1. Formulate an Executive Strategy
A good strategy starts with disgruntled customers in mind, not technologies.
2. Identify and Prioritise Ideas
It is more productive for companies to look at A.I through the lens of business capabilities rather than technologies.
3. Ask the right questions about Data
Unique data, rather than cutting-edge modeling, is what creates a valuable A.I solution.
4. Perform the necessary Risk Assessments
Risk assessment are best performed by outside players.
5. Choose the relevant Method & Model
All models are wrong, but some are useful.
6. Make a BBP decision
BBP choices depend highly on both the executive strategy and the industry to which a company belongs.
7. Run performance checks
Beware of the “rage-to-conclude”.
8. Deploy the algorithm
Do not be afraid of redesigning workflows around the new solution.
9. Communicate both successes and failures
Under-hyping tends to be more productive than over-hyping.
10. Track Changes
The world changes a lot faster than you think. And an algorithm cannot see that.