As I was preparing a talk about my new book on AI Project Management, The AI Project Handbook, I thought I would put the lessons from the book into one single document. I realized I was really trying to define some AI Agile principles. I call the document the AI Agile Manifesto in honor of the 2001 Manifesto for Agile Software Development (written twenty years ago!). Have a look and tell me what you think. I will revise it based on your comments and suggestions.
The AI Agile Manifesto
- You need to know what you want to achieve with AI. There is a trade-off between feasibility and business impact.
- The organization has to be committed to the AI project.
- The AI team leader needs to be an effective manager and a leader with a shared vision of AI.
- Design thinking and Agile are valuable tools. Be laser-focused on the to-do-list to control the scope, cost, and schedule of the AI project.
- You need to know all the factors that can influence the AI project.
- The AI project needs to leverage and be consistent with all the organizational process assets.
- An AI project needs great people, models, and data.
- AI quality is not only about model and software quality but also about people and data.
- AI risk management requires a constant risk assessment, a risk strategy, and Human-in-the-loop.
- You need to involve all the stakeholders and have a clear communication plan, especially when things go wrong.
- You need to identify, understand and address the ethical concerns caused by AI.
- Agile for AI requires a specific approach with longer cycles and more exploration.
