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The Business Case for Applied Artificial Intelligence
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.
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The Business Case for Applied Artificial Intelligence
- 1. Business Case for Applied AI THEBUSINESS 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 GlobalAI 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 Howto introduce AI in the enterprise
- 5. Business Case for Applied AI AIIn The Enterprise AI application areas Source: O’Reilly
- 6. Business Case for Applied AI AIIn The Enterprise Challenges of AI introduction and operation Source: O’Reilly
- 7. Business Case for Applied AI AIIn The Enterprise Source: Monica Rogati, Data Science Advisor, published on Hackernoon
- 8. Business Case for Applied AI AIIn 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 AIIn 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 Howto build a successful AI startup
- 11. Business Case for Applied AI AIOffering Overview
- 12. Business Case for Applied AI SuccessfulAI 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 SuccessfulAI Startups The MMC Ventures AI Investment Framework Source: David Kelnar, Partner and Head of Research at MMC Ventures
- 14. Business Case for Applied AI SuccessfulAI Startups The MMC Ventures AI Investment Framework Source: David Kelnar, Partner and Head of Research at MMC Ventures
- 15. Business Case for Applied AI SuccessfulAI Startups The MMC Ventures AI Investment Framework Source: David Kelnar, Partner and Head of Research at MMC Ventures
- 16. Business Case for Applied AI SuccessfulAI 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 SuccessfulAI Startups Data: an asset to defendability – positioning options Source: Louis Coppey, VC @ pointninecap
- 18. Business Case for Applied AI ImplementationAspects ML Canvas Technical Debts UX
- 19. Business Case for Applied AI MachineLearning Canvas Source: Louis Dorard, www.louisdorard.com
- 20. Business Case for Applied AI MachineLearning Canvas
- 21. Business Case for Applied AI TechnicalDebt 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 UXAspects 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 EtchicalConsiderations
- 24. Business Case for Applied AI AIEthics „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 AIEthics 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 AIEthics 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/
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