There is a boom in machine learning (ML) and artificial intelligence (AI) initiatives right now. Even the federal government and military are taking note. With the “new normal” of remote work, this boom is here to stay. If you’ve made the decision to explore ML and AI capabilities for an initiative or about to embark on a ML and AI product journey, this article roundup is for you.
The articles and links below are a summary of ML/AI delivery trends and best practices for executives, implementation, product and project managers. Topic headers include:
- What is Machine Learning?
- ML/AI Strategy
- Managing Machine Learning and AI Projects
- Use Case Studies
What is Machine Learning?
There is a lot of frightening jargon for ML/AI: supervised versus unsupervised learning, classification models, Random Forrest versus Conditional Inference algorithms etc. This article is a good starting point to describe ML/AI concepts. It’s a little crass (i.e. curse words) but the points are solid.
- Machine Learning 101: https://vas3k.com/blog/machine_learning/?ref=hn
- Artificial Intelligence 101: https://www.zdnet.com/article/what-is-ai-everything-you-need-to-know-about-artificial-intelligence/
Machine Learning and Artificial Intelligence Strategy
- How to Create a Data Strategy for Machine-Learning-Powered Artificial Intelligence by Gartner: https://www.gartner.com/en/doc/3734817-how-to-create-a-data-strategy-for-machine-learning-powered-artificial-intelligence
- Artificial Intelligence (AI) strategy: 3 tips for crafting yours: https://enterprisersproject.com/article/2020/7/artificial-intelligence-ai-strategy-3-tips
- 6 Steps to Implementing a Machine Learning Strategy by Google: https://cloud.withgoogle.com/build/data-analytics/new-report-6-steps-implementing-ml-strategy/
- How Your Organization Can Become AI Powered: https://www.clickz.com/how-your-organization-can-become-ai-powered/262306/
Managing Machine Learning and AI Projects
- The Dumb Reason Why Your AI Project Will Fail: Every technology project should start with the question, “Why will this effort fail?” in order to mitigate risks up front versus after the million dollar check has been written for the effort. I’ve seen first hand how planning for operations integration is rarely taken into account for a new digital innovation initiative. This article explains the pitfalls of that: https://hbr.org/2020/06/the-dumb-reason-your-ai-project-will-fail
- AI (Artificial Intelligence) Projects: Where To Start: https://www.forbes.com/sites/tomtaulli/2020/04/11/ai-artificial-intelligence-projects-where-to-start/#5a54339f1c11
- Managing Machine Learning Projects by AWS: This is my go-to guide when embarking on ML/AI projects. This article from AWS includes best practices for staffing ML/AI projects to assessing financial risk. https://d1.awsstatic.com/whitepapers/aws-managing-ml-projects.pdf
- Organizing Machine Learning Projects: Project Management Guidelines: https://www.jeremyjordan.me/ml-projects-guide/
- Bringing an AI Product to Market: https://www.oreilly.com/radar/bringing-an-ai-product-to-market/
- How to Build a Machine Learning Model in 7 Steps: A great companion to the AWS article. This is a step by step breakdown for ML/AI projects that Executive leaders can use to assess build out a ML model for their business problem. https://searchenterpriseai.techtarget.com/feature/How-to-build-a-machine-learning-model-in-7-steps
- Why Agile Methodologies Miss the Mark for AI/ML Projects: https://www.forbes.com/sites/cognitiveworld/2020/01/19/why-agile-methodologies-miss-the-mark-for-ai–ml-projects/#658735b321ea
- How to Manage AI Projects: From POV to Ready-to-Execute Solution: https://appinventiv.com/blog/ai-project-management/
- The Importance of Project Management for AI/ML Initiatives: https://www.techrepublic.com/article/how-project-managers-are-essential-to-ai-deployment/
- Cognitive Project Management for Artificial Intelligence Methodology: https://www.cognilytica.com/cpmai-methodology/
- Machine Learning Best Practices in Financial Services by AWS: Want to get real nerdy? This whitepaper from AWS details best security practices for Financial Services ML initiatives in Amazon’s SageMaker.
- Managing Bias and Risk in the AI Build Process by Harvard Business Review: https://hbr.org/2019/10/managing-bias-and-risk-at-every-step-of-the-ai-building-process
Use Case Studies
- Amazon’s ML/AI resource repository that includes business cases and how to best drive business value from ML/AI initiatives. https://aws.amazon.com/ai/resources/
- My First Year as a Project Manager for Artificial Intelligence: https://towardsdatascience.com/my-first-year-as-a-project-manager-for-artificial-intelligence-ai-16127a4a37c2
Published on August 14, 2020
Starr Corbin is the Founding Partner of Corbin Solutions Group. Follow her on LinkedIn and Twitter @StarrCorbin.