Hans-Christian Boos, CEO and Founder, arago

1. Chris Boos
26 Sept. 2015
AI as Game Changer –
How Blue Chips Can Survive in a Digitized World

2. The History of Industrialization
First Industrial Revolution Second Industrial Revolution Third Industrial Revolution

3. The Economic Food Chain

4. …ArmamentAgriculture
The World as It Was a Long Time Ago

5. …AutomotiveFinance
The World as It Was only Yesterday

6. The World as It Is Today

7. Examples of Tangible Disruption
• Introducing Google car reduces the need for
new cars by 70%
• Facebook’s production cost for a retail
banking account would be 98% cheaper than
any pure online bank’s
• Quantum computers such as D:WAVE’s can
potentially substitute the entire IT hardware
industry

8. Consumers Using
New Business Models
Was the Beginning
of the Change Cycle.

9. Information
Speed:
Twitter has shortened the news cycle by 80%
Reach:
Everybody is a journalist
Cost:
Why pay for ads if you can get
the same reach for free

10. Entertainment
Medium:
CD/BlueRay were the
moneymakers, then came MP3/MP4,
now it‘s streaming
Ownership:
Streaming is the new owning
Commercialization:
Artists are businesses – no longer the song
sells, but concerts and merchandise

11. Transportation & Travel
Business model:
• The sharing economy is taking over
• Pricy infrastructure no longer is an asset
Regulation:
The UBER Case might become blue print
for how a regulated market is being replaced
Platforms:
Proofs the platform trend

12. IT Infrastructure
Entry barrier:
Owning a data center with adequate
connectivity, good security and computing
power used to be a huge investment
Access:
Today, all this is available on demand and
at low prices to anyone

13. In the 2nd Part of the
Change Cycle High-Tech
Is Moving into All
Business Models.

15. For Businesses,
Change Is No Longer Optional.

16. What‘s Holding Back?
The Disadvantages of Blue Chip Companies

17. Operational Spend
70% 30%
operations
keeping the lights on
job preservation
change
redoing business
reinvention
20% 80%Tech leader
Blue Chip

18. Brain Drain
?

19. “[…] successful, outstanding
companies can do everything
‘right’ and yet still lose their market
leadership – or even fail – as new,
unexpected competitors rise and
take over the market.”

20. Legacy Thinking
„We‘ve always
done it like that …“

21. How to Catch on …

22. Legacy Thinking
… goes with market
pressure: If you are
desperate, you are
willing to do the
unthinkable!

23. … goes with legacy thinking,
because that is what keeps
businesses from thinking out of
the box.

24. … leaves two to go ...

25. How Automation Can Help

26. Lower costs
Free up minds for
innovation
Retain knowledge

27. Automation Is Not Economies of Scale,
It Is ARTIFICIAL INTELLIGENCE
and that Is Good for People.

28. Industrialization Means
Making Smart People Work like Dumb Machines …

29. … and Then Replace Them with Dumb Machines.

30. Artificial Intelligence Means
Making Machines Work like Smart People

31. A B
Result: Only one problem solved
This Is the Way Machines Solve a Problem

32. This Is the Way Humans Solve a Problem
A B
Result: Multiple problems solved
ambigious
input
wrong input
changing
assumptions
incomplete input

33. If People Teach Smart Machines,
This Is What Smart Machines Can Do
A B

34. AI Can Do for Experts What eCommerce Did
for the Mom & Pop Store.

35. Extend Reach thus Market

36. Give Acknowledgment to People

37. Increase Value

38. arago’s Example from IT Operations:

39. AI Based Automation
Extension of Applicability
Industrialized Automation
OS
database
SAP network
vs.

40. 3 Month Learning Curve

41. Business Case
Case study on a 3 year operating
budget:
Before 356M€
After 191M€
Savings 46.34%
Business case on traditional
automation was 8,14% savings
Examples from IT Operations:
before traditional new
Storage 50,79 50,79 26,84
Backup 68,68 68,68 43,63
Compute (incl. NW) 69,93 69,93 28,80
OpSys 30,88 30,88 5,98
Database 15,29 15,29 9,29
Middleware 21,14 21,14 13,81
Manpower 48,28 33,80 24,27
Special Bids 51,62 36,13 38,08
Total Mn € 356,61 326,64 190,70
before traditional new
Storage 50,79 50,79 26,84
Backup 68,68 68,68 43,63
Compute (incl. NW) 69,93 69,93 28,80
OpSys 30,88 30,88 5,98
Database 15,29 15,29 9,29
Middleware 21,14 21,14 13,81
Manpower 48,28 33,80 24,27
Special Bids 51,62 36,13 38,08
Total Mn € 356,61 326,64 190,70

42. Too few engineers,
machines can multiply humans
Best engineers in blue chip
economy busy in operations
Experts in operations would
prefer doing new things
Community gives
acknowledgement to people who
teach machines
Instead of making them leave,
businesses save money and
have competence on board
Marketplace for knowledge of
smaller teams of experts in
community
Why We Applied our Technology
to IT Operations

43. This Is Only the Beginning and It Is
a Huge Opportunity …

44. We at arago Have Shown that AI Can Be a
Win-Win Situation for People and Companies.

45. To Make This Generally True,
Change Needs to Happen.

46. Change Not Just in Policy, Technology etc. But in
Enterprise IT and Perception.

47. Thank you for your time which we hope was well invested,
because dismissing good ideas can harm your future