problematic, as sensitive or confidential
information may be inadvertently – or intentionally – recorded by the
chatbot provider.20

Customer Compliance

Recent research revealed what many chatbot analysts had anticipated and
what many chatbot providers had feared. As Martin Adam, Michael Wessel,
and Alexander Benlian report, “Though cost- and time-saving opportunities
triggered a widespead implementation of AI-based chatbots, they still
frequently fail to meet customer expectations, potentially resulting in
users being less inclined to comply with requests made by the chatbot.”21

While AI-based chatbots are undoubtedly smart, they may not be
smart-enough to conduct the highly-random conversations that occur between
an enterprise and its customers, particularly in a contact center context
where customers may be resentful that they are not talking to a human


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Calculate Chatbot ROI

As with any IT product or service, enterprise officials should calculate
the return on their chatbot investment. As detailed by analyst Abhiraj
Dayal, there are three primary considerations in computing ROI:

  • Query Resolution Time

    – The difference between the time taken
    by a live agent to resolve a particular problem or issue and the time
    consumed by a chatbot.

  • Chatbot/Agent Work Dynamics

    – “Agents can only attend to a
    single user at a time. On the other hand, chatbots can handle multiple
    queries from various users at the same time, and are available 24/7. The
    simple way to calculate this ROI would be to measure how much
    rudimentary work of one live agent could be handled by a chatbot.”

  • Customer Satisfaction Level

    – Surveying customers relative to
    their chatbot versus agent experiences should produce an objective,
    i.e., numerical, ROI value.22

Assess Workforce Impact

As automated productivity tools, the wide scale use of chatbots will have
a significant impact on employees in terms of:

  • Worker training
  • Business process reengineering
  • Even jobs, especially in HR, customer contact centers, and other
    departments where the impact of chatbots may be profound

Enterprise officials should perform a Workforce Impact Assessment prior
to any wholesale introduction of chatbots. To that end, the assessment
process might be informed by conducting minor pilot programs, each testing
the viability of a particular chatbot (or class of chatbots) within the
enterprise ecosystem.


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1 Webopedia.

2 Cem Dilmegani. “Top 30 Chatbots in 2022 & Reasons For
Why They Are The Best.” AI Multiple. February 7, 2022.

3 Bharathi Ramadass. “The Truth About Chatbots.”
January 21, 2022.

4 Webopedia.

5 Matt Schlicht. “The Complete Beginner’s Guide to Chatbots.”
Chatbots Magazine. April 20, 2016.

6 Michael Yuan. “A Developer’s Guide to Chatbots.” IBM
Corporation. August 10, 2016.

7 Bharathi Ramadass. “The Truth About Chatbots.”
January 21, 2022.

8 Matt Schlicht. “The Complete Beginner’s Guide to Chatbots.”
Chatbots Magazine. April 20, 2016.

9 “An Introduction to AI Chatbots.”, Inc. 2021.

10 Team. “Chatbot: What Is a Chatbot? Why Are
Chatbots Important?” March 17, 2020.

11 Werner Geyser. “Best AI Chatbot Platforms for 2022.”
Influencer MarketingHub. December 24, 2021.

12 David Schatsky and Peter Gratzke. “The Conversational
Enterprise.” Deloitte Development LLC. November 4, 2016.

13 Team Linchpin. “25 Chatbot Stats and Trends Shaping
Businesses in 2021.” Linchpin SEO, LLC. March 3, 2021.

14 Abhiraj Dayal. “How Chatbots Help Businesses to Improve
Customer Experience in 2021.” Emplifi Inc. June 1, 2021.

15 Ibid.

16 Dan Shewan. “10 of the Most Innovative Chatbots on the
Web.” WordStream. January 26, 2021.

17 Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, and
Shmargaret Shmitchell. “On the Dangers of Stochastic Parrots: Can Language
Models Be Too Big?” FAccT ’21: Proceedings of the 2021 ACM Conference on
Fairness, Accountability, and Transparency. March 2021:610-623.

18 Stephen Marche. “The Chatbot Problem." The New Yorker. July 23, 2021.

19 Mike Baker. “What’s the Risk? Three Things to Know About Chatbots and Cybersecurity.” UBM. September 19, 2016.

20 Deborah Matthews Phillips. “Are Intelligent Assistants
Smart Enough Yet?” Jack Henry & Associates Inc. August 17, 2016.

21 Martin Adam, Michael Wessel, and Alexander Benlian.
“AI-Based Chatbots in Customer Service and Their Effects on User
Compliance.” Springer. March 17, 2020.

22 Abhiraj Dayal. “How Chatbots Help Businesses to Improve
Customer Experience in 2021.” Emplifi Inc. June 1, 2021.

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About the Author

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James G. Barr is a leading business continuity analyst
and business writer with more than 30 years’ IT experience. A member of
“Who’s Who in Finance and Industry,” Mr. Barr has designed, developed, and
deployed business continuity plans for a number of Fortune 500 firms. He
is the author of several books, including How to Succeed in Business
BY Really Trying
, a member of Faulkner’s Advisory Panel, and a
senior editor for Faulkner’s Security Management Practices.
Mr. Barr can be reached via e-mail at

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