Oh my Bot, I still can’t believe it

WHITEPAPER
Oh my bot, I Still
can’t believe it!
Update:
Trends and use scenarios of
chatbots in the digital workplace

CONTENTS
Introduction 5
Current market developments 6
Conversation with Gillian McCann about the potentials of chatbots 9
BOTS IN THE DIGITAL WORKPLACE 12
Human resource management 12
IT service management 13
Internal communication 14
Software development 15
How you get to your bot 16
Get your chatbot in five steps 17
Successful examples from customers 18
OUTLOOK 21
Imprint:
Whitepaper Publication February 2019
T-Systems Multimedia Solutions GmbH
Riesaer Strasse 5, 01129 Dresden, Germany
Authors:
Kevin Hähnlein
Oliver Reithage
Organization:
Project management: Isabel Uhle
Layout: Peter Brücker

INTRODUCTION
Our first whitepaper on chatbots, which appeared in April 2017, has been in great demand. It
presented use cases for bots along the customer journey and introduced the possibilities and
potentials of a technology whose poignancy in the areas of digitization and IT has continued to
increase in recent years. But what’s really behind a chatbot? In 2019, can we finally talk about
artificial intelligence or is a chatbot just a cooler, algorithm-based user interface? To what degree
has the hype regarding offer and demand continued to evolve in the last two years?
The aim of this whitepaper is to investigate these questions and provide a current overview of
the agile and growing market around conversational interfaces, in other words, chatbots and
voice assistants. In addition, based on use scenarios for various company departments, it
shows how a chatbot can be used to reach the next level of a successfully established digital
workplace in practice.
KEVIN HÄHNLEIN
SOCIAL BUSINESS TECHNOLOGY CONSULTANT
... has worked in consulting for social business technology at
T-Systems Multimedia Solutions since 2016 and guides companies
in their transition to a digital workplace. For his master’s thesis,
the political scientist and economist has also conducted research
on the influence of artificial intelligence on the process of political
opinion formation.
STRONGEST
GROWTH
Web chats and virtual
assistants are the leading
growth trends in the
coming year (in
Europe)
69%
of the companies project
an increase in customer
contacts that are processed
fully automatically
OLIVER REITHAGE
MASTER’S DEGREE CANDIDATE, SOCIAL BUSINESS TECHNOLOGY
... has worked at T-Systems Multimedia Solutions since 2017 as a
working student and master’s degree candidate. The communications
scientist is researching the automation of communication for
his master’s thesis and is an expert in use scenarios for employee-oriented
chatbot systems in the digital workplace.
17%
Phone communication in
the last two years. Telephony
is increasingly replaced
by messenger services
Source: http://www.ibusiness.de/aktuell/db/902403SUR.html
25%
Every fourth resident
in Germany wants to
use chatbots
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INTRODUCTION
INTRODUCTION
CURRENT MARKET DEVELOPMENTS
Chatbots and voice assistants continue to be among the key topics in digitization and are increasingly
prevalent in our everyday personal and business matters. Pioneers in China and the
United States publish new breakthroughs on a weekly basis; in Germany, the start-up scene
around chatbots is also growing steadily. The major players Microsoft and Google, which
until recently observed the dynamic market with some reserve, began their first acquisitions
of successful software last year and can be expected to significantly push their free chatbot
frameworks—Dialogflow and Virtual Assistant—in the near future.
About the technology itself: When it comes to these conversational interfaces, the advancement
of the graphical user interface (GUI), to what degree are we already dealing with artificial
intelligence (AI) nowadays? AI has intrigued humans for decades and has received more or
less attention in public discussion throughout the course of digital progress. At the moment, AI
is again dominating many debates in business, politics and science—and has long arrived in
the personal life of any smartphone user who communicates with voice assistants such as Siri
and Alexa or follows personalized recommendations for songs and shows by Spotify or Netflix.
WHAT DOES (ARTIFICIAL) INTELLIGENCE MEAN?
The inventor of the intelligence quotient, William Stern, defined intelligence as the “capacity
of an individual to consciously adapt his thinking to new requirements.” It is the “general
mental adaptability to the new tasks and conditions of life.” If, in turn, one follows the model
of development levels first described by the Swiss biologist Jean Piaget in the late 1950s, four
levels can be observed in the development of human intelligence: sensomotoric intelligence;
the ability to imagine and speak; thinking ahead and planning; and abstract thinking that lets
us develop hypotheses and analyze problems theoretically as well as systematically. It seems
natural to transfer Stern’s definition and Piaget’s development levels to the creation of artificial
intelligence and smart machines when discussing the opportunities and potentials of new
technologies like chatbots in a modern work environment.
The aim of AI is to get computers to think and act like humans in areas in which humans do
well and perform even better than machines. A study panel at Stanford University describes AI
in this context as a science and collection of various computer technologies that are inspired
by the human body and nervous system so they can learn to feel, reason and act. Rudolph,
Syvikhin & Ebert call this phenomenon cognitive computing and simulate human behavior with
auto-adaptive models. This is based on algorithms that are seen as the fundamental element of
computing and describe a series of computational steps which generate an output based on a
given input. In other words: Algorithms are computer codes that strive to solve computational
problems.
So these technologies enable computers or machines to perceive the world, collect information,
analyze it and understand it through natural voice processing, make decisions and
recommend procedures, as well as reflect on results and learn from them. All these are the key
functions of a chatbot whose architecture and various layers are presented generically in the
text below.
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