Don't let your AI opportunities fail in adoption?

Some companies squander on AI/ML opportunities as they see them as technologies. Companies should start seeing AI/ML as an opportunity. An opportunity to automate predictions which can be used for steering business outcomes. Businesses should start looking at opportunities where it is worth to make a prediction and where historical data is available which can be used to learn and make a prediction. Companies use it for Sales forecasting, Customer churn, Employee attrition, Payment risk assessment, etc.

While companies should view AI/ML as an opportunity and adopt it for business application, due care should be taken to assess the impact before it is implemented else would lead to failure in adoption. Some healthcare companies have tried to automate part of the Radiologists' work only to realize in the end that the Radiologists are double checking the output produced from the AI application leading to double work. As a result, this leads to failure in adoption.

Carry out the below impact assessment before implementing an AI solution:

1. Perform an assessment to check how many tasks are impacted for a particular role (removed, changed, added). If there are too many (more than 1/3rd), then the risk is higher and hence proper change management would be critical.

2. Perform an assessment to check how many roles are impacted. If there is more than one, it would be a complex deployment and hence emphasis should be laid on handshakes between tasks performed by different roles.

3. Judge the willingness and ability to adopt the solution and check for barriers in both areas. More often, these are results of not involving the right people for the implementation. This can be addressed by conducting interviews well before the implementation starts.

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