A CEO returns from a trade meeting excited about an machine learning computing tool demo she has seen. She believes the technology holds the potential for significant benefits for her company. She immediately calls a meeting of her IT and operational managers to discuss this opportunity. You are her CTO, so naturally you are in the meeting too. The CEO wants this technology assimilated into the IT in her sales force, and charges the group to make it so. What are the major issues to be faced? How would you initiate and manage the assimilation? What are some of the risks to be faced in the assimilation a re-engineering process? Be sure to address all relevant strategic and behavioral issues; cite at least seven theories in the support of your points.

ANS 1. Issues to be faced are :

1. Data collection : the most important step is the collection to data, which uses most of the time and the data needs to accurate at all times.

2. Less training data : the most common problem that can be faced is the less availability of the data that can be trained and used in ML.

3. Poor data quality : the other problem that can arise from the first one is when the data is not upto the mark and is of poor quality.

4. Unwanted features : there are many features that can make the whole process of implementation very slow and cumbersome , so these unwanted features can be a con in this ML.

5. Underfitting of the training data : this is the problem in which the model is Very simple to handle the type of data that has been collected and the complex data is not handled properly.

-- Initiate and manage the assimilation :

1. By gathering proper knowledge about the ML.

2. By deployment of various teams to do different tasks i.e. one to collect the data , other to get the idea about user needs .

3. By creating a working space that is open to new technology .

4. By giving training to the employees about the ML and how to use such devices.

5. Deployment of a maintenance team to ensure that the ML Device are working upto the mark

-- Risks to be faced :

There are mainly 3 which are :

1. Bad solutions to the problem alignment.

2. Higher cost of implementation and large time.

3. Possibility of any unexpected behaviour.

There are further main risk which are :

1. Strategy risk .

2. Financial risk .

3. Technical risk

4. Process risk

5. Explainability Risk

6. Regulatory Risk

7. Ethical Risk