Mitch Johnstone

Writing

Essays on AI strategy, data and making better decisions.

The AI Strategy Framework

A field guide to building AI that actually pays for itself, one layer at a time: product vision, data collection, storage, transformation, analytics, machine learning and, at the top, AI.

  1. Part IIntroducing the AI Strategy Framework
  2. Part IICrafting a Compelling AI Product Vision and Narrative
  3. Part IIIData Collection - The Essence of AI
  4. Part IVEnsuring Reliable and Accessible Storage
  5. Part VData Exploration & Transformation
  6. Part VIAnalytics and Insights
  7. Part VIIMachine Learning - The Continuous Improvement Cycle
  8. Part VIIIAI & Deep Learning - Reaching the Pinnacle

Essays, 2019–2020

  1. Apr 2020Where AI Can Help Someone Buy a Home
  2. Mar 2020The Covid Toilet Paper Crisis Teaches Us How to Build a Better Future with AI
  3. Feb 2020Data = Money: Why Data-Driven Companies Need to Act like Banks
  4. Feb 2020Big Data & The Black Swan: How Management Can De-Risk AI
  5. Feb 2020Bracing for the Singularity: Contemplating the Ethical Impacts of AI Implementation
  6. Feb 2020What Venture Investors Teach Us About AI Decision-Making
  7. Jan 2020The Race for Personalization: 3 Steps to Get Ahead
  8. Jan 2020Lessons From Combat: What Navy SEALs Can Teach Us About AI Transformations
  9. Jan 2020Data Is the Fuel: Two Questions Before Any AI Project
  10. Dec 2019No Need to Cannonball: How to Wade into AI Innovation
  11. Dec 2019The Robot Next Door: Understanding the Impacts of Robotic Process Automation
  12. Dec 2019The Tortoise or The Hare: Exploring the Ideal Pace for AI Transformations
  13. Nov 2019Putting the Puzzle Pieces Together: A Brief Guide to Deep Learning
  14. Nov 2019Slow Down to Speed Up: How to Stop Losing Money your AI Transformation
  15. Nov 2019Using AI for Good: Autonomy, Ethics and Bias
  16. Nov 2019How Investors Can De-Risk an AI Investment
  17. Oct 2019Managers Search for Meaning: How to Interpret Machine Learning Results and Build Strategy
  18. Oct 2019How to Measure Success in Machine Learning Models
  19. Oct 2019Matching Algorithms to Business Problems in 4 Steps
  20. Oct 2019What it Means to ‘Clean’ Data and ‘Train’ Machine Learning Algorithms
  21. Sep 2019How Football Helps to Understand Bad Algorithms
  22. Sep 2019Politics and Machine Learning are not a Good Match
  23. Sep 2019What Do Marshmallows and Machine Learning Have in Common?
  24. Sep 2019How an Understanding of Machine Learning Helps Craft Better Strategy
  25. Sep 2019Why AI and Machine Learning Aren’t the Same Thing
  26. Aug 2019Getting Employees Ready for AI Transformation
  27. Aug 2019Can Someone Please Tell Me What AI Actually Is?
  28. Aug 2019The AI Translator: The Manager Every AI Team Needs