The AI Hierarchy: crafting a successful AI strategy from the ground up
Part I: Introducing the AI Strategy Framework
Itinerary
- Part I: Introducing the AI Strategy Framework (👈You’re here)
- Part II: Crafting a Compelling AI Product Vision and Narrative
- Part III: Data Collection - The Essence of AI
- Part IV: Ensuring Reliable and Accessible Storage
- Part V: Data Exploration and Transformation
- Part VI: Insights & Analysis - See the Unseen
- Part VII: Machine Learning - The Continuous Improvement Cycle
- Part VIII: AI & Deep Learning - Reaching the Pinnacle
From 2015 to 2017 I spent over one thousand hours studying for the Chartered Financial Analyst exams with eyes on becoming an investment banker. I passed the three exams across 18 months.
Then I quit.
The reason?
The long answer is in the twenty thousand words that make up this blog series. Each week over the next eight I’ll be releasing a new blog in the series to help explain why I threw away all those hours.
Although I had spent all those hours studying for the CFA exams to turn around and pursue a completely new industry, the time was not wasted. Within the endless textbook readings were many concepts foundational to data science.
From my early research into AI I could tell the topic was similar to the statistics and risk measurement techniques I had already mastered.
I decided to commit to a career in AI and applied to take a Master of Management in Artificial Intelligence at Queen’s University. This would allow me to blend the highly technical data science courses and the strategic business courses.
I could add value by understanding both the technology and its impact on the bottom line.
Since graduating from the Masters program I’ve worked with several companies across industries to craft AI strategies and implement them.
My focus is always on ensuring the technology delivers value to the business.
This blog series is my way of sharing the learnings, failures, and triumphs I’ve experienced along the way.
Turning AI Into Something Approachable
This series captures my AI Strategy Framework inspired by this Hackernoon article. By providing you with a tested framework, my hope is that you make fewer mistakes and are able to deliver value from AI technology to your organization.
The AI Strategy Framework is a pyramid where each layer contains a separate task. Each successful AI project will complete the layers one-by-one progressing from the bottom to the top. I’ve learned the hard way that it's not possible to skip steps and be successful.
This strategy will show you to walk before you run, while ensuring that your organization sees value from your AI strategy early and often.
Framework Overview
Each blog post will focus on a different layer of the pyramid and walk you through how to use the AI Strategy Framework to successfully get your AI projects delivered. Here is a preview of what you’ll see in the coming weeks:
- Part I: Introducing the AI Strategy Framework (👈You’re here)
- Part II: Crafting a Compelling AI Product Vision and Narrative
- Part III: Data Collection - The Essence of AI
- Part IV: Ensuring Reliable and Accessible Storage
- Part V: Data Exploration and Transformation
- Part VI: Insights & Analysis - See the Unseen
- Part VII: Machine Learning - The Continuous Improvement Cycle
- Part VIII: AI & Deep Learning - Reaching the Pinnacle
As we delve deeper into this series, you'll uncover:
- What is data and its importance to great business decisions and great AI algorithms
- How to use the cloud to make data storage easy
- Why cleaning up raw data into a curated and trusted form is like printing money
- The benefits of data visualization for business success
- How machine learning works and how to get your first model out
- And, the grand finale, where we make complex AI applications accessible
My goal is to equip you with the practical tools and insights needed to bring your AI aspirations to life. Success in AI doesn't come from magic. It comes from a good strategy and the relentless pursuit of improvement. I hope you join me and enjoy learning what it takes to deliver valuable AI solutions. It’s never too late to start - the AI revolution is only just getting started.
Need Help?
If you're seeking to unlock the full potential of AI within your organization but need help, we’re here for you. Our AI strategies are a no-nonsense way to derive value from AI technology. Reach out. Together we can turn your AI vision into reality.
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Mitchell Johnstone
Director of Strategy
Mitch is a Strategic AI leader with 7+ years of transforming businesses through high-impact AI/ML projects. He combines deep technical acumen with business strategy, exemplified in roles spanning AI product management to entrepreneurial ventures. His portfolio includes proven success in driving product development, leading cross-functional teams, and navigating complex enterprise software landscapes.