The document discusses the business case for applied artificial intelligence. It covers how AI can enhance enterprises and how to build successful AI ventures. Specifically, it notes that global AI business value is forecast to reach $3.9 trillion by 2022. It then discusses how to introduce AI in enterprises, including defining objectives and benefits. It also outlines challenges of AI introduction. Additionally, it provides a framework for successful AI startups with factors around value creation, implementation, and competitive positioning. The document concludes by discussing implementation aspects like machine learning canvases and technical debts, as well as ethical considerations around issues like bias, privacy, and accountability.

1. Business
Case for
Applied AI
THE BUSINESS CASE FOR APPLIED
ARTIFICIAL INTELLIGENCE
How to enhance the enterprise with AI
&
How to build successful AI ventures
Ottó Werschitz

2. Business
Case for
Applied AI
Global AI Business Value
 Global Artificial Intelligence Business Value to Reach $1.2 Trillion
in 2018
 This is an increase of 70 % from 2017
 AI-derived business value is forecast to reach $3.9 trillion in 2022
Source: Gartner
 AI Startup funding reached $ 15 Billion in 2017
 AI funding grew at CAGR 83% between 2012 - 2017
 AI startup exits (acquistion and IPO) grew at CAGR 39% between
2012 - 2017
Source: Gartner
Source: Venturescanner

3. Business
Case for
Applied AI
Contents
1. AI in the enterprise
2. AI startup
3. Implementation aspects
4. Ethical considerations

4. Business
Case for
Applied AI
How to introduce AI in the
enterprise

5. Business
Case for
Applied AI
AI In The Enterprise
AI application areas
Source: O’Reilly

6. Business
Case for
Applied AI
AI In The Enterprise
Challenges of AI introduction and operation
Source: O’Reilly

7. Business
Case for
Applied AI
AI In The Enterprise
Source: Monica Rogati, Data Science Advisor, published on Hackernoon

8. Business
Case for
Applied AI
AI In The Enterprise
Define the AI business objectives, users, benefits
1. business task / problem the AI handles, e.g.
churn, fraud detection
2. what is the overall value added (revenue /
cost )
3. who are the enterprise - internal users, e.g.
customer service, SCM, etc.
4. who are the external users / beneficiaries, e.g.
subscribers, buyers, etc.

9. Business
Case for
Applied AI
AI In The Enterprise
Successful AI implementation:
1. managed
2. resilient
3. performant
4. measureable
5. continuous
Source: Dinesh Nirmal of IBM published on Venturbeat

10. Business
Case for
Applied AI
How to build a successful AI
startup

11. Business
Case for
Applied AI
AI Offering Overview

12. Business
Case for
Applied AI
Successful AI Startups
The MMC Ventures AI Investment Framework
Created for applied AI startup ventures
Based on 17 sucess factors in 3 domains
1. Value Creation
2. Value Realisation (Implementation)
3. Defendability (Positioning – Sustainable
Competitive Edge)
Source: David Kelnar, Partner and Head of Research at MMC Ventures

13. Business
Case for
Applied AI
Successful AI Startups
The MMC Ventures AI Investment Framework
Source: David Kelnar, Partner and Head of Research at MMC Ventures

14. Business
Case for
Applied AI
Successful AI Startups
The MMC Ventures AI Investment Framework
Source: David Kelnar, Partner and Head of Research at MMC Ventures

15. Business
Case for
Applied AI
Successful AI Startups
The MMC Ventures AI Investment Framework
Source: David Kelnar, Partner and Head of Research at MMC Ventures

16. Business
Case for
Applied AI
Successful AI Startups
Data: an asset to defendability
Success in AI
1. Algorithm / model
2. Talent (AI and domain expertise)
3. Data
Source: Louis Coppey, VC @ pointninecap
* Data

17. Business
Case for
Applied AI
Successful AI Startups
Data: an asset to defendability – positioning options
Source: Louis Coppey, VC @ pointninecap

18. Business
Case for
Applied AI
Implementation Aspects
ML Canvas
Technical Debts
UX

19. Business
Case for
Applied AI
Machine Learning Canvas
Source: Louis Dorard, www.louisdorard.com

20. Business
Case for
Applied AI
Machine Learning Canvas

21. Business
Case for
Applied AI
Technical Debt
1. Code debt (as with any other software)
2. Data debt such as threat of correlation
changes, unforeseen surprises or unstable
data
3. Math debt: the more complex the model
you have built, the more difficult to
understand and maintain it
4. Platform debt
Source: O’Reilly

22. Business
Case for
Applied AI
UX Aspects
Human Centered Machine Learning (Google UX
community)
 Don’t expect Machine learning to figure out
what problems to solve
 Ask yourself if ML will address the problem
in a unique way – Is ML really needed?
 Fake it with personal examples and wizards
 Weigh the costs of false positives and false
negatives
Source: Josh Lovejoy and Jess Holbrook @ Google Design

23. Business
Case for
Applied AI
Etchical Considerations

24. Business
Case for
Applied AI
AI Ethics
„The greatest threat that humanity faces from artificial
intelligence is not killer robots, but rather, our lack of
willingness to analyze, name, and live to the values we
want society to have today.”
(John C. Havens: While We Remain)

25. Business
Case for
Applied AI
AI Ethics
Some issues to consider (not a full picture)
1. Bias in decision-making (on the basis of biased
datasets)
2. Impact on human behaviour and interaction
3. Artificial Stupidity (mistakes by machines)
4. Security – keep it safe from adversaries
5. User Data
Source: World Economic Forum

26. Business
Case for
Applied AI
AI Ethics
What to require from AI-based systems which augments
or replace human judgement and work tasks?
AI-based decisions should to be transparent.
AI-based decisions should be explainable.
AI actions should be predictable.
AI system must be robust against manipulation.
AI decisions should be fully auditable.
Clear human accountability for AI actions must be
ensured.
Source: The Cambridge handbook of artificial intelligence, quoted by Kim Larsen in
https://aistrategyblog.com/2018/05/31/human-ethics-for-artificial-intelligent-beings/

27. Business
Case for
Applied AI
Thank you