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10 steps to your very own AI project

Nov 25, 2021

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.

Click here to read the full story if you want to know more.

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