7 Questions Executives Should Ask Before Starting Any AI Work

Photo by Khaled Ali on Unsplash

Executives struggle with deciding which AI work is feasible and which project should be prioritized over competing work. Here’s my list of 7 questions that executives should ask. The quality of these answer tell you a lot about the homework that the team has done.

1. Do we have a clear intention and problem statement, with clearly stated inputs/outputs and business goal that define success?
2. What is the opportunity cost: AI vs Non-AI vs BAU (not every problem is AI compatible)? what is the risk vs reward-matrix and the expected costs for the entire lifecycle (not just model development and deployment)?
3. Do we have ample, high quality, representative data? What is the data provenance? is this in line with our digital maturity? does our data architecture support this initiative?
4. Do we have a diverse team (ideally, the AI governance team but not every organization has an official oversight board) who has vetted this for ethical and user experience considerations?
5. Was there a ‘Design Thinking’ session in which we considered our assumptions, unknowns, layers of effects (unintended consequences)?
6. What’s the governance plan, pre-launch and post-launch?
7. How robust is the approach? What happens if things go wrong — do we have resources to test the model against attacks? are there safeguards in place?

Note that I did not include anything about the type of model, devops or deeply technical because as an executive you should delegate those to your experts.