The Ultimate Guide to Implementing Conversational AI

The Ultimate Guide
to Implementing
Conversational AI
Within Your Organization

For more information visit www.hyro.ai

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Table of Contents:
Introduction …………………………………………………………….………………... 2
Conversational AI vs. Chatbots ………..……………………………………………. 4
How to Determine if Conversational AI Is Right for Your Business …………... 10
Best Practices for Implementing Conversational AI ……………………………. 15
Implementing Conversational AI as a CIO and Digital/IT Leader …………….. 24
Implementing Conversational AI as a Customer Support/Success Leader …. 29
Implementing Conversational AI as a Customer Engagement Leader ……… 34
Implementing Conversational AI as an Operations and Logistics Leader ….. 38
Covering all Corners with Omnichannel Conversational AI ……………………. 42
Implementing Conversational AI on Your Website ………………………….……. 44
Implementing Conversational AI in Call Centers …...…………………………….. 49
Implementing Conversational AI in SMS/Apps …...………………………………. 53
How to Scale Conversational AI ………..……………………………………….….. 56

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Introduction
At this point, most of us are well acquainted with artificial intelligence (AI).
AI has evolved over the last couple of decades from a science fiction trope to a
universally recognized technology with innumerous benefits to humans. One reason
for this shift in our collective paradigm is the increasing application of AI in almost
every facet of our daily lives.
AI is being harnessed today by
hundreds of different industries, from
healthcare and real estate to finance,
education, and more. What was once
the domain of programmers, engineers,
and rocket scientists has become a
powerful tool for decision-makers
throughout any industry to grow their
companies and fulfill their
business goals.
The range of industries that use multiple forms of AI has catalyzed the evolution of subsets
within AI. However, before discussing the various forms AI may take in a business setting, we
must first define AI in its most basic state.
Although the definition of AI is widely contested and hotly debated, both for ideological and
scientific reasons, in essence, the basic definition of AI is to give technologies such as
computers or robots the ability to use software that mimics human thought or
intelligence. In short, it endows technologies with the ability to "think".
Introduction

3
The goal of implementing AI into technology is to improve its performance in tasks that require
human-like intelligence, such as learning or problem-solving, with the capabilities of data
aggregation and analysis of a machine.
As mentioned, there’s a myriad of AI forms applied in business settings today and used in a
wide variety of capacities. One of the most commonly used and practically applicable among
these is “conversational AI,” which businesses are using to bridge the digital gap and
communicate with their customers.
Conversational AI
Conversational AI is one of the subsets found in AI and refers to a technology that uses
artificial intelligence to communicate or "talk" to users. In the next section of this guide, we
will discuss conversational AI's definition in greater detail and delineate the crucial ways it
differs from chatbots.
Even within the realm of AI, conversational AI is a subject with many facets to it. While it is
impossible to discuss its entire scope, this guide will hopefully give you a comprehensive view
of what conversational AI is, the various forms it can take in a business setting, and how to
best apply it to your organization.
This guide is ideal for any organization or decision-maker planning to take their conversational
AI and automation capabilities to the next level. By the end of this guide, you will have a
thorough understanding of what conversational AI is, how to make it work for your
organization, its business applications, and the best practices to implement to maximize its
potential.
Introduction

4
Conversational AI can be summarized as a technology that can communicate with its
users. It aggregates massive volumes of data and uses machine learning (ML) algorithms
and natural language processing (NLP) to imitate human speech patterns and mimic
human responses.
Along with other AI-powered technologies, the adoption and use of conversational AI is
sky-rocketing. Some reports indicate that intelligent systems such as conversational AI will
conduct 70% of all customer interactions by 2022. Although chatbots and conversational AI
are often categorized together, and the two terms are even used interchangeably, it’s important
to note that there are criticaldistinctions between them.

Conversational AI vs. Chatbots
What Is Conversational AI?
To understand the benefits of implementing conversational AI for your organization,
we need to zoom in on what defines conversational AI, its goal, and what purposes
it serves.
Introduction

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The Typical Chatbot
Chatbots can be divided into two distinct categories:
those which are rule-driven and those which are intent-based.
Rule-Based Chatbots Intent-Based Chatbots
Rule-based chatbots rely on a predetermined set of
rules to follow the predicted ﬂow of the user’s input.
Using the rules of language and typical conversational
patterns, chatbots create a more rigid and structured
experience for users.
Intent-based chatbots are trained on hundreds of
thousands of diﬀerent parameters. Based on
Machine Learning (ML) models, these chatbots
require mounds of manually inserted data to
generate outputs to any given input.
Requires Heavy Data to
Create Outputs
Limited Rule-Based Flows

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Conversational AI Introduces Advanced Capabilities
One of the key differences that helps us distinguish conversational AI from chatbots is the use
of back-end systems to provide the user with information. Conversational AI has direct access
to information sources such as websites, APIs, and databases, which it can then retrieve and
present to the user as required.
When we discuss conversational AI, we refer to a technology that utilizes natural language
processing, natural language understanding, machine learning, deep learning, and predictive
analytics to communicate with users more spontaneously and intuitively.
While the composition of conversational AI may vary, it is generally composed of an automatic
speech recognizer (ASR), a spoken language understanding (SLU) module, a dialog manager
(DM), a natural language generator (NLG), and a text-to-speech (TTS) synthesizer. The ASR
takes raw text and audio inputs and transcribes them into word suggestions sent to the SLU.
The SLU then identifies the semantics of the word sequence and identifies the dialogue
domain. In the meantime, the DM communicates with the user and assists them in achieving
their goals. It ensures that the semantic representation is filled and selects what the system’s
following action will be. It also has access to the relevant knowledge database to retrieve
information for the user. Dialog state tracking and policy selection also assist the dialog agent
and allow it to make more dynamic decisions.

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This composition allows conversational AI to conduct more flexible conversations when
compared to the rigidness of chatbots sticking to a limited “script” or intent.
Unlike chatbots, conversational AI learns by absorbing information from various sources such
as databases, websites, and APIs. Additionally, when a source is modified or updated, the
conversational AI platform will automatically apply these revisions to its interface.
On the other hand, chatbots require maintenance, such as updating or other modifications, to
be done manually, which is costly and inefficient as programmers must make regular updates
to ensure that the chatbots remain efficient and functional.
Continual access to databases and APIs also provides conversational AI interfaces with
enough information and context to maintain a flexible and carried conversation, allowing their
interactions with users to come across as more fluid and dynamic. If a user were to change
their mind or require a different service mid-interaction, a conversational AI solution would fulfill
the user’s needs and maintain the conversation flow, as it has enough information available to
it. Meanwhile, a chatbot will be forced to stick to its script and cannot spontaneously produce
new and dynamic output when required.
An additional point in conversational AI’s favor is that it has a greater understanding of user
inputs. Conversational AI uses natural language processing (NLP) and natural language
understanding (NLU) - both subfields of computer science, artificial intelligence, and linguistics
- enabling conversational AI platforms to analyze and comprehend input received from users,
whether in the form of text or speech.

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While chatbots may seem like they understand the words and sentences the user inputs, all
they are doing is following pre-programmed rules. Unlike conversational AI, chatbots cannot
interpret or even identify any subtle nuances found in human language. In contrast,
conversational AI can respond to contextual clues and understand vernacular, slang, synonyms
and homonyms, and even professional jargon.
Chatbots are also limited to one form of input and can only react and respond to text
commands, whereas conversational AI can also respond to audio input. This makes
conversational AI extremely useful as a virtual assistant (think Siri or Google Home) or a smart
speaker (such as Amazon’s Alexa), or even as a virtual call center agent or conversational voice
layer on a website. Conversational AI platforms’ medium-ﬂexibility allows enterprises to use
one conversational AI solution across all their digital platforms, streaming information directly
into one central analytics hub.


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Chatbots rely on their data being up to date and the user acting predictably, meaning that once

their data is out of date or the user says something oﬀ-script, the chatbot becomes obsolete

and, in the worst-case scenario, even frustrating for users to interact with. Conversational AI
will automatically update itself and can react to user’s conversations in real-time.

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How to Determine if Conversational AI Is
Right for Your Organization
The benefits of conversational AI are significant, but it's essential to clearly
understand what it can do for your organization before jumping right in.
Conversational AI can be applied to a diverse array of fields and implemented on a
variety of channels. However, while it may be highly beneficial for some businesses,
that doesn't mean it will benefit yours. Before you begin, ask yourself the following
questions:
What are your customer service needs?
The best way of assessing whether conversational AI is right for you is by taking an honest look
at your business and analyzing your customer service needs. For example, if your company
has continuous and long-term interactions with customers, using conversational AI will provide
more benefits than a chatbot, which is better suited for one-off interactions as it allows for a
less dynamic experience for users. Limited by its script, it can only manage basic interactions.
Is conversational AI right for your business size?
Enterprises and multi-million dollar companies are more likely to run large-scale customer
service operations. For companies of this size, which maintain ongoing interactions with
customers, conversational AI can dramatically optimize customer service operations. Satisfied
customers will be more likely to return, and customers that feel like your company is available
to them when they need it will become loyal customers with a high lifetime value. That doesn't
mean you have to be a giant corporation to benefit from this type of solution. Any business with
robust customer service operations will have at least one customer communications channel
already in place. Once a company has installed this infrastructure, automating and optimizing it
with conversational AI becomes far more straightforward and less costly.
How to Determine if Conversational
How to Determine if Conversational AI Is Right for Your Business
AI Is Right for Your Business

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The Benefits & Capabilities of Conversational AI
Before making a decision, it’s essential to know what to expect from an effective
conversational AI solution.
More efficient customer service operations
Large companies that have regular contact with customers or include aspects of customer
service where the user's needs may not be predictable cannot rely on a simple chatbot.
For businesses in the healthcare, finance, and real estate industries and others that rely heavily
on maintaining consistent communication with customers, implementing conversational AI can
help keep customers satisfied and alleviate unnecessary stress and frustration on their part.
Reduced costs and workforce
Automating customer service management streamlines every work process while reducing
costs and labor, allowing you to redirect these resources into different channels.
High-quality 24/7 support
Conversational AI also ensures that you have support available for customers 24/7 and that
their problems or queries are dealt with efficiently and quickly as it does not rely on human
intervention or supervision to operate.
More than just customer service
The benefits of conversational AI are hardly limited to customer service alone; it can also be
used to develop other business activities. For example: For a large company, recruiting new
employees and conducting HR activities can become extremely difficult to manage and keep
track of. Adding conversational AI to these processes can streamline the whole experience for
potential employees and the company itself. Conversational AI can send important notifications
to candidates, call candidates to schedule, and assist new hires with acclimating to the
company by explaining employee benefits or the like. Conversational AI can even manage
employee training by allowing employees to practice and hone their customer service skills by
role-playing various AI situations beforehand.


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Increase customer base
Conversational AI can help businesses gain new customers and upsell existing ones.
Conversational AI can suggest products to customers, follow up on potential customers who
show an interest in a product or service, and streamline the entire process for users.
Automating the cycle means that potential buyers have a virtual salesperson and access to
information 24/7. Additionally, by analyzing previous conversations and other information
available on potential buyers, conversational AI can ensure more eﬀective targeting for higher
conversions - this is done by showing users products that are more in line with their behavior,
taste, and needs.


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Making the Decision
If conversational AI has piqued your interest, start by assessing your business's stage on its
journey towards implementing AI technologies. Have you decided AI is right for your business
but don't know how to implement it? Have you already found conversational AI solutions to
implement, but you feel unsure of how your customers will react to the change?
Understanding the stage of implementation your business has reached allows you to prepare a
strategy for continued performance and optimization in the future to keep your business on a
growth trajectory.
Does Conversational AI Support Your Business Goals?
Another way to evaluate if conversational AI is right for your business is by analyzing your
company's goals and intentions and by asking yourself a few questions:

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While the methods of implementing conversational AI are diverse, and there are many ways
conversational AI can promote business growth, it is not a one-size-ﬁts-all solution. Conditions
may vary, and companies should do their research to assess whether it’s right for them.
Customers face a vast array of options before opening up their wallets, making it crucial to
respond to them quickly and connect them with their product and service of choice. It is also
important to remember not to distance dependable customers who have utilized your services
in the past and may not yet be ready for change.

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Best Practices for Implementing
Conversational AI
Conversational AI can be applied to almost any industry, whether for customer
service or even managing employees. Before you start, it’s best to have a thorough
understanding of what you hope to accomplish, who you want to involve in the
implementation process, and how much time, effort, and resources you’re willing
to invest. Creating and implementing a complex system that can interact naturally with
users is not simple and requires research, revision, and intense planning. While you
may face some trial and error along the way, you can help make the process smoother
for your team and company by adhering to several best practices.
In this section, we’ll explore the best practices we recommend when implementing
conversational AI into your organization. These practices should be adopted throughout the
implementation process and can (and should) be tailored towards your organization’s specific
needs and goals.

Create
Customer
Profiles
Conversational AI is primarily focused on your customers, i.e., the people
interacting with the deployed conversational interface most often. One of the
most critical aspects of implementing conversational AI is keeping your
customers in mind during the design and implementation process.
As mentioned previously, many people struggle to adjust to change, and you
want to make the transition as seamless as possible for all parties involved.
The best way to get an idea of how to create the ideal conversational AI for
your customer base is by creating profiles or defining personas of your core
audience. This allows you to gain a perspective on how familiar your users
are with technology tools. For example, when working with an older
customer base, designers should take their discomfort and lack of digital
fluency when interacting with technology into account. For such users, you
need to be extra aware of user experience and ensure your tutorials and
input methods are simple and easy to grasp.
Best Practices for Implementing Conversational AI

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Mapping Your
Users’ Digital
Journeys
Take a closer look at your customers’ needs - identify what they are and at
which point in the process they are needed. An easy way to do this is by
creating a graphic guide or map which will track each step on your users’
journey until they achieve their goal. By mapping out the digital process they
follow, you can review which parts of the process are more intuitive and
which require more attention and polishing. Notice which digital channels you
offer at each point in the journey, and make sure guidance is available where
needed. Understanding the user journey will help make the experience
smoother and enable a more natural flow when implementing conversational
AI. The below image shows an example of a journey your user might take
before deciding to use your company’s service. In this instance, the journey
begins with a customer deciding to search for healthcare and then searching
for a doctor. Once the customer reaches the step in the process where they
decide to schedule an appointment, you can implement your AI, or perhaps
when following the rest of the customer’s journey; you may find a stage
where the AI will be more effective and valuable to the user. You can even
choose to implement it at more than one stage, such as when the user books
an appointment and later in the process to send a reminder to schedule a
follow-up appointment via SMS.

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Identify Your
Organization’s
Goals
Sometimes, getting caught up in the details (and there can be a lot of details)
can make you lose sight of the end goal. Take a step back and focus on the
issues you want to solve and the goals you want to achieve with
conversational AI. The way you implement your AI solution can change
depending on your goals. Are you focused on churn rate, engagement,
business reputation, or customer satisfaction? Is there a problem with current
ticket management or workload that you want to solve? These questions
should guide you through the entire process, from choosing the right solution
to implementing it and customizing it to your needs.
Create a
Conversational
Style Guide
Fluctuating in tone and using an inconsistent style can appear unprofessional
and create more confusion than clarity for your users. It may be challenging to
find the right balance for your conversational AI at first, but being fluent in
your company's messaging and brand voice can create conversational
interactions that are more coherent and efficient for your audience. An
acute understanding of your business’s voice, vocabulary, and level of
formality can help guide the tone you set for your AI. For example, maintaining
a friendly style is crucial; however, an informal tone of speech may be
inappropriate in some industries, like healthcare. In healthcare, an overly
casual tone may come across as flippant and unprofessional, and an overly
serious and formal tone may intimidate customers and make them feel like
they are dealing with a severe issue. Keeping a consistent voice not only builds
a positive user experience but can also strengthen your brand identity. Another
aspect of conversational style worth noting is humanity. The AI must come
across as human enough that customers feel comfortable interacting with it,
but it shouldn't come across as a caricature of humanity. The ideal way to do
this is by creating a balance between efficiency, empathy, and helpfulness.
Keep interactions concise and to the point and focus on providing customers
with access to the help or resources they need.

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Identify Your
Organization’s
Goals
Unlike a typical chatbot that only deals with simple requests and relies on
basic scripts, conversational AI maintains prolonged social contact with
users, requiring conversational context.
A chatbot will only need to manage simple, one-off commands, but
conversational AI conducts far more complex and prolonged interactions that
generally involve making contact multiple times over certain periods of time.
This means that it will require access to previous data and have the ability to
understand the context of the current conversation to a degree. This is why AI
is so critical for such advanced capabilities - as it enables the solution to
analyze relevant data about a user and previous interaction in order to create
better conversations in real-time. To make sure your AI always has the correct
context for the interaction, it is critical to include the data it has collected in
previous interactions with the customer, even those held with human agents.
Enhance Your
Brand Image
Branding may not be the first thing that comes to mind when considering
implementing conversational AI, though it certainly offers several
essential branding opportunities.
Your AI will have close and consistent interactions with your users. When
executed correctly, in line with your brand tone and messaging, this can
significantly improve the user experience and brand loyalty. 73% of
customers cite a positive experience as a key influence when choosing to be
loyal to a brand. To enhance your brand image, focus on a consistent style
that accurately represents your brand voice. Before implementing your AI,
ensure that it is professionally developed, easy to use, and reflects your
brand’s high standards.

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Customize
the Experience
Unlike‌‌
a‌‌
chatbot,‌‌
conversational‌‌
AI‌‌
does‌‌
not‌‌
need‌‌
to‌‌
stick‌‌
to‌‌
a‌‌
basic‌‌
script,‌‌

and‌‌
it‌‌
has‌‌
access‌‌
to‌‌
databases‌‌
with‌‌
customers'‌‌
data.‌‌
These‌‌
two‌‌
factors‌‌

enable‌‌
it‌‌
to‌‌
personalize‌‌
suggestions‌‌
and‌‌
conversations‌‌
to‌‌
match‌‌
each‌‌
user's‌‌

preferences,‌‌
location,‌‌
previous‌‌
behavior,‌‌
and‌‌
more.‌‌
Personal‌‌
experiences‌‌

improve‌‌
conversion‌‌
and‌‌
customer‌‌
satisfaction.‌‌
Studies‌‌
show‌‌
that‌‌
‌
80%‌‌
of‌‌

customers‌
‌‌
are‌‌
likely‌‌
to‌‌
complete‌‌
the‌‌
purchasing‌‌
process‌‌
from‌‌
a‌‌
brand‌‌
that‌‌

provides‌‌
a‌‌
personalized‌‌
user‌‌
experience.‌‌
Starting‌‌
your‌‌
AI‌‌
off‌‌
with‌‌
all‌‌
the‌‌
data‌‌

you‌‌
have‌‌
on‌‌
the‌‌
customer‌‌
allows‌‌
it‌‌
to‌‌
begin‌‌
with‌‌
the‌‌
advantage‌‌
of‌‌
already‌‌

being‌‌
able‌‌
to‌‌
customize‌‌
the‌‌
first‌‌
interaction‌‌
it‌‌
has‌‌
with‌‌
your‌‌
customer.‌‌
As‌‌
it‌‌

develops,‌‌
it‌‌
will‌‌
continue‌‌
to‌‌
add‌‌
the‌‌
data‌‌
it‌‌
has‌‌
collected‌‌
to‌‌
further‌‌
customize‌

future‌‌
interactions.‌ ‌

Be‌‌
Prepared‌

to‌‌
Handle‌ ‌

Irregular‌‌

Requests‌ ‌

Continuous‌‌
and‌‌
long‌‌
conversations‌‌
can‌‌
often‌‌
include‌‌
unusual‌‌
questions.‌‌ ‌

For‌‌
a‌‌
chatbot‌‌
built‌‌
for‌‌
only‌‌
simple‌‌
commands,‌‌
this‌‌
presents‌‌
a‌‌
problem.‌‌

Conversational‌‌
AI‌‌
is‌‌
designed‌‌
for‌‌
these‌‌
types‌‌
of‌‌
conversations‌‌
and‌‌
is‌‌
able‌ ‌

to‌‌
provide‌‌
relevant‌‌
responses‌‌
while‌‌
keeping‌‌
a‌‌
natural‌‌
flow.‌‌ ‌

That‌‌
being‌‌
said,‌‌
even‌‌
with‌‌
the‌‌
platform’s‌‌
access‌‌
to‌‌
user‌‌
data,‌‌
at‌‌
some‌‌
point,‌

someone‌‌
will‌‌
ask‌‌
a‌‌
question‌‌
it‌‌
can’t‌‌
answer.‌‌
Avoid‌‌
generic‌‌
error‌‌
messages‌‌

often‌‌
used‌‌
with‌‌
chatbots,‌‌
and‌‌
create‌‌
a‌‌
response‌‌
that‌‌
clearly‌‌
points‌‌
out‌‌
the‌‌

error‌‌
and‌‌
provides‌‌
guidance‌‌
on‌‌
how‌‌
to‌‌
solve‌‌
it‌‌
or‌‌
what‌‌
the‌‌
user‌‌
should‌‌ ‌

do‌‌
next.‌ ‌


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Invest in
Testing and
QA (Quality
Assurance)
Working with conversational AI involves numerous factors - you need to
maintain consistency, have your users in mind, and consider as many
scenarios and conversations as possible. Implementing conversational AI
doesn’t have to be complicated with the right solution and guidance. Still, it is
highly recommended to test it out after initial implementation and when
changes are made to ensure optimal execution. Consider it a QA phase, just
like you would with new websites and products. Test your conversational AI
thoroughly before it’s launched and at every update. Ideally, have a team
assigned to testing and reviewing your conversational AI’s performance. This
team should be involved in the planning and implementation stages to get an
idea of the product’s goals and what it looks like when it’s behaving properly
versus a malfunction. This will also help your team discover ways to improve
it, add additional scenarios, and bring up needed features or capabilities that
you may not have initially considered. The testing team should look out for
language, consistency, and data retrieval issues and ensure everything is
running smoothly before the conversational AI platform is released and at
regular intervals once it’s live as an additional precaution.
If you plan to implement conversational AI within your organization for
employee use, having employees in on the design and implementation
process will build excitement and allow the employees to weigh in on their
needs for the solution. Additionally, the employees involved will feel like part
of the process and will be more open to accepting the changes.

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Quick Tips for Conversational AI
There’s a lot to consider before, during, and after you implement conversational AI, so
here’s a short recap of the key guidelines to keep in mind.


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Here are several conversation design best practices to keep in mind during
the implementation phase:
Charting the conversation design in a ﬂow map style makes it easier to review the entire
conversation in one place. It will serve as a useful guide to look over at each point during the
design and implementation process. Take a look at the ﬂow-map example below:


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Before implementation, select the channels or software you want to integrate your
conversational AI into. This is where a clear understanding of your company's goals is crucial.
As there are many options for integration, it is up to you to decide which will be most beneﬁcial
and which platforms your users are most likely to use.
Among the many options are: messaging applications, CRMs, payment systems, booking
calendars, Slack, email, smart speakers, voice apps, call centers, ticketing softwares, and your
company’s website.

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Implementing Conversational AI
as a CIO and Digital/IT Leader
As those responsible for introducing and implementing new technologies into their
companies, CIOs shoulder much of the responsibility for ensuring their success and
proving their ROI and value. As a CIO, your job does not only entail ﬁnding and
introducing new technologies but also ensuring that the implementation process goes
smoothly and without a hitch. As with any new technology, conversational AI presents
its challenges to all parties involved. However, CIOs must be prepared to manage the
common issues that may come up during the implementation process.
One of the challenges CIOs must be prepared to
manage when implementing conversational AI is
ensuring that the organization’s data is of good
quality and in sufficient quantity. AI systems in
general and conversational AI in particular
strongly rely on the quantity and quality of the
data available to them for high performance
and efficiency.
AI Relies On You to Identify High-Quality Data
Conversational AI uses large datasets with information on customers or employees to "learn"
how to hold conversations, give context to interactions, and answer queries. To ensure that users'
interactions with your conversational AI platform are high quality, its speech patterns are natural,
and its information is accurate, it is crucial to provide the platform with access to as much
updated, high-quality data as possible. This presents several issues, such as accessing the data
and deciding which data meets the conversational AI platform's standards.
Implementing Conversational AI as a CIO and Digital/IT Leader

25
Conduct an audit to establish what data you already have at your disposal. If the interface
is intended for company employees' internal use, this data can be gathered from an employee
database. Suppose the platform will be primarily dedicated to customer service purposes. In
that case, information can be collected from prior interactions customers have had with human
employees or forms customers have submitted.
Once you have collected the relevant data already in your possession, you will need to
categorize it and compare it to the data your AI requires. Categorize your data into subsets
such as structured and unstructured. Make a note of where the data you’ve collected is stored.
Once you have matched your data to what the platform requires, you will be able to identify any
gaps in information still missing for the platform to function optimally.

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Some of the missing information can be supplemented with publicly available information
and can easily be accessed by the system. Other information may be difficult to collect at
first; however, synthetic data can fill in the gaps. Synthetic data is artificially made and not
generated by actual events, and although it is generally based on actual data, it is not as
functional as the real thing. Synthetic data can be used for the learning phase of implementing
conversational AI. Ideally, it should be replaced by “real” data at the earliest possible
opportunity.
Knowing what data you have and what data remains to be collected gives
you a clear idea of how to grow your dataset to best benefit your conversational AI.
Another issue you may face as a CIO or IT leader implementing conversational AI is the
difficulty non-technical staff may have in coming to grips with using this new technology.
The ideal way to combat any fears or insecurities non-technical staff may have is with
education, patience, and understanding.
As the company's CIO or IT leader, it is your responsibility to bridge the gap between new
technology and employees without creating insecurities or hostilities. This means ensuring that
you have a thorough understanding of operating the technology and how it works, and where
your colleagues stand in relation to it. Once you are familiar with the technology, you and your
team can introduce the rest of the staff to how conversational AI works and what it can and
can't do. Suppose you or your team don't feel ready to educate the rest of the staff. In that
case, an alternative is to invite an expert on conversational AI to prepare them ahead of
implementation or have your conversational AI vendor handle the onboarding process for you
(when applicable).

27
Another risk inherent in implementing conversational AI is that the technical staff themselves
are resistant to implementing it. One reason tech or IT employees may feel insecure about
implementing an AI is that they think they lack the skills to manage it.
A global study by Harris Insights in collaboration with IBM found that while more than 80% of
employees in the U.S. and UK believe having AI skills will be a competitive advantage for their
companies, 42% said they don’t believe their HR departments can execute the needed training
programs to get them up to speed.
It is challenging to create and embrace digital transformation within a company when the tech
staff doesn't feel equipped to handle the change. In addition, retraining or finding new tech
staff to keep up with the changes is incredibly difficult.
Due to the popularity of AI, there is a shortage of people with the skills and knowledge to help
implement it. Fortunately, there are several solutions CIOs or IT leaders can turn to. One option
is to look beyond those traditionally expected to have the skill set to manage AI
implementation, such as IT graduates, and turn to less conventional talent pools. This can
mean turning to self-educated programmers or graduates of coding boot camps. Another
option is to stick with the staff you already have and offer them retraining to help them develop
the skills they need to implement and maintain such a solution. Finally, encourage skill
development among your tech staff and grow their professional capabilities to meet your
company’s needs. This point ties into the need to preserve knowledge and skills by providing
staff with regular learning opportunities and training seminars, keeping them up to date on the
newest trends in conversational AI.

28
By implementing conversational AI into your company, you can lead it through a successful
digital transformation process which will:
Increase employee productivity
Reduce the costs of customer care
Create an interactive form of brand messaging
Improve customer interaction and satisfaction
Make your company more accessible to customers
CIOs have proven, time and time again, that their roles are invaluable to an organization's
success, especially when it comes to spearheading digital transformation.


29

Implementing Conversational AI as a
Customer Support/Success Leader
As a customer support/success leader, introducing
the concept of conversational AI to your staff and
preparing them for the implementation process can
be a complex and sensitive process. Some staff
members may feel threatened, as conversational AI
is intended to fill a customer service role, which has
solely been held by humans up until this point.
The best way to get your team on board is by
introducing them to the benefits conversational AI
brings to the company as a whole and the realm
of customer service in particular.
24/7 Access
With conversational AI, customers enjoy
access to a customer service representative
24/7 - even if it’s an artificial one. As a result,
your company no longer needs to maintain a
24/7 shift cycle or force customers to wait
for regular working hours to speak with a live
customer service representative.
Reduced Costs
Research has found that the average duration
of a customer service call clocks in at just over
11 minutes, with a direct labor cost of around
$1.60 per minute or $17.5 per conversation.
A Tellus International study revealed that
conversational AI platforms garner average
support center time savings of more than four
minutes per inquiry, which amounts to saving
$6.5 per interaction.
Implementing Conversational AI as a Customer Support/Success Leader

30
The vast number of customer care staff
experiencing burnout also affects the
company as a whole by lowering staff morale
and creating added expenses. High burnout
rates lead to a high turnover rate and staff
shortages, increasing costs for the company
scrambling to replace their employees. Many
of the contributing factors to this
phenomenon, such as boredom, long and
arduous work hours, work overload, and
stressful work environments, can be
mitigated by implementing conversational AI.
Large Volumes
Conversational AI can manage large volumes of customers and tickets and hold several

customer interactions concurrently. When customers have access to the information they need

when they need it, they are more likely to make a purchase or use your company’s services.

Customers will also feel more satisfied and less frustrated when their issues or queries are

dealt with efficiently and promptly.
How does conversational AI help your support team? Employee turnover in a majority
of call centers has been estimated at an alarmingly high 25% and up, with many settling
at a 40%-50% mark, according to F. Curtis Barry & Company. An explanation generally
accepted for this alarming phenomenon is that staff working in call centers experience
incredibly high burnout rates.

31‌

Training‌‌
AI‌‌
with‌‌
data‌‌
that‌‌
your‌‌
company‌‌
already‌‌
has‌‌
allows‌‌
it‌‌
to‌‌
handle‌‌
the‌‌

most‌‌
basic‌‌
and‌‌
repetitive‌‌
queries‌‌
and‌‌
tasks‌‌
that‌‌
are‌‌
known‌‌
contributors‌‌
of‌‌
support‌‌
staff‌‌

burnout.‌‌
Far‌‌
from‌‌
replacing‌‌
the‌‌
human‌‌
staff‌‌
in‌‌
a‌‌
call‌‌
center,‌‌
AI‌‌
is‌‌
designed‌‌
to‌‌

work‌‌
for‌‌
them.‌‌
By‌‌
managing‌‌
the‌‌
simple‌‌
queries‌‌
users‌‌
may‌‌
have,‌‌
the‌‌
AI‌‌
allows‌‌
support‌‌
staff‌‌
to‌

focus‌‌
their‌‌
energies‌‌
on‌‌
solving‌‌
more‌‌
complex‌‌
issues‌‌
users‌‌
face,‌‌
which‌‌
are‌‌
more‌‌
stimulating‌‌

and‌‌
therefore‌‌
far‌‌
less‌‌
likely‌‌
to‌‌
lead‌‌
to‌‌
boredom‌‌
and‌‌
eventual‌‌
burnout.‌‌
Additionally,‌‌
having‌‌
a‌‌

AI‌‌
virtual‌‌
assistant‌‌
available‌‌
to‌‌
interact‌‌
with‌‌
users‌‌
24/7‌‌
allows‌‌
call‌‌
center‌‌
staff‌‌

to‌‌
enjoy‌‌
more‌‌
flexible‌‌
work‌‌
hours.‌‌
Once‌‌
users‌‌
have‌‌
access‌‌
to‌‌
answers‌‌
for‌‌
their‌‌
initial‌‌

questions,‌‌
they‌‌
will‌‌
be‌‌
far‌‌
more‌‌
willing‌‌
to‌‌
wait‌‌
patiently‌‌
for‌‌
human‌‌
assistance‌‌
in‌‌
answering‌‌

their‌‌
more‌‌
substantial‌‌
questions.‌ ‌

Allowing‌‌
your‌‌
call‌‌
center‌‌
staff‌‌
to‌‌
focus‌‌
on‌‌
areas‌‌
in‌‌
which‌‌
their‌‌
skills‌‌
are‌‌
utilized,‌

rather‌‌
than‌‌
wasting‌‌
their‌‌
time‌‌
by‌‌
having‌‌
them‌‌
constantly‌‌
look‌‌
up‌‌
mundane‌‌

information,‌‌
makes‌‌
them‌‌
feel‌‌
valued‌‌
and‌‌
develops‌‌
their‌‌
soft‌‌
skills.‌‌ ‌

The‌‌
Role‌‌
of‌‌
Human‌‌
Representatives‌ ‌

It‌‌
is‌‌
worth‌‌
reiterating‌‌
that‌‌
AI‌‌
is‌‌

designed‌‌
to‌‌
work‌‌
with‌‌
human‌‌
support‌‌
and‌‌
not‌‌
in‌‌

place‌‌
of‌‌
humans.‌‌
Although‌‌
AI‌‌
may‌

become‌‌
developed‌‌
enough‌‌
in‌‌
the‌‌
not-too-distant‌‌

future‌‌
to‌‌
replace‌‌
human‌‌
customer‌‌
support‌‌
roles‌‌

entirely,‌‌
today,‌‌
it‌‌
should‌‌
be‌‌
viewed‌‌ ‌

as‌‌
‌
a‌‌
force-multiplier‌‌
for‌‌
human‌‌
agents‌
.‌‌ ‌

Studies‌‌
have‌‌
shown‌‌
that‌
‌‌‌
‌
71%‌‌
of‌‌
customers‌‌ ‌

said‌‌
they‌‌
would‌‌
not‌‌
continue‌‌
to‌‌
use‌‌
a‌‌
brand‌‌ ‌

that‌‌
did‌‌
not‌‌
allow‌‌
them‌‌
access‌‌
to‌‌
human‌‌

customer‌‌
service‌‌
representatives‌‌
when‌‌

necessary.‌‌
AI‌‌
at‌‌
its‌‌
best‌‌
serves‌ ‌

as‌‌
a‌‌
tool‌‌
utilized‌‌
for‌‌
the‌‌
convenience‌‌
of‌‌
both‌‌ ‌

your‌‌
customers‌‌
and‌‌
your‌‌
team‌‌
operating‌‌ ‌

the‌‌
call‌‌
center.‌ ‌ ‌


32
This two-pronged approach guarantees that the customer’s basic needs are met quickly,
and that human assistance is available for more nuanced questions which could require
intervention.
For many call centers that experience high turnover rates and high burnout levels, the constant
rotation of staff can mean that most new employees lack sufficient training. Implementing a
conversational AI platform can help speed up the training flow of new employees. New team
members unsure of how to answer specific queries can turn to conversational AI assistants,
which can absorb unlimited amounts of data. Even veteran employees often struggle to
memorize the hundreds of terms and procedures involved in answering customer questions,
and AI can fill in the gaps. This particularly applies to call center operators working in the
medical, financial, banking, and government fields.
Companies are turning in droves to conversational AI as an easy solution for their customer
care needs. However, while conversational AI is developing in leaps and bounds, can
handle most user queries, and even “recall” the context of user interactions, it still cannot
entirely replace human agents in a call center or other customer service operation.
A combined approach of conversational AI in cohesion with live human support is
the preferred approach companies should consider.

33
Once you have reassured your agents that this new technology is not there to replace them but
to enhance their capabilities and allow them to make use of their skill sets, and you have
illustrated the beneﬁts conversational AI can bring to the customer service department as a
whole, they are far more likely to get on board with the implementation process.
Empower your team with the skills, knowledge, and resources they need to understand and
use conversational AI. This is particularly important at the beginning of the implementation
process, when your conversational AI platform may need some adjustment. At this stage of
implementation, staﬀ can supervise the AI and inform IT of any changes that may be required.

34‌

Implementing‌‌
AI‌‌
as‌‌
a‌

Customer‌‌
Engagement‌‌
Leader‌ ‌

For‌‌
a‌‌
customer‌‌
engagement‌‌
leader,‌‌
much‌‌
of‌‌
the‌‌
benefits‌‌
of‌‌
implementing‌‌

AI‌‌
seem‌‌
apparent.‌‌
In‌‌
your‌‌
role‌‌
of‌‌
driving‌‌
the‌‌
customers‌‌
to‌‌
continually‌

engage‌‌
with‌‌
your‌‌
company‌‌
and‌‌
have‌‌
your‌‌
product‌‌
or‌‌
service‌‌
top‌‌
of‌‌
mind,‌‌
providing‌‌

customers‌‌
with‌‌
access‌‌
to‌‌
information‌‌
on‌‌
your‌‌
service‌‌
or‌‌
product‌‌
24/7‌‌
seems‌‌
like‌‌
an‌‌

ideal‌‌
situation.‌ ‌

The‌‌
obvious‌‌
benefits‌‌
of‌‌
reducing‌‌
wait‌‌
time‌‌
for‌‌
customer‌‌
service,‌‌
fast‌‌
interactions,‌‌
query‌‌

resolution,‌‌
and‌‌
information‌‌
availability‌‌
are‌‌
likely‌‌
to‌‌
increase‌‌
customer‌‌
‌
satisfaction‌
,‌‌
and‌‌

continuous‌‌
access‌‌
to‌‌
service‌‌
will‌‌
increase‌‌
customer‌‌
‌
engagement‌
.‌‌
Additionally,‌‌
not‌‌
needing‌‌
to‌

hold‌‌
or‌‌
wait‌‌
for‌‌
long‌‌
periods‌‌
of‌‌
time‌‌
will‌‌
reduce‌‌
frustration.‌‌
Having‌‌
‌
significant‌‌
time‌‌
lapses‌‌

between‌‌
a‌‌
customer's‌‌
first‌‌
engagement,‌‌
such‌‌
as‌‌
form‌‌
submission‌‌
and‌‌
first‌‌
contact‌‌
made‌‌
by‌‌

sales‌‌
representatives,‌‌
has‌‌
been‌‌
shown‌‌
to‌‌
have‌‌
a‌‌
strong‌‌
effect‌‌
on‌‌
whether‌‌
these‌
‌‌
‌
contacts‌‌

choose‌‌
to‌
‌‌
use‌‌
your‌‌
company's‌‌
product‌‌
or‌‌
service.‌ ‌

Using conversational AI to reach out to these customers to provide information,
targeted oﬀers or other personalized messages makes them more likely to choose
your company's service and continue to engage.
Implementing Conversational AI as a Customer Engagement Leader

35‌

Despite‌‌
These‌‌
Benefits,‌‌
Some‌‌
Hurdles‌‌
May‌

Deter‌‌
Customers‌‌
from‌‌
Engaging‌‌
with‌‌
Your‌‌

Company‌‌
Through‌‌
AI.‌‌ ‌

As‌‌
a‌‌
customer‌‌
engagement‌‌
leader,‌‌
take‌‌
charge‌‌
and‌‌
prepare‌‌
your‌‌
customers‌‌
for‌‌
the‌‌
changes‌

they‌‌
may‌‌
experience‌‌
during‌‌
the‌‌
implementation‌‌
process.‌‌
When‌‌
working‌‌
with‌‌
customers,‌‌
it‌‌
is‌

essential‌‌
to‌‌
consider‌‌
cultural‌‌
background.‌‌
Some‌‌
sectors‌‌
of‌‌
society,‌‌
in‌‌
particular‌‌
older‌‌

generations,‌‌
may‌‌
feel‌‌
uncomfortable‌‌
communicating‌‌
with‌‌
a‌‌
computer‌‌
software.‌‌
While‌‌
it‌‌
may‌

take‌‌
some‌‌
users‌‌
time‌‌
to‌‌
get‌‌
used‌‌
to‌‌
the‌‌
idea‌‌
of‌‌
communicating‌‌
with‌‌
an‌‌
AI,‌‌
once‌‌
customers‌‌

have‌‌
experienced‌‌
firsthand‌‌
the‌‌
convenience‌‌
AI‌‌
provides‌‌
and‌‌
are‌‌
assured‌‌
that‌

they‌‌
still‌‌
have‌‌
access‌‌
to‌‌
a‌‌
human‌‌
customer‌‌
service‌‌
representative‌‌
if‌‌
needed,‌‌
they‌‌
will‌‌
grow‌‌

more‌‌
comfortable‌‌
with‌‌
the‌‌
idea‌‌
and‌‌
embrace‌‌
the‌‌
transition.‌ ‌

Some‌‌
of‌‌
the‌‌
ways‌‌
you‌‌
can‌‌
simplify‌‌
the‌‌
transition‌‌
process‌‌
for‌‌
your‌

customers‌‌
include:‌ ‌

Maintaining‌‌
a‌‌
clear‌‌
line‌‌
of‌‌
communication‌‌
with‌‌
your‌‌
users‌‌
throughout‌‌
the‌‌
implementation‌

process‌‌
and‌‌
ensuring‌‌
that‌‌
they‌‌
understand‌‌
the‌‌
changes‌‌
taking‌‌
place‌ ‌

Synchronizing‌‌
the‌‌
customer‌‌
information‌‌
that’s‌‌
collected‌‌
and‌‌
the‌‌
last‌‌
interactions‌‌
held‌‌
with‌

customers‌‌
across‌‌
all‌‌
channels‌‌
and‌‌
platforms‌ ‌

Ensuring‌‌
that‌‌
your‌‌
AI’s‌‌
interface‌‌
is‌‌
user-friendly‌‌
and‌‌
easy‌‌
to‌‌
navigate‌

Implementing‌‌
your‌‌
AI‌‌
on‌‌
platforms‌‌
users‌‌
expect‌‌
to‌‌
interact‌‌
with‌‌
AI‌‌
on,‌‌
such‌

as‌‌
your‌‌
company‌‌
website‌ ‌

Creating‌‌
a‌‌
interface‌‌
with‌‌
a‌‌
focus‌‌
on‌‌
keeping‌‌
a‌‌
consistent‌‌
brand‌‌
voice‌‌
and‌‌ ‌

meeting‌‌
customer’s‌‌
needs‌‌
-‌‌
this‌‌
includes‌‌
designing‌‌
natural‌‌
and‌‌
human-sounding‌‌
conversations‌


36
The central function of a conversational AI platform is to hold conversations with customers.
In order to create an interface that users can comfortably interact with, the design process
must begin with a clear direction in mind. This platform will be the first point of contact for most
of your users; an unpleasant interaction will cause your users to avoid your company's
conversational AI interface altogether.
When a conversational AI platform is constructed without
a clear understanding of the interactions it will have with
users, it will incorrectly identify users’ needs or requests,
and most interactions will end up out of scope.
Another mistake often made when implementing
conversational AI is misidentifying the channels where a
conversational layer is most needed. Companies may choose
to implement their platform on the company website when
users would rather interact with it via WhatsApp. Paying
attention to the channels your users are mainly engaging with
will indicate where to implement your platform for the most effective interactions.
Remember: The Most Crucial Aspect of a
Conversational AI Platform Is the Conversation
Itself.
If your conversational AI platform feels uninviting and is awkward for users to interact with,
it will create an irksome experience which customers are likely to retain. In fact, according to
research by Ungapped, 59% of customers say it only takes one or two bad customer
service experiences to decide not to work with a company in the future. Customers who
are already uncomfortable with the idea of interacting with AI will feel even more discomfited.
The convenience of a shorter wait time and accessible information can't make up for the
disappointment and frustration caused by unnatural and unintuitive interactions.


37‌

As‌‌
a‌‌
customer‌‌
engagement‌‌
leader,‌‌
ensure‌‌
that‌‌
the‌‌
voice‌‌
guidelines‌‌
for‌‌
your‌‌

interface‌‌
are‌‌
well‌‌
written‌‌
and‌‌
consider‌‌
your‌‌
company's‌‌
tone,‌‌
technical‌‌
jargon,‌‌
and‌‌
formality‌‌

level.‌‌
Additionally,‌‌
it‌‌
is‌‌
crucial‌‌
to‌‌
ensure‌‌
your‌‌
AI‌‌
platform‌‌
can‌‌
access‌‌
all‌‌
the‌‌

databases‌‌
and‌‌
information‌‌
it‌‌
may‌‌
need‌‌
to‌‌
provide‌‌
context‌‌
to‌‌
user‌‌
interactions.‌‌
Small‌‌
details‌‌

such‌‌
as‌‌
error‌‌
messages‌‌
or‌‌
live‌‌
hand-offs‌‌
to‌‌
a‌‌
human‌‌
representative‌‌
also‌‌
need‌‌
to‌‌
be‌‌
carefully‌‌

phrased‌‌
to‌‌
avoid‌‌
user‌‌
discomfort‌‌
and‌‌
ensure‌‌
that‌‌
users‌‌
will‌‌
want‌‌
to‌‌
engage‌‌
with‌‌
your‌‌

AI‌‌
again‌‌
in‌‌
the‌‌
future.‌‌
The‌‌
staff‌‌
in‌‌
your‌‌
company‌‌
who‌‌
are‌‌
ideally‌‌
positioned‌‌
to‌‌

contribute‌‌
to‌‌
this‌‌
process‌‌
are‌‌
those‌‌
most‌‌
experienced‌‌
in‌‌
directly‌‌
interacting‌‌
with‌‌
your‌‌

company's‌‌
client‌‌
base‌‌
-‌‌
your‌‌
customer‌‌
support‌‌
team.‌‌
This‌‌
staff‌‌
should‌‌
be‌‌
ready‌‌
to‌‌
step‌‌
in‌‌

should‌‌
your‌‌
AI‌‌
interfaces‌‌
encounter‌‌
an‌‌
out-of-scope‌‌
question.‌‌
Additionally,‌‌

throughout‌‌
the‌‌
implementation‌‌
process,‌‌
this‌‌
staff‌‌
can‌‌
supervise‌‌
the‌‌
platform's‌‌
interactions‌‌
and‌

advise‌‌
if‌‌
any‌‌
changes‌‌
or‌‌
adjustments‌‌
need‌‌
to‌‌
be‌‌
made.‌‌
Between‌‌
this‌‌
staff‌‌
and‌‌
an‌‌
algorithm,‌‌

and‌‌
by‌‌
analyzing‌‌
data‌‌
from‌‌
past‌‌
customer‌‌
interactions,‌‌
your‌‌
AI‌‌
should‌‌
develop‌‌

a‌‌
natural-seeming‌‌
speech‌‌
pattern‌‌
that‌‌
will‌‌
set‌‌
users‌‌
at‌‌
ease‌‌
and‌‌
make‌‌
them‌‌
more‌‌
eager‌‌
to‌‌

interact‌‌
with‌‌
your‌‌
AI.‌ ‌

AI‌‌
can‌‌
also‌‌
be‌‌
used‌‌
for‌‌
other‌‌
forms‌‌
of‌‌
user‌‌
interaction,‌‌
such‌‌
as‌‌
outreach‌‌

through‌‌
personalized‌‌
content‌‌
on‌‌
social‌‌
media‌‌
or‌‌
email‌‌
campaigns‌‌
and‌‌
responding‌‌
to‌‌
customer‌

questions‌‌
and‌‌
comments‌‌
online.‌ ‌


38

Implementing Conversational AI as an
Operations and Logistics Leader
Managing operations or logistics for a company of any size is no simple feat. In
addition to managing logistics on the customer’s end by ensuring clear
communication and timely product and service delivery, you must also address
complex logistical procedures within your company.
A fundamental factor in managing complex logistical operations is having clear and open
communication with the parties involved, whether that entails customers or employees. As
intricate as managing a vast web of contact points and managing a network of operations can
be, employing conversational AI can help simplify many aspects of the process.
In addition to the evident applications of conversational AI as a customer service vehicle, when
it comes to business operations and logistics, it is a versatile tool that can facilitate both
internal and external communications and streamline various logistical tasks.
Some of the logistical tasks that conversational AI can facilitate include:
Ticket/appointment booking
Tracking cargo or vehicles
Rate comparisons
Answer FAQs
Placing or making changes to an order
Follow up with customers
Notifying customers of any changes or delays

Implementing Conversational AI as an Operations and Logistics Leader

39
AI can increase productivity and motivation by
automating tasks that lead to burnout
Besides helping customers manage their logistical needs and keeping them informed,
conversational AI can also increase communication and productivity within your operations
department. Conversational AI can be used as a virtual assistant for employees to increase
their productivity and enhance their skills by providing information and context they may not be
aware of. Moreover, it can increase employee satisfaction and reduce risks of burnout or
boredom by automating repetitive and “boring” tasks such as appointment or delivery
scheduling for customers. By automating these tasks, conversational AI allows your employees
to turn their attention to more complex work which requires human intervention. By focusing on
more engaging work, your employees will feel more productive and stimulated and are less
likely to suﬀer from boredom or burnout.

Implementing Conversational AI as an Operations and Logistics Leader

40‌

Automating‌‌
Logistical‌‌
Tasks‌‌
with‌

AI‌ ‌

Report‌‌
Generation‌‌
and‌‌
Invoice‌‌
Delivery‌ ‌

AI‌‌
can‌‌
automate‌‌
complex‌‌
tasks,‌‌
like‌‌
generating‌‌
reports‌‌
automatically‌ ‌

and‌‌
sending‌‌
them‌‌
to‌‌
relevant‌‌
parties,‌‌
keeping‌‌
managers‌‌
and‌‌
other‌‌
superiors‌‌
informed,‌

invoice‌‌
processing,‌‌
and‌‌
maintaining‌‌
communication‌‌
between‌‌
customers,‌‌
suppliers,‌‌ ‌

and‌‌
service‌‌
providers.‌ ‌

Simplifying‌‌
Communication‌ ‌

Using‌‌
AI‌‌
can‌‌
also‌‌
improve‌‌
the‌‌
efficiency‌‌
of‌‌
communications‌‌
by‌‌
cutting‌‌
down‌‌
on‌

a‌‌
lot‌‌
of‌‌
the‌‌
unnecessary‌‌
interactions‌‌
typically‌‌
involved‌‌
in‌‌
coordinating‌‌
tasks‌‌
with‌‌
multiple‌‌

stakeholders.‌‌ ‌

For‌‌
logistics‌‌
managers‌‌
managing‌‌
product‌‌
shipments‌‌
and‌‌
deliveries,‌‌
or‌‌
supply‌‌
chain‌‌

operations,‌‌
AI‌‌
can‌‌
better‌‌
communicate‌‌
with‌‌
those‌‌
involved‌‌
in‌‌
the‌‌
manufacturing‌

and‌‌
delivery‌‌
process.‌‌
Delivery‌‌
drivers,‌‌
for‌‌
example,‌‌
are‌‌
familiar‌‌
with‌‌
providing‌‌
updates‌‌
via‌‌
text‌‌

message‌‌
or‌‌
similar‌‌
communication‌‌
platforms.‌‌
However,‌‌
by‌‌
implementing‌‌
AI‌‌ ‌

into‌‌
the‌‌
delivery‌‌
process,‌‌
drivers‌‌
not‌‌
only‌‌
have‌‌
a‌‌
more‌‌
efficient‌‌
and‌‌
constantly‌‌
available‌‌
source‌

to‌‌
communicate‌‌
with,‌‌
but‌‌
can‌‌
also‌‌
receive‌‌
assistance‌‌
and‌‌
information‌‌
on‌‌
the‌‌
go.‌‌ ‌

Fleet‌‌
Management‌ ‌

AI‌‌
can‌‌
provide‌‌
companies‌‌
with‌‌
regular‌‌
updates‌‌
on‌‌
their‌‌
fleet,‌‌
such‌‌
as‌‌
the‌‌

vehicles‌‌
currently‌‌
in‌‌
service,‌‌
and‌‌
alert‌‌
if‌‌
they‌‌
require‌‌
maintenance‌‌
or‌‌
are‌‌
out‌‌
of‌‌
order‌‌
through‌

ongoing‌‌
contact‌‌
with‌‌
drivers‌‌
and‌‌
technicians.‌‌ ‌

mplementing Conversational AI as an Operations and Logistics Leader

41‌

Warehouse‌‌
Management‌‌
Automation‌ ‌

When‌‌
working‌‌
with‌‌
supply‌‌
chain‌‌
operations,‌‌
an‌‌
additional‌‌
use‌‌
for‌‌
AI‌‌
is‌‌
utilizing‌

it‌‌
to‌‌
automate‌‌
customer‌‌
orders‌‌
and‌‌
warehouses.‌‌
Firms‌‌
operating‌‌
large‌‌
warehouses‌‌
and‌‌

delivering‌‌
vast‌‌
quantities‌‌
of‌‌
products‌‌
must‌‌
constantly‌‌
be‌‌
attentive‌‌
and‌‌
communicative‌ ‌

about‌‌
customer‌‌
orders.‌‌
AI‌‌
can‌‌
provide‌‌
and‌‌
obtain‌‌
from‌‌
customers‌‌
timely‌‌

updates‌‌
on‌‌
canceled‌‌
orders,‌‌
delayed‌‌
orders,‌‌
unclaimed‌‌
orders,‌‌
or‌‌
other‌‌
sudden‌‌
changes.‌‌ ‌

By‌‌
having‌‌
access‌‌
to‌‌
real-time‌‌
changes‌‌
and‌‌
orders‌‌
made‌‌
by‌‌
customers,‌‌
you‌‌
and‌‌
your‌‌
team‌ ‌

will‌‌
attain‌‌
a‌‌
more‌‌
realistic‌‌
picture‌‌
of‌‌
the‌‌
supply‌‌
needed‌‌
and‌‌
will‌‌
be‌‌
able‌‌
to‌‌
make‌‌
adjustments‌‌

on‌‌
the‌‌
go.‌‌ ‌

This‌‌
AI-led‌‌
approach‌‌
allows‌‌
warehouse‌‌
managers‌‌
to‌‌
plan‌‌
only‌‌ ‌

for‌‌
what‌‌
is‌‌
needed,‌‌
minimizing‌‌
waste,‌‌
and‌‌
saving‌‌
your‌‌
company‌‌
money‌‌
and‌‌
resources.‌

mplementing Conversational AI as an Operations and Logistics Leader

42

Covering All Corners with Omnichannel
Conversational AI
According to Harvard Business Review, around 73% of customers looking to purchase a
product go through multiple channels before committing to a purchase. Customers generally
prefer to do as much research as possible before making a decision.
Omnichannel refers to the focus on
multiple communication channels to provide
customers with a holistic
customer service experience.
Omnichannel conversational AI means
implementing conversational interfaces onto more
than one channel simultaneously, i.e., website,
mobile app, voice assistants, smart speakers, call
centers, and more.
While generally, companies will implement the
interface onto the channel on which their
customers are most engaged, for example, social
media or the company's website, taking an
omnichannel approach ensures that your users
are covered no matter the channel they prefer to
use. Adopting an omnichannel strategy to
conversational AI grants customers consistent
access to information or customer service
regardless of their favored medium. Besides
creating a more comfortable and seamless
experience for your customers, it can also help
bolster your marketing and bottom line. A study
conducted by Adobe found that companies that
support an omnichannel approach to customer
engagement achieve a 25% increase in close rates.

Covering all Corners with Omnichannel Conversational AI

43
Omnichannel conversational AI can also help your company build datasets by gathering
customer information from various channels. The data collected and the ability to resume
interactions on multiple platforms enables you to create uniquely personalized cross-channel
customer experiences. This feature is often missed by companies who prefer to only implement
conversational AI on the channel their users are most commonly found on; however,
maintaining a consistent presence across all channels signiﬁcantly inﬂuences customer
satisfaction and brand loyalty.

Covering all Corners with Omnichannel Conversational AI

44‌

Implementing‌‌
AI‌

on‌‌
Your‌‌
Website‌ ‌

To‌‌
gain‌‌
the‌‌
most‌‌
out‌‌
of‌‌
your‌‌
AI‌‌
platform,‌‌
perhaps‌‌
the‌‌
most‌‌
crucial‌‌
best‌

practice‌‌
to‌‌
consider‌‌
(other‌‌
than‌‌
adopting‌‌
an‌‌
omnichannel‌‌
approach)‌‌
is‌‌
implementing‌‌

the‌‌
interface‌‌
first‌‌
onto‌‌
the‌‌
channel‌‌
your‌‌
customers‌‌
are‌‌
most‌‌
comfortable‌‌
with‌‌
and‌‌
are‌

most‌‌
engaged‌‌
on.‌ ‌

For‌‌
most‌‌
companies,‌‌
that‌‌
channel‌‌
is‌‌

their‌‌
website,‌‌
serving‌‌
as‌‌
the‌‌
central‌‌

hub‌‌
of‌‌
their‌‌
online‌‌
presence‌‌
and‌‌
the‌‌

first‌‌
place‌‌
customers‌‌
turn‌‌
to‌‌
for‌‌
more‌

information.‌‌
Making‌‌
that‌‌
information‌‌

accessible‌‌
to‌‌
users‌‌
may‌‌
make‌‌
the‌‌

difference‌‌
between‌‌
a‌‌
frustrated‌‌
or‌‌

loyal‌‌
customer.‌ ‌

A‌
‌‌
‌
survey‌‌
conducted‌‌
by‌‌
eMarketer‌‌

showed‌‌
that‌‌
‌
63%‌
‌‌
of‌‌
customers‌‌
were‌

more‌‌
likely‌‌
to‌‌
return‌‌
to‌‌
a‌‌
website‌‌
if‌‌

it‌‌
offered‌‌
live‌‌
chat.‌‌
Furthermore,‌‌ ‌

the‌‌
study‌‌
found‌‌
that‌‌
online‌‌
buyers‌‌

who‌‌
had‌‌
used‌‌
live‌‌
chat‌‌
were‌‌
more‌‌

likely‌‌
to‌‌
make‌‌
online‌‌
purchases‌‌
at‌‌

least‌‌
once‌‌
a‌‌
week‌‌
(‌
40%‌
)‌‌
than‌‌
buyers‌

who‌‌
had‌‌
never‌‌
chatted‌‌
(‌
22%‌
).‌ ‌

Implementing Conversational AI on Your Website

45
Implementing conversational AI on your
company's website offers a slew of advantages:
Most customers are comfortable navigating the platform
Customers are able to browse your products’ catalogue and are likely
to want more information
Customers can quickly complete the process of making a purchase or
committing to using a service
Customers have 24/7 access to information
Your website is your most accessible channel, especially due to new website
accessibility tools
These Are Some of the Top Best Practices Hyro
Recommends Companies Adopt When
Deploying Conversational AI on Their Website:
Choose the Best Place to Implement Your
Conversational Interface
The location and accessibility of a conversational
interface (mainly in the form of a chatbot or virtual
assistant) deployed on your website can make a
world of difference. Some users may appreciate
having a window pop up and customer service
offered to them as soon as they access your site,
while others may find this intrusive or irritating.


46
As with selecting a channel, the key here is to know your audience and
understand where AI intervention will be most helpful.
Identify where your AI has the highest potential of positively impacting current and potential
customers; this may be your checkout page, homepage, or both. An AI virtual agent can serve
as your customer's introduction to your product or as a method of collecting customer
feedback. Having a clear understanding of the customer base you cater to will allow you
to deploy conversational AI effectively and efficiently to create a positive digital journey
and experience for every customer.
Create Personalized Content
Creating personalized content is a
cornerstone of conversational AI use and
implementation. Research conducted by
Epsilon has shown that 80% of customers
are more likely to complete a purchase
when companies create a personalized
experience for them. Arguably, there is
nowhere as essential to ensure your AI
reflects your brand voice as on your
company's website. Context is also a
crucial aspect of creating personalized
content. The 'voice' your AI will use needs
to reflect more than just your company's
brand voice, but also a clear
understanding of who your customer is
and what they want to accomplish.
The ability to accumulate and analyze conversational data is one of the prime advantages
of using conversational AI. Using the data gathered from previous interactions with users or
conversations conducted with live support agents, your AI can contextualize new customer
interactions. This allows it to target each interaction towards a specific customer, better
understand, and even predict what they will need.

47
Take Time to Test Everything
Conversational AI plugged into your website will be most closely associated with your business
in your customer's eyes versus its use on any other channel. This means that while testing is a
critical part of implementing conversational AI in general, it is particularly crucial to do so on
your website, as it directly affects your brand image.
Furthermore, when implementing conversational AI in a call center or on a pre-existing
messaging platform, there will already be an established UI/UX for your user to interact with.
Whereas, when using your website as a channel, you will have to ensure that the design
remains consistent, easy to use, and accessible to all your users. Test your layouts on
multiple devices and in different languages and on all browsers to ensure that the quality
and style remain fluid and consistent. While numerous methods for performing automated
tests exist, it is highly advisable to perform manual tests at each stage of development.
Ensure Security and Transparency
One of the challenges of implementing conversational AI onto a company website is running
the risk of customers being reluctant to take advantage of it. This may be because they are
uncomfortable communicating with an AI, distrust the security of the information they divulge,
or in some cases, your chat window may appear to be just another form of spam to your
customers. In this case, your AI will achieve the opposite of its goal, with customers doing
whatever they can to avoid interacting with it.
Well executed UI and UX can help encourage customers, even reluctant ones, to interact with
your AI. A sleek and professional design endows your conversational interface with legitimacy
and assures users that it's not a spam-related tool. Well-designed conversational flows, which
feel more human to customers, can also help remedy these issues. An AI that interacts more
humanly and is culturally sensitive, and responsive to customer communications will help your
customers feel more comfortable interacting with artificial intelligence. One of the most
effective ways to put your customers at ease around interacting with an AI is by being
transparent with them.

48
Manage expectations and make it clear to your customers that they are interacting with

an AI upfront, rather than mistakenly misleading them into believing that they are dealing

with a customer service representative.
Establish trust by educating your users on the new interface and by assuaging any
privacy-related concerns they may have. Finally, ensure that your interface meets the highest
security standards, both to protect your users' data and to ensure that it does not divulge any
sensitive information to third parties.


49

Implementing Conversational AI in Call
Centers
In the past, using AI to automate call centers meant customers had to interact with a
robotic voice and rigid script. AI was extremely limited in the ways it could interact
with and assist customers. Today, conversational AI is fully capable of initiating and
maintaining meaningful interactions with customers.
Modern conversational AI can successfully conduct transactions and provide customers with
the information or care they require. The evolution of conversational AI and the many benefits
that come with its implementation has led consulting firms such as Gartner to predict in 2019
that by 2021, 15% of customer service interactions conducted worldwide will be managed by
AI alone. This represents a 400% increase in AI performed interactions from 2017.
While the coronavirus pandemic has stunted the growth of many industries, it likely
contributed to AI development. With human employees limited by efforts to contain the virus,
the phenomenon of using conversational AI to conduct customer service operations became
more widespread. A more recent study revealed that 71% of IT decision-makers believe in AI's
ability to improve customer service during the pandemic, and 64% of them revealed plans to
increase investments in AI and automation for the foreseeable future.
With conversational AI recognized as an asset to customer service and call centers, it has
become a must-have component for call centers looking to keep up with the competition and
provide customers with 24/7 availability and other benefits, which can be expensive or even

Implementing Conversational AI in Call Centers

50
impossible without the use of AI. While the decision to implement conversational AI into your
call center may seem like a no-brainer, the process is less straightforward. Here are a few best
practices you can put in place to smooth the process of implementing conversational AI into
your call center:
Identify Which Calls the AI Is Most Suited to Deal With
Although conversational AI has evolved and can manage most simple customer interactions, it
is still recommended to have a human representative available to take over more nuanced,
sensitive requests. AI can manage transactional interactions with greater efficiency, but human
agents are more suited for dealing with emotional interactions such as customer complaints.
For analytical tasks such as finalizing product registration or changing the delivery details, AI is
less likely to make mistakes and get things done more quickly, and human agents are better
equipped to manage complex and emotionally involved tasks which require empathy.
While AI excels at tasks that require speed, consistency, and basic information retrieval,
knowing which calls the AI will not be able to handle is the first step in creating a successful
conversational AI platform for your call center. Starting your calls off with your AI allows it to
gather the customer's information, document whichever procedures it has already applied, and
pass that information on to a human agent.
Use Smart Call-Routing Techniques
Most of us are all too familiar with the frustration of waiting for hours on a customer service
hotline, only to be transferred to the wrong department. By using conversational AI's analytical
capabilities, callers can be routed to the most appropriate representative to troubleshoot their
issues, optimizing your live agents' time and your company's resources, in addition to
improving your customers' experience.
AI can also direct customers to the ideal agent to fulfill their requests by using analytical
capabilities to profile your agents. While AI's profiling capabilities are generally used to gather
data on customers, knowing the skills and specialties of your agents can make delegating
customers an easier task. Some agents may excel at managing complaints, while others are
better at assisting. By looking at the agent's sales numbers, experience, call handle time, and
other such metrics, the AI will assign customers to an agent best suited to serve them.


51
Identify and Define Your Goals
While implementing conversational AI should reduce your company's costs and improve your
customer satisfaction in general, it is vital to set and define your goals for the AI during the
implementation process. Conversational AI works similarly to humans in that it learns and
should develop over time. AI should only need to be taught once before it can use a skill.
Setting defined goals gives you a benchmark to measure the success and evolution of your AI.
The goals you set for your AI may involve reducing customer effort or increasing customer
service speed.
Identify your company's pain points to help find the areas where your AI can contribute the
most and use them to guide you when setting goals for your AI. Specify your challenges and
set KPIs to showcase your conversational AI's interface value to other stakeholders in the
company. For example, if you know that your customers become frustrated and leave
when they are forced to hold for long periods of time waiting for an agent, your AI's goal
would be to cut down these wait times by an X number of minutes per call.
Work with Your IT Department
Simply inserting AI into your already running call center is a recipe for disaster. Before
deploying, make sure your conversational interface is fully integrated with your call center
apparatus. One of the first steps is ensuring your AI can recognize your callers through their
phone numbers, which will require giving it access to your CRM. Enabling the AI to access your
CRM will allow it to process all the data it necessitates to deal with customers and provide
them with a personalized experience, such as identifying details, activity history, and more.
Other datasets will need to be accessed and scraped, including information about your
company, to answer user queries and confirm transactions. To train your AI properly and ensure
it has access to all the necessary information, you will need to collaborate with your company's


52
IT department from the earliest stages of the process. Ensure the IT team clearly understands
your business objectives and what components your AI will require to function efficiently in the
call center.
Ensure Your AI Has Context for Conversations
Context gathered by your conversational AI interface is essential in a call center scenario. In
addition to 'teaching' the AI how to interact with customers, human agents can also use the
data gathered to create complete customer profiles.
The historical data can reveal the customer's previous interactions with the company.
The AI will apply this data to personalize future interactions held with the customer.
Understanding the background and context of a customer's interaction allows your
conversational interface to engage more naturally, and in some cases, even anticipate requests
or questions. Context also simplifies the customer's journey by mitigating valuable time wasted
on explaining the background of a request and the reason for contacting the company. If the
query becomes too complex for the AI to manage, having the context to build a customer
profile allows the AI to redirect the customer to the right agent with all the knowledge the agent
needs to start the conversation on the right foot.


53‌

Implementing‌‌
AI‌‌
in‌

SMS/Apps‌ ‌

Using‌‌
SMS‌‌
or‌‌
messaging‌‌
applications‌‌
for‌‌
marketing‌‌
purposes‌‌
can‌‌
come‌‌
across‌‌
to‌‌

customers‌‌
as‌‌
a‌‌
tired‌‌
gimmick‌‌
or‌‌
even‌‌
annoying‌‌
spam,‌‌
but‌‌
implementing‌‌
a‌‌

AI‌‌
interface‌‌
into‌‌
your‌‌
SMS‌‌
campaigns‌‌
can‌‌
breathe‌‌
new‌‌
life‌‌
into‌‌
them.‌

Customers‌‌
can‌‌
receive‌‌
personalized‌‌
messages‌‌
and‌‌
suggestions‌‌
and‌‌
even‌‌
obtain‌‌
further‌‌

information‌‌
or‌‌
finalize‌‌
their‌‌
purchase‌‌
on‌‌
the‌‌
same‌‌
platform.‌ ‌

AI‌‌
also‌‌
empowers‌‌
you‌‌
to‌‌
review‌‌
your‌‌
campaigns'‌‌
effectiveness,‌‌
providing‌‌
you‌‌
with‌‌
valuable‌‌

analytics‌‌
such‌‌
as‌‌
the‌‌
number‌‌
of‌‌
replies,‌‌
actions,‌‌
conversions,‌‌
and‌‌
sales‌‌
completed.‌‌
Instead‌‌
of‌

taking‌‌
a‌‌
shot‌‌
in‌‌
the‌‌
dark,‌‌
you‌‌
can‌‌
develop‌‌
your‌‌
campaigns‌‌
and‌‌
A/B‌‌
test‌‌
them.‌ ‌

Other‌‌
benefits‌‌
of‌‌
implementing‌‌
AI‌‌
in‌‌
SMS‌‌
and‌‌
messaging‌‌
applications‌‌
include:‌

Customers can directly contact your company by simply replying to a received message
There is no need to redirect customers to another platform to ﬁnalize a transaction
Create customized messages based on user data to promote your product
One AI platform can communicate with multiple customers simultaneously, saving on
human labor and resources
Customers are likely to read the messages you send them and even respond. According to
areport by EZTexting, consumers are X4.5 more likely to respond to an SMS message
than to an email
Almost every customer will have access to SMS or a messaging app, which is not a
guarantee with social media platforms
Most customers are already familiar with how to use SMS and messaging apps

54
These advantages can be further amplified when implemented with best practices. To achieve
the best results with conversational AI, here are the top five best practices we recommend:
Communicate Clearly with Users
SMS and most messaging apps do not include buttons, meaning that your customer will need
to reply with letters and numbers. The AI will need to communicate clearly with customers to
receive the replies it needs. To simplify this further, try to make requests which only require a
single character reply. This is easier for the AI to analyze and minimize the risks of misspellings
and grammatical errors, which may damage the interaction flow. You’ll notice this is often used
in SMS campaigns which include a call to action like “send 1 to join”, “type YES to get the
latest deal”, etc.
Collect Customer Data
This practice is particularly important when using SMS. Having the customer's phone number
gives the AI access to a goldmine of information available online, allowing you to personalize
messages and simplify interactions. Instead of asking for details in vague terms, the AI will
gather the information and only need the customer to confirm its accuracy. Beginning an
interaction in a more personal way also makes the interaction feel more natural and engaging.
Write Engaging Copy and Use Emojis (if relevant to your audience!)
When using SMS, there is no guarantee that your customer is using a smartphone. This means
it is preferable to avoid sending media such as images or videos, which may be sent out
corrupted, out of order, or not at all. The ideal way to engage your customers is by ensuring
your AI uses creative and dynamic copy. If your company generally uses a less formal tone
when engaging with customers, feel free to use emojis when appropriate, mainly when the
customer is near or has reached their goal on their digital journey. However, when using
emojis, keep in mind that some look drastically different on iOS than Android or other
operating systems, so test your campaigns out on different devices.

Implementing Conversational AI in SMS/Apps

55
Maintain Engagement
There is a well-known rule for driving re-engagement on Facebook: always send a user a
second message after 24 hours.
There's no "24-hour rule" for SMS, but you should still be careful to avoid spamming your
customers. Follow-up messages should be designed strategically to appeal to each specific
customer. Using conversational AI allows you to tailor these messages to suit your customer's
needs or ensure that your advertising applies to them and isn't just spam. For example,
suppose your company is running a promotion only in a specific city. In that case, AI allows you
to send the information only to customers who live in that city or who are currently staying
there based on recent location data freely available on social media.
Provide Your Customers with Added Benefits
Using conversational AI to promote your company to potential customers provides a unique
opportunity to make customers feel that they are getting more than just an advertisement. You
have the opportunity to provide customers with something that will make their interaction with
your AI feel like a positive, memorable experience. Giving customers something that adds value
for them, such as a free quote or personalized plan of action, makes them feel like they have
gained something from interacting with your company.

Implementing Conversational AI in SMS/Apps

56

How to Scale Conversational AI
Congratulations! With the help of this guide, you have successfully implemented
conversational AI into your company.
Expect to experience:
Higher productivity
Lower customer care costs
Personalized brand messaging
Direct contact with customers
Statistics and metrics illustrating customer engagement
Increased employee satisfaction
Better customer care
Revenue-driving conversational insights
And overall upticks in customer engagement, conversions, and satisfaction
But, don't rest on your laurels just yet. As your company grows, the scale of the conversational
AI platform you invested time, money, and eﬀort into will need to develop and grow to match
your company's needs. Otherwise, you run the risk of having an interface that seems sloppy
and provides inconsistent customer service. Your AI should be able to "learn" and develop to
meet increasing customer demands. As it evolves, you will create more engaging experiences
and natural interactions for your customers and continue to meet their demands as your
business grows. While we have discussed various use cases for conversational AI, it is most
commonly used to improve customer service, lead to a more positive customer experience, or
improve internal communications and lead to greater eﬃciency of internal operations.
Supervising such a vast project and maintaining the AI to ensure it keeps pace with company
growth can present several challenges.


57
These are the top three most common challenges that companies attempting to scale their
conversational AI encounter:

Taking the Variety of Demands Into Account
Customers and employees will use your AI, each encountering it through different
channels and in varying formats, and both will make demands of it. Your AI will need
to adapt and produce a positive experience by meeting the demands of both. For
example, a customer may interact with the AI through SMS or chat, while your
employees will interact with it directly through the business interface. Customers are
also likely to go through various channels, make the first contact on your company's
site or via messaging app, and then dial a call center to follow up. To achieve this
kind of synergy, all moving parts must be in complete sync and updated
regularly to create a smooth customer journey.
Having your AI sync across multiple channels makes it easier for customers to feel
like their needs are understood and will be met. When a user has to explain their
issue several times on multiple platforms, it looks like the company lacks cohesion
and will make the client reluctant to trust you. The drawback of this approach is that it
demands much more scalability. The variety of demands from different sources
creates a real challenge when scaling AI, particularly for contact centers.
Automating Complex Systems
The entire basis for AI is automation, both when used for customer service and
internally. Companies need to be prepared to manage a broad range of processes,
applications, and rules to automate AI across the entire company successfully. While
it may sound simple, the intricate nature of these systems can complicate this. Some
infrastructures may use a UI, while others will be more back-end-based and the same
with APIs. The diversity of these programs makes it more challenging to scale
conversational AI throughout the company. Automating each section system by
system will also cost a considerable amount of time, effort, and money. Hence, it is
critical to find a solution that can be implemented seamlessly across all
channels, covering all bases without unnecessary complications.

58‌

Assess‌‌
What‌‌
Needs‌‌
to‌‌
Improve‌

Organizations‌‌
often‌‌
feel‌‌
that‌‌
once‌‌
they‌‌
have‌‌
set‌‌
up‌‌
and‌‌
implemented‌‌
their‌‌
AI‌‌

interface,‌‌
it‌‌
can‌‌
be‌‌
left‌‌
to‌‌
its‌‌
own‌‌
devices‌‌
and‌‌
independently‌‌
resolve‌‌
any‌‌
issue‌‌
that‌‌
comes‌‌
its‌‌

way.‌‌
This‌‌
is‌‌
a‌‌
common‌‌
misconception,‌‌
and‌‌
AI‌‌
has‌‌
not‌‌
yet‌‌
reached‌‌
this‌‌
point‌‌
technologically.‌‌
‌
AI‌

operating‌‌
in‌‌
contact‌‌
centers‌‌
should‌‌
still‌‌
be‌‌
monitored‌‌
for‌‌
improvement‌‌
opportunities‌‌
and‌

to‌‌
ensure‌‌
that‌‌
it's‌‌
making‌‌
a‌‌
difference‌‌
in‌‌
customer‌‌
engagement‌‌
and‌‌
conversions.‌
‌‌
If‌‌
the‌‌

platform‌‌
isn't‌‌
improving‌‌
your‌‌
call‌‌
center,‌‌
serious‌‌
overhauls‌‌
need‌‌
to‌‌
be‌‌
made.‌‌
After‌‌
all,‌‌
why‌‌

keep‌‌
investing‌‌
precious‌‌
money‌‌
and‌‌
time‌‌
into‌‌
something‌‌
that's‌‌
not‌‌
proving‌‌
ROI?‌ ‌

Every‌‌
step‌‌
of‌‌
the‌‌
customer's‌‌
journey‌‌
should‌‌
be‌‌
carefully‌‌
scrutinized‌‌
to‌‌
determine‌‌
areas‌‌
for‌‌

improvement‌‌
and‌‌
growth.‌‌
Enterprises‌‌
should‌‌
take‌‌
full‌‌
advantage‌‌
of‌‌
AI's‌‌

analytics‌‌
and‌‌
insights‌‌
to‌‌
classify‌‌
and‌‌
alleviate‌‌
detrimental‌‌
pain‌‌
points‌‌
to‌ ‌

their‌‌
customers'‌‌
digital‌‌
journeys.‌ ‌

Lack‌‌
of‌‌
Data‌ ‌

Most‌‌
companies‌‌
struggle‌‌
to‌‌
grasp‌‌
the‌‌
sheer‌‌
volume‌‌
of‌‌
‌
data‌‌
required‌‌
to‌‌
maintain‌‌

intent-based‌‌
or‌‌
machine‌‌
learning-based‌‌
AI‌
‌‌
and‌‌
downplay‌‌
the‌‌
time‌‌
and‌

effort‌‌
needed‌‌
to‌‌
gather‌‌
this‌‌
data.‌‌
When‌‌
beginning‌‌
to‌‌
scale‌‌
your‌‌
AI,‌‌
data‌‌
becomes‌‌
an‌‌

even‌‌
more‌‌
crucial‌‌
component.‌‌
Companies‌‌
must‌‌
ensure‌‌
that‌‌
the‌‌
information‌‌
they‌‌
have‌

collected‌‌
is‌‌
appropriately‌‌
stored‌‌
in‌‌
datasets‌‌
which‌‌
the‌‌
AI‌‌
can‌‌
access‌‌
and‌‌
that‌‌
data‌‌

definitions‌‌
and‌‌
management‌‌
are‌‌
standardized.‌‌
Manually‌‌
curating‌‌
such‌‌
vast‌‌
quantities‌‌

of‌‌
data‌‌
is‌‌
practically‌‌
impossible.‌‌
‌
To‌‌
scale‌‌
these‌‌
platforms,‌‌
the‌‌
amount‌‌
of‌‌
data‌‌

must‌‌
increase‌‌
both‌‌
in‌‌
quantity‌‌
and‌‌
complexity.‌ ‌


59
Scaling Conversational AI with the
World’s First Adaptive Communications
Platform
These challenges may seem impossible if no obvious solution presents itself. There is,
however, an easier way to scale conversational AI. Hyro's Adaptive Communications Platform,
powered by a uniquely hybrid computational linguistics and knowledge graphs approach to
Natural Language Understanding (NLU), is the only conversational interface on the market that
does not demand complex, expensive, and tasking implementation and deployment, and can
be fully operational in a matter of hours, not days across any and all of your digital channels.
As Hyro's Adaptive Communications Platform automatically scrapes and ingests continuously
updated information from sources such as websites, databases, APIS, and CSVs, its capacity
to scale and adapt to your company's growth is limitless.


60
To learn more about implementing conversational AI within your organization painlessly and
effortlessly, book a free consultation with one of our experts, schedule a demo, and see Hyro's
Adaptive Communications Platform in action.
About Hyro
Hyro is the world’s first Adaptive Communications Platform. Featuring plug & play
conversational AI and natural language automation, Hyro empowers enterprises to flex their
processes and messaging across their most valuable platforms, services, and
channels—including contact centers, chat solutions, SMS, and more. Say goodbye to rigid
chatbots and voice assistants running on intent-based flows that constantly break. With the
adaptive advantage for enterprise, Hyro is ushering in a new age of conversational
technologies that are quick to deploy, easy to maintain and simple to scale—conserving vital
resources while generating better conversations, more conversions, and revenue-driving
insights.


The Ultimate Guide to Implementing Conversational AI

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