Introduction of Artificial Intelligence - Opportunities and potential for companies

1. Brief introduction
August 2019
Introduction of Artificial Intelligence.
Opportunities and potential for companies

2. Artificial Intelligence (AI) refers to the automation of intelligent behavior and is a
cross-sectional technology incorporating various disciplines.
1
Philosophy
Computer
Science
Psychology
Neuro
Sciences
Mathematics
Linguistic
Economy
Artificial
Intelligence
Source: Mücke Sturm Company
Definition & basics of AI
Cross-sectional areas involved in AI
Overview
Minsky McCarthy
“Artificial intelligence
…describes any task
performed by a program or a
machine that, if a human
carried out the same activity,
we would say the human
had to apply intelligence to
accomplish the task.”
“Artificial intelligence
… is intelligence
demonstrated by machines,
in contrast to the natural
intelligence displayed by
humans and other animals. ”
“Artificial intelligence
…is a system’s ability to
correctly interpret external
data, to learn from such data,
and to use those learnings to
achieve specific goals and
tasks through flexible
adaptation.”
Kaplan Haenlein
“Artificial intelligence
…is the ability of a digital
computer or computer-
controlled robot to perform
tasks commonly associated
with intelligent beings.”
Künstliche
Intelligenz
„Artificial
Intelligence“
Various definitions of „Artificial Intelligence“
Extract

3. Artificial intelligence has various fields of application and technologies which are
based on human abilities and actions.
2
Artificial Intelligence – fields of application
Source: Mücke Sturm Company; McKinsey, 2018
Machine Learning
Independent Learning
Computer Vision
Understanding and capturing vision
Natural Language Processing
Language comprehension and interaction
Smart Robotics
Environmental manipulation
Digital Virtual Agents
Digital personal assistants
Autonomous Vehicles
Autonomous Driving
Machine Learning Vision Speaking and listening
Feel and act Decision and Knowledge Navigate through complex environments
▪ Learning based on specific
results without the need for
specific programming
▪ Use and transfer of existing
knowledge to new problems
▪ Visual recording of the
environment on e.g. pictures
▪ Evaluation and understanding
of objects based on visual
information
▪ Understanding of written or
spoken words
▪ Evaluation and drawing of
conclusions based on linguistic
interaction
▪ Manipulation of the environment
using mechanical systems such as
gripper arms
▪ Recording and evaluation of
interactions with the environment of
the system
▪ Support and adaptation to
individual needs and
preferences
▪ Assumption of simple tasks
▪ (Partially) autonomous
control and navigation
▪ Reaction to dynamic
changes
Field of application
Description
AI Technology
Field of application
Description
AI-Technology

4. Potentials and chances through artificial intelligence have either evolutionary or
disruptive character and involve products, business models and processes.
3
Artificial Intelligence – Potential and chances
Source: Mücke Sturm Company; 1 CX – Customer Experience
Evolution Disruption Evolution
▪ Increase of transparency using AI
▪ Increased efficiency through
mechanization or automation
▪ Replacement of repetitive work
(where possible)
▪ Use of AI for new or higher
revenues
▪ Creation of competitive
advantages through innovative
business models
▪ Enabler for higher efficiency in
existing business models
▪ Use of artificial intelligence for e.g.
personalization or
individualization of products
▪ Creation of new interaction
possibilities for the customer with
the product
Products Business models ProcessesBusiness area
Potential &
chances
selection
Focus
indicative
Improvement CX1 New Revenues Increased Effectiveness
High-level
Goals
indicative

5. The successful approach of chances and potentials of AI depend on the business
direction & certain aspects which need to be considered during the introduction.
4
Challenges of implementing the first AI projects
Alignment of AI projects
Success
story
Lighthouse
pilots
HighLow
HighLow
Outlay
Infrastructure, data, abilities, skills, etc.
Scalability
Extensibility,modularity,adaptability,etc.
Question mark
projects
Guarantee for
frustration
?
Important steps for AI projects
Selection
Fail Fast
Willingness to experiment. Fastest possible validation or
falsification of ideas based on data.
Fail Fast
Convey your vision and strategy
Definition and communication of your AI vision and strategy;
inclusion and collection of all relevant stakeholders.
Convey your vision and strategy
Empower your organisation
Adaptation of organization, teams and infrastructure to be
able to implement AI.
Empower your organization
Source: Mücke Sturm Company

6. Mücke, Sturm & Company GmbH
Head Office Munich
Theresienhöhe 12 T +49 89 461399 0
80339 München F +49 89 461399 777
Germany
5
Matthias Mainone
Munich
www.muecke-sturm.de
Associate Partner
m.mainone@muecke-sturm.de
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