IT Trends Reports 2016

IT Trends Reports 2016

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Description: Those who identify the potential of new technologies, trends and technological progress at an early stage will obtain a competitive advantage and build the foundation for innovation. Constantly increasing technological complexity leads to a growing number of areas that are relevant for our company to keep an eye on. The objective of the IT Trend Radar 2016 is to identify relevant new technologies for ERGO, MunichRE, and MEAG and evaluate them from a group perspective.

We focus on the innovation potential of individual trends and review their practical suitability for the reinsurance and primary insurance sector. The purpose is to provide a better understanding of trends & correlations and to strategically support the product development. The team heading the Trend Report would be pleased to advise and assist with further analysis and workshops.

 
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Contents:
IT TREND REPORT

2016

INTRO

Those who identify the potential of new technologies, trends, and technological progress at an early stage will obtain a competitive advantage and
build the foundation for innovation. Constantly increasing technological
complexity leads to a growing number of areas that are relevant for our
company to keep an eye on. The objective of the IT Trend Radar 2016 is
to identify relevant new technologies for ERGO, MunichRE and MEAG
and evaluate them from a group perspective. We focus on the innovation
potential of individual trends and review their practical suitability for the
reinsurance and primary insurance sector. The purpose is to provide a
better understanding for trends & correlations and to strategically support
the product development. The team heading the Trend Report would be
pleased to advise and assist with further analysis and workshops.

Tom Bonaty
Contact Munich RE

Roland Braun
Contact ERGO

IT Trend Report 2016 - Bonaty / Braun

2

CONTENT

Intro 
2
Content 
3
IT Trend Radar 2016 
4
Overview Trends / Infographic 
6
1 Algorithmic Business 
8
2 Blockchain Technology 
10
3 New Payment Models 
12
4 Internet of Things 
14
5 Advanced Machine Learning 
16
6 Smart Home 
18
7 Digital Health Services   20
8 Information of Everything 
22
9 Autonomous Agents 
24
10 3D Printing Materials 
26
Contact 
28

IT Trend Report 2016 - Bonaty / Braun

3

IT TREND RADAR 2016

IT Trend Radar 2016

Munich Re (IT Governance) and ERGO (IT Strategy) in cooperation

Continuously providing insights of key trends that influence business at Munich Re and ERGO

with the Institute of Electronic Business gathered future trends

Promoting innovative initiatives within Munich Re and ERGO based on trends and developments from the outside

The Trend Radar provides information about technology driven

outside of ERGO and aggregated them in the Trend Radar 2016

Intensifying collaboration and interaction between Munich Re and ERGO

trends relevant for Munich Re and ERGO. It is a collaborative

in order to provide a comprehensive view on technology trends,

i
­nitiative by Global IT Governance at Munich Re and ERGO IT

their maturity and relevance for Munich Re and ERGO. This year

Strategy. It aims at sharpening awareness, evoking discussion

is directly involved in the initiative for the first time also MEAG IT.

and initiating new business opportunities appealing to all units

The top trends of the Trend Radar are published in the Trend

in both Munich Re and ERGO.

Report 2016.

Quantum Computing new!

Algorithmic
Business new!

3D Printing Materials
Ambient User
Experience new!

Loc-based Services
Autonomous
Vehicles

Artificial General
Intelligence new!

Industrialization 4.0
Augmented and
Virtual Worlds

Smart Machines
Smart Dust new!
Information of
Everything new!

Advanced
Machine Learning
new!
Blockchain Technology

Context-aware
Computing

Autonomous
Agents

Hold

(Watch list)

Assess

(Evaluation
needed)

Trial

Cybersecurity

Predictive
Analytics

Web-Scale IT
Smart Home

Adopt

(Start initiatives
in your unit!)

Data driven
Decisions

Wearable
Devices

Digital Health
Services

Internet of Things

(Initiatives in
affected units)

Crowd
Sourcing

Collaborative
Consumption

Robotics/Drones

The Device Mesh

Telematics
Digital Identity

Haptic Technologies

Cloud/Client
Architecture

New Payment Models

Web 5.0
Adaptive Security
Architecture

Open Data
Digitalization
User Centered
Design

Adopt

Trial

Assess

IT Trend Radar 2016 - Bonaty / Braun

Hold
IT Trend Report 2016 - Bonaty / Braun

3 März 2016

1

5

OVERVIEW TRENDS / INFOGRAPHIC

10 3D Printing Materials

9 Autonomous Agents

8 Information of Everything

7 Digital Health Services

3D fabricating is a process to make three-­ imensional solid
d
o
­ bjects from a digital model

Virtual personal assistants such as Apple‘s Siri or Google Now
are part of the ambient user experience, instead of interacting
with buttons and menus, users can speak to an app

everything in the digital mesh produces, uses and transmits
information – including sensory and contextual information:
information analysis techniques bring meaning to the deluge of
information

describe the opportunity for remote monitoring of users’ health
status through smartphones, wearable devices and apps

$49.000.000.000

$19.000.000.000.000

$5.400.000.000

global opportunity to create value in the next
decade3

predicted global revenues from connected
f
­ itness trackers alone – in 20164

projected global market for 3D printers and
services in 20251

32%

3 New Payment Models

4 Internet of Things

5 Advanced Machine Learning

6 Smart Home

mobile payment is becoming a billion dollar industry, all major
tech companies have developed mobile payment services; whereas virtual currencies don’t have a legal status or guarantee in
any jurisdiction

miniscule sensors are attached to objects to make them
identifiable by their own unique IP address, to autonomously
communicate with one another and provide information

the science of getting computers to act without being explicitly
programmed

highly connected and automated home technology: household
systems are digitally connected and enable monitoring and
control from afar – at the office, on vacation etc.

$3.700.000.000
Global financing amount invested in mobile
payments startups in 20158

expected annual growth rate
in the global virtual assistant
market 2015 – 20222

$28.100.000.000
IoT units expected to be installed in 20207

2 Blockchain Technology

1 Algorithmic Business

decentralized verification system for transactions of all types
that are recorded across a multitude of computers around the
world

a company built around smart algorithms – soon these
a
­ lgorithms will be able to work independently, define business
p
­ rocesses and predict possible threats.

$1.000.000.000

invested in Bitcoin related tech startups by companies
such as AmEx, Bain Capital, Deloitte, Goldman Sachs,
Mastercard and the New York Life Insurance Company 9

98%

of insurance executives familiar
with cognitive computing believe
that it will play a disruptive role
in the industry6

29%

expected annual growth rate
of revenue in the smart home
market5

Sources
1) http://www.smitherspira.com/products/market-reports/printing/the-future-of-3d-printing-to-2025
2) http://www.transparencymarketresearch.com/pressrelease/intelligent-virtual-assistant-industry.htm
3) http://www.weforum.org/agenda/2014/01/are-you-ready-for-the-internet-of-everything/
4) http://www.parksassociates.com/blog/article/pr-march2015-whcc

$60.900.000.000

5) http://www.statista.com/outlook/279/100/smart-home/worldwide#market-revenue

projected global sales volume of Big Data
Solutions in 202010

8) https://www.cbinsights.com/blog/payments-tech-funding-statistics-and-growth/

6) http://www-01.ibm.com/common/ssi/cgi-bin/ssialias?infotype=PM&subtype=XB&htmlfid=GBE03710USEN
7) http:// www.idc.com/downloads/idc_market_in_a_minute_iot_infographic.pdf
9) http://money.cnn.com/2015/11/02/technology/bitcoin-1-billion-invested/
10) http://wikibon.com/executive-summary-big-data-vendor-revenue-and-market-forecast-2011-2026/
IT Trend Radar 2016 - Bonaty / Braun

7

1 ALGORITHMIC BUSINESS
Algorithms are the DNA of software. They codify the macro steps
of how computers already run large parts of the world.
The ‘Algorithmic Business’ is a term describing companies that
build their business models around smart algorithms. These algorithms turn data into actions and insights about consumers.
For that it needs a new system architecture of information classification and semantics.
In the digital future these algorithms are able to work independently, define business processes, create a differentiated
c
­ ustomer experience and predict possible threats. Therefore,
a
­ lgorithmic business models require target-oriented and self­
optimizing algorithms (see: Advanced Machine Learning).
According to Gartner, by 2018 already 20% of all business

50%

of the fastest
growing companies

will have fewer employees

than smart machines by 2018.
Source: Gartner, 2015

$60.9 billion

projected global sales volume
of Big Data solutions in 2020.
Source: Executive Summary: Big Data Vendor Revenue and Market Forecast, 2011-2026

c
­ ontent will be authored by machines.

IT Trend Report 2016 - Bonaty / Braun

8

Examples and Initiatives

Amazon algorithm is the recommendation engine of Amazon,
based on „item-to-item“ collaborative filtering. It is rumored to

BENEFITS

provide 10% to 15% of additional revenue on Amazon.com.

B
 etter, fast and independent decisions by automated
analytical processes.

Kreditech is a “digital bank“ that provides customtailored

I
ncreased efficiency for organizations and employees
through Advanced Analytics and cost savings.

f
­ inancial products based on algorithmic banking. The data-driven

D
 ynamic and individual customer services.

tech­ ology offers its customers a high convenience through fully
n

Focus on actionable algorithms and meaning of data
instead of amounts of data.

o
­ nline integrated business processes. Founded in 2012, the company raised $92 million in the latest Series C round with PayPal
co-founder and early Facebook ­nvestor Peter Thiel being one of
i
the leading investors.

CHALLENGES
R
 equirement to leverage information sources to drive
growth as part of their information strategy.
B
 y trend, algorithmic business relies on gaining further
insights from data in order to predict customer behavior,
trends and/or outcomes.
I
nformation management becomes a key requirement for
innovation within rapid information processing.

Kreditech digital banking services
in comparison to a traditional bank
(Source: kreditech.com)

Amazon algorithm: recommendation engine,
2016

IT Trend Report 2016 - Bonaty / Braun

9

2 BLOCKCHAIN TECHNOLOGY
Blockchain technology provides a shared, trusted and secure

The idea has already been in use for Bitcoin. A total of US$ 1

public ledger to record financial transactions / digital assets and

billion has been invested already in Bitcoin-related tech start-ups

‘smart contracts’. These are recorded independently – not in one

by companies such as American Express, Bain Capital, Deloitte,

place but distributed across a multitude of computers around the

Goldman Sachs, Mastercard, the New York Life Insurance Com-

world. The records are condensed (into blocks) and interlinked

pany and the New York Stock Exchange. As demonstrated in

(to form chains), using complex cryptographic algorithms.

Gartner’s Hype Cycle for Emerging Technologies cryptocurrency
exchange are expected to reach the plateau of productivity wit-

Thus Blockchain records are locally decentralized in a peer-to-

hin 2 to 5 years (see fig. X).

peer network but still constitute a logically centralized immutable set. No central authority or trusted third party is required to
secure transactions.

Gartner Hype Cycle for Emerging Technologies (Source: Gartner; August 2015)
IT Trend Report 2016 - Bonaty / Braun

10

Examples and Initiatives

Nasdaq is testing a new use of blockchain transaction technologies for the stock markets in favor of creating a more secure and
efficient stock trading system. Potentially, the transfer can be
provided without fearing manipulation by third parties. By introducing the blockchain to the trading of financial assets, Nasdaq
aims to replace the verification process previously done manually
by lawyers through a more secure technology.
Blockverify provides a blockchain-technology-based solution
to track products along the supply chain. By implementing the
blockchain technology in this sector, companies are provided
with a transparent environment that makes it impossible to
d
­ uplicate products. Further, companies can create a product
register, monitor supply chains and identify counterfeit ­products.

BENEFITS
A
 dvantages of a blockchain ledger lie in the verification of
portfolio data between primary and reinsurance.
A
 utomated smart contracts or transactions become
frictionless and can be processed more quickly with less
bureaucracy (e. g. identity validation).
C
 hance for new insurance models emerge: peer-to-peer
insurances or smart policies (e.g. automatic pay-outs
based on a climate data feed for crop insurances).
CHALLENGES
D
 ecentralization of insurances (e. g. peer-to-peer models,
mutual insurances): The competition can increase with
non-insurance players that could employ the blockchain
technology for new insurance models, which requires
early adoption of the technology.
I
nsurances have to figure out use cases for blockchain
technology as an integral part of their future IT strategy.

Nasdaq is testing bitcoin technology
(Source: The Wall Street Journal, 2015)

Blockverify features (Source: blockverify.io)

IT Trend Report 2016 - Bonaty / Braun

11

3 NEW PAYMENT MODELS
Mobile payment refers to the function of making payments with

An emerging trend is instant payment. instant payment refers to

one’s smartphone or other wearable smart devices. According to

a electronic payment solution that enables users to carry out

Gartner, the projected number of mobile payment users will

authorized transaction in real-time. Especially cross-border

exceed 450 million by 2017.

instant payment is a rising trend with huge market potential

With the mobile payment sector becoming a billion dollar industry, all major tech companies have developed mobile payment
services for their customers. Moreover, new players are entering
the market, e.g. utilizing virtual currencies such as Bitcoin. Virtual currencies are a type of digital money which is created and
controlled by its developers.

$2849 billion

Projected global mobile

transaction market in 2020.
Source: Future Market Insights, 2015

$3.7billion
Global financing amount
invested in mobile payments startups in 2015.
Source: CB Insights, 2015

Source: visa.com

12

Examples and Initiatives

MobiKwik is a digital wallet that was developed for various mo-

BENEFITS

bile transactions scenarios, e. g. paying in online shops, transfer-

T
 he reduction of physical payment generates more and
better data of consumer payment habits.

ring money to a friend or paying one’s life insurance.

N
 ew payment models create new insurance products, i.e.:
protection of your online wallet.

Founded in 2009, the Indian start-up already has more than 25
million users together with a retail network of 50.000 partners

Reduced response time for claims process and other
insurance related services

and processes ca. 60 million mobile payment transactions per
month.

M
 obile payment provides users a faster and more
comfortable way to pay for online services, i.e. on
demand insurances.

Square is a mobile payment company that offers Point-of-Sale
Software for every part of a running business, e.g. credit card
processing, sales monitoring, inventory management and creation of sales reports.

CHALLENGES

The company cooperates with Navy Federal, Creditera, Gravity
Payments, Starbucks and Whole Foods among others.

I
nsurance companies can be placed at a competitive
disadvantage by the inability to adapt to mobile payment
technologies.
N
 ew transaction processes create new security vulnerabilities and data privacy uncertainties.

MobiKwik App
(Source: mobikwik.com)

Square Dashboard (Source: squareup.com)

IT Trend Report 2016 - Bonaty / Braun

13

4 INTERNET OF THINGS

The ‚Internet of Things’ is becoming a buzzword and the techno-

daily consumer objects, enable information gathering and ma-

logy trend with repercussions across the business spectrum. By

nagement of these devices to increase efficiency, new services or

connecting to the internet, billions of everyday devices – from

achieve other health, safety or environmental benefits.

fitness bracelets to industrial equipment – the Internet of Things
merges the physical and online worlds, opening up a new oppor-

The IoT is also a relevant field for many other trends e. g. Smart

tunities and challenges for companies and consumers.

Home, Healthcare and Fitness Tracking (quantified self) – and
the Industrial Internet of Things (Smart Factory, “Industry 4.0”).

The vision of the Internet of Things (IoT) is to connect devices and

$7,065 billion

market revenue in 2020

28.1 billion
IoT units in 2020
(Source: IDC, 2015 )

$2,712 billion

market revenue in 2015

(Source: IDC, 2015)

In 2020, there will exist

a black market for

fake sensor & video data

$5

valued at over

14

billion
(Gartner 2016)

Examples and Initiatives

Lumkani’s smart alert

BENEFITS

Lumkani’s early-warning system of connecting smoke detectors to
reduce damage by shack/slum fires in urban settlements

N
 ew services can emerge such as remote health monitoring for elderly patients and pay-as-you-use services.

Grillo: a sensor system detecting earthquakes

R
 educed loss costs, claims and expenses and dynamic,
optimized pricing in insurance products.

Grillo measures data through IoT technologies, sends geo-located
alerts to people all over the world.

I
ncreased availability and quality of more consumer data,
enabling more customization and (micro) targeting.
CHALLENGES
C
 urrent lack of standards.
P
 rivacy and security concerns move into focus.
R
 equire a shift from reactive restitution to proactive
protection and prevention and to repeated interactions
(life cycle).

Source: lumkani.com, 2016

Source: Grillo App, 2015

IT Trend Report 2016 - Bonaty / Braun

15

5 ADVANCED MACHINE LEARNING

Machine-based learning is described as the science of getting
computers to act without rules-based programming. One of the
goals in this field is the replication of cognitive capabilities of the
human brain and the development of algorithms / computer

98%

of insurance
executives familiar
with cognitive computing

programs that teach themselves.

believe that it will play a

Technologies based on machine learning will be able to not only

Source: IBM Institute for Business Value, 2015

disruptive role in the industry.

collect data, but learn based on the data. Through this process
much of the initial analysis prior done by humans will switch to
being completed by machines.
Advanced Machine Learning uses new data in order to improve
programs and adjust program actions according to recognized
patterns in new data. Advanced Machine Learning is related to
the trends Algorithmic Business and Autonomous Agents.

$13.7billion
Expected global cognitive
computing market 2020.
Source: Allied Market Research, 2015

IT Trend Report 2016 - Bonaty / Braun

16

Examples and Initiatives

The Artificial-intelligence system Quill provides data-based
intelligent storytelling narratives by generating natural language
t
­hrough data analysis. The sys-tem is able to write reports in seconds with a quality of a human author using data from specific
data sources.
How Quill Works (Source: narrativescience.com)

Osaro Website (Source: osaro.com)

Osaro develops automation solutions for computer and robotic
systems driven by advanced machine learning software.

TensorFLow logo

TensorFlow is a machine-learning technology used in various
Google products such as Gmail, Google Photos, speech
r
­ ecognition and Search.
Recently Google open-sourced the framework for developers in
order to foster and accelerate research on machine learning.

BENEFITS
Automated data analysis & increasing effectiveness of process and products, including
D
 etection of more granular or predictive information
I
ncreased effectiveness of existing products
P
 rovision of deep insights for better risk assessment
R
 eduction of processing times and operational costs
I
mproved decision making

IT Trend Report 2016 - Bonaty / Braun

17

6 SMART HOME

Making homes “smart” is an emerging trend that has gone from

17%

Expected annual
growth rate for
the revenue in the smart home market.

button-press security systems to controlling and observing your
home from anywhere. Smart Home is a highly connected and
automated home. Not only computers are connected but also
machines and control centres for heating, cooling, lighting and

Forecast 2015-2020.

security are part of home networks.

Source: RnR Market Research, 2015

The idea of a Smart Home system is a seamless interaction to

$58.7billion

reduce human work and energy costs.
By 2022, the falling cost of adding sensing and communications

Expected market value

to consumer products will mean that a family home in a mature,
affluent market could contain several hundred smart objects.

of the global smart home market in 2020.

These will enable a wide range of new digital business oppor-

Source: MarketsandMarkets, 2015

tunities as well for the insurance market.

5%
10%
37%

10%

Smart appliances
Smart energy meters
Wearable devices

13%

Connected cars
Smart healthcare devices

25%

None of these

Connected devices likely to be used within the next five years.
Source: GSMA, KRC research, 2015

IT Trend Report 2016 - Bonaty / Braun

18

Examples and Initiatives

Digitalstrom: smart home system
Intelligent building automation system that connects existing
electronic devices and domestic lighting.

Nuki: smart bluetooth key
Nuki is connected to your door lock via Bluetooth. The door is
opened when the user returns home and closed after leaving.

Netflix “The switch”: smart home connector
Connects devices and gets the home ready for the “Netflix mode”
at the touch of a button (turns on the TV, dims the lights).

BENEFITS
D
 amage reduction and prevention for buildings and
household insurances: Smart Home applications provide
more safety using sensors to prevent dangers in early
stages leading to fewer claims for insurance companies.

CHALLENGES
D
 ata protection: hacking and security losses are relevant.
Also people might not want insurance companies to
know every last detail of their private lives.
D
 evelopment of a multi-layered security strategy.

S
 mart Home services enable new products especially in
the health care sector.
F
 lexible household insurance based on tracked application
data.
IT Trend Report 2016 - Bonaty / Braun

19

7 DIGITAL HEALTH SERVICES
Digital Health Services describe the opportunity for remote moni-

Diseases might be recognized at an early state as well as

toring of users’ health status through advanced smartphones

a
­ ccidents by elderly persons (especially if they’re living alone). As

and apps or smart wearables like smart watches.

a side effect home care becomes cheaper: people can continue

Doctors or health insurance funds have the opportunity to see

living a ­elatively independent life for a much longer time. And
r

the users’ condition in real-time. Digital Health Services allow to

new care products emerge, e.g. care robots can alleviate the care

monitor movement activity, ­ eartbeat, or sleeping activity.
h

burden of chronically ill persons’ family ­ embers.
m

$5.4 billion

More than

75%

Global revenues from

of all patients expect to

Source: Parks Associates

Source: McKinsey Digital Patient Study, 2014

connected fitness trackers by 2019.

use digital services in the future.

Global digital health market forecast 2020 (by segment).

$103.2
billion

$55.9
billion

$29.1
billion

$6.3
billion

Wireless health

Mobile health

EHR / EMR

Sources: Accenture; Allied Market Research; Arthur D. Little; GSMA Intelligence; HIS; MarketsandMarkets, 2014

Telehealth
IT Trend Report 2016 - Bonaty / Braun

20

Examples and Initiatives

Medtronic: Remote Monitoring System for patients with

BENEFITS

implantable pacemakers

Digital health services help to provide an efficient support
and more customer centricity, including

received FDA approval for its app-based system
e-Celsius: Performance health monitoring system

p
 revention of diseases, regeneration and support in case
of chronic diseases

uses a pill that measures body temperature and is able to store up

r
eal-time health records

to 80.000 data sets per pill.

s
 implification of complex business and clinical models
P
 atient control and access to health information

Evolent Health: sells software as well as advisory services, and
information technology to hospitals. The technology they use

L
 ower costs through better understanding the customers
needs

gathers and crunches relevant data about patients so that doctors can treat them better at lower costs.

CHALLENGES
O
 ngoing risk analysis and management is needed to
provide relevant and safe data (life cycle).

Source: evolenthealth.com
Meditronic
Source: Meditronicheart.com

E-Celcius
Spurce: Bodycap-medical.com

IT Trend Report 2016 - Bonaty / Braun

21

8 INFORMATION OF EVERYTHING

Information is the lifeblood of Digital Business. Information has
always existed everywhere but has often been isolated or unavailable. Nowadays through the Internet of Things we have a
huge amount of data that is not only nearly fully ­ ncompassing
e
but also potentially valuable.
The ‚Information of everything’ describes everything in the
d
­ igital mesh produces, uses and transmits information – including sensory and contextual data.
Graph databases as well as other emerging semantic data classification and information analysis techniques will bring meaning
to the often chaotic flood of information.
According to a report of the World Economic Forum, more than 5
billion people and 25 billion devices will be connected to the
i
­nternet, generating virtual amounts of information.

$19 trillion
Global opportunity to create value in
the next decade
Source: World Economic Forum, 2015

44 zettabytes

Projected volume of data in the digital world
Source: IDC, 2014

Source: Cisco, 2013
IT Trend Report 2016 - Bonaty / Braun

22

Examples and Initiatives

IBM Watson Health combines clinical, research and social data

BENEFITS

helping physicians gain insights from the data from medical

A better understanding of themselves and their customers
enables more purposeful and target-group-specific actions
including:

r
­ecords, research to fitness bands and provide patients with personalized treatment. The Watson Health Cloud brings together
medical data into one cloud-based thinking hub and combines

I
mproved business practices

traditional analytics with the advanced cognitive capabilities of

I
mproved assessment of risks

Watson to turn this data into knowledge about patients and

Individualized and nnovative customer products
i

­treatment methods.

R
 eduction of operational costs

The Legislative Influence Detector (LID) helps discovering insights about the origin and diffusion of policy ideas and the real
influence of various lobbying organizations. Since reading legislative bills manually takes quite a bit of time, LID users are provided
with the possibility of investigating text matches for large sets of
text. The algorithm checks the texts for similarities and returns
the best matches with a highlighted text for further review.

IBM Watson Health data sources (Source: Youtube.com)

Result of the Legislative Influence Detector analysis (Source: dssg.uchicago.edu)

IT Trend Report 2016 - Bonaty / Braun

23

9 AUTONOMOUS AGENTS

Autonomous smart agents or virtual personal assistants (VPAs)
are on the rise and are becoming a more sophisticated technology,
enhanced through (advanced) machine based learning.
VPAs such as Apple’s Siri or Google Now are part of the ambient
user experience, instead of interacting with buttons and menus
users can speak to a smart app, which is an intelligent agent.
Autonomous agents are on the verge of becoming a valuable asset
in the workplace as well as for personal purposes. In the near
f
­uture intelligent agents will be able to provide the users with
d
­ ynamic and contextual information and augment human activity.

$5.1 billion
Global virtual assistant market
volume forecast for 2022.
Source: Transparency Market Research, 2015

31.8%

Global virtual
assistant market

compound annual growth rate (CAGR) 2015 – 2022
Source: Transparency Market Research, 2015

24
Siri on Ios 9 (source: apple.com)

Examples and Initiatives

Apple Proactive is an intelligence technology implemented in its
latest iOS. The system provides the user with the most relevant

BENEFITS

information and suggests actions at a particular moment based

A
 utomation of coordinative tasks reduces failure rates and
saves time

on usage patterns i.e. most relevant contacts, launching your

O
 perational cost savings

yoga app for your morning workout or reminding you about

A
 utonomous agents work around your schedule to
provide you with services whenever you need them

s
­ omething when you get in your vehicle or display local news
based on your location.

T
 he collected data from Autonomous Agents contains
marketing relevant customer information

Amazon Echo is a voice activated personal assistant for the
connected home. It can be placed anywhere around the house
and processes human speech via a sophisticated voice
r
­ ecognition technology. The device runs on Amazon Web
S
­ ervices, offering various services like music streaming, radio or
programmable tasks using IFTTT.

Amazon Echo
Source: Amazon.com

CHALLENGES
R
 isk of insurance claims through technology failures with
more severe damages
P
 otential damages from uncontrolled data collection is a
major challenge for businesses

Proactive is a IOS 9 intelligence that supports the user by
predicting the context of use (Source: Youtube.com)

IT Trend Report 2016 - Bonaty / Braun

25

10 3D PRINTING MATERIALS

3D printing is a process of manufacturing three-dimensional solid
objects from a digital model.
These technologies have primarily been used in the field of
p
­ rototyping for industrial design. But nowadays, the quality of 3D
printing has vastly improved. Simultaneously, printer and supply
costs have dropped to a level that broadens the appeal of 3D
printing to a wide range of businesses, schools and private
c
­ onsumers. Also, 3D-printable material now includes human tissue, food, glass. This opens new markets!
Siemens predicts that 3D printing will become 50% cheaper and
up to 400% faster in the next five years.

$49 billion
Projected global market for 3D printers

and services in 2025.
Source: Transparency Market Research, 2015

+300%

Projected global market growth for 3D printing
technology in the next decade.
Source: Transparency Market Research, 2014

24,5%

Prototyping
Product development

16.1%

Innovation

11.1%

Figure X: the three most common reasons companies are pursuing 3-D printing (Source: Gartner; November 2014)

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Examples and Initiatives

Airbus has started using 3D printing, also called Additive Layer
Manufacturing (ALM) for tooling, prototyping and manufacturing
parts used in test flights but also in commercial aircraft, using the
technology for its new Airbus A350 XWB.
3D printed aircraft part (Source: airbusgroup.com)

NASA is using the 3D printing technology for printing tools
based on a design file which is transmitted from Earth to a 3D
printer at the ISS. Furthermore a NASA team is currently testing
a 3D printed high performance rocket engine under space-like
conditions.
3D printed Ratchet Wrench (Source: NASA)

Biobots was founded in 2014 by two graduates of the University
of Pennsylvania. Biobot 1 is a 3D bioprinter that builds 3D living
tissues out of human cells. The company has introduced the desktop 3D printer onto the market in 2015 at a competitive price of
$US 10,000.

BENEFITS
Q
 uick production of complex products with minimal lead
times

Desktop 3D printer from Biobots (Source: biobots.io)

CHALLENGES
A
 dded complexity to some supply chains

O
 n-demand customization

L
 iability concerning product quality in areas of biotechnology or pharmaceuticals

Q
 uick product tests

L
 egal issues of copyright infringement

U
 se of 100% of the raw material, leading to minimal, if
not zero, waste.

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Contact

Tom Bonaty

Roland Braun

Global IT Governance

IT ERGO, IT Strategy

E-Mail: TBonaty@munichre.com

E-Mail: Roland.Braun@itergo.com

In Cooperation with:

Institute of Electronic Business e.V.
Schlesische Str. 26
10997 Berlin
www.ieb.net
Prof. Dr. Dr. Thomas Schildhauer
Wissenschaftlicher Direktor
E-Mail: schildhauer@ieb.net
Theresa Schleicher
Wissenschaftliche Mitarbeiterin
E-Mail: theresa.schleicher@ieb.net
Claudia Nichterlein
Wissenschaftliche Mitarbeiterin
E-Mail: nichterlein@ieb.net

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