1. Definition and History
- Igniting Forces: ICT, GPT – Information Communication Technology, General Purpose Technology, Metcalf’s & Moore’s Law
- Related Concepts: Machine learning, Deep learning, Neural networks, Big Data, Robotics, Singularity, Superintelligence, Internet of Things, Weak vs Strong AI, Symbolic vs Subsymbolic AI
- How Corporations React? Use Cases vs Strategies, IT vs AI, ROI of AI, KPIs, Cultural Challenges, Skill Challenges, Speed of Change
2. Managing AI: Turning Challenges into Opportunities
- The Data Challenge: Data Drives AI, Data Science, Big Data, IoT, Data as an Asset, APIs (Application Programming Interfaces)
- Predictive AI: New Data Sources, New Competitors, Why We Buy
- Managing Machine Learning: Optimization, Networks, Regression, Speech, Cluster, Video, Text, Image, Recommend, Predict, Classify
- Preparing the Workforce: Hybrid Models, Machines and Humans working together, best practices from Budweiser to Commerzbank
- Mistakes to Avoid: AI vs Legacy IT, Efficiency vs Disruption, The Efficiency Mirage, Lack of Ecosystems, Digital Convergence
- Case Study: Stitch Fix: Your Online Personal Stylist from SV
3. The Big Picture: Fundamental Trends in AI to Follow
- New Industries Born: Climate, DNA, Platform Economy, P2P
- Strategy by Machines: Machines that Design Strategy
- Expectations Management: AI Investment, The Red Queen Effect, Ambitions, Training, Make vs Buy, AI Leaders, 6 HR Effects by BCG
- Digital Confidence: Tech Skills, Cross Industry Skills, Serving and Employing Millennials, The Loyalty Conundrum, Machines as Colleagues, Administration vs Judgement
4. Innovation Tactics and Strategies, Next Steps, Summary
- Key Tactics: Venture Capital Funds, Accelerators, Incubators, Labs, IBM AI M&A, Deloitte and Kira Systems, McKinsey Solutions
- Key Strategies: Christensen, Ambidextrous, Toyota, TRIZ, H1,2,3
- Summary of Training: Key Concepts, Resources, Tools, Trends, ‘To Do’s, Feedback
Stephen Hawking: “AI will be either best or worst thing for humanity”.
This TRAINING PROGRAM provides managers with the ability to see through AI in a way that helps their organization win it. Paraphrasing the eternal genius Stephen Hawking, we can say: ‘AI will be either best or worst thing for our company’.
This course provides four key tools for AI Management:
(1) It summarizes and structures state of the art management paradigms related to AI: Harvard, MIT, McKinsey, BCG, Deloitte, Accenture and more.
(2) It places AI Management into a wider picture: Key innovation management tactics and strategies are being introduced.
(3) It provides definition of key expressions and concepts related to AI, Machine Learning, Data and beyond – necessary for meaningful boardroom discussions.
(4) It introduces key forward-looking trends within AI: Data as an Asset, Predictive AI changing consumer decisions, Digital Convergence, Machine Driven Corporate Strategy, Building ‘Digital Confidence, The Red Queen Effect
AI Divides technology experts. Some think it is dangerous, some believe it is the new electricity. In business we have to be prepared either ways.