What is a benefit of data quality and transparency as it pertains to bias in generative AI?
What is a benefit of data quality and transparency as it pertains to bias in generative AI?
Data quality and transparency are essential in addressing bias in generative AI. While it is not possible to completely eliminate bias due to the complex nature of data and human intervention, high data quality and transparency help in identifying, understanding, and reducing the potential biases. This ensures that the generative AI system is more fair and reliable, thereby mitigating the chances of bias.
A business analyst (BA) wants to improve business by enhancing their sales processes and customer support.
Which AI applications should the BA use to meet their needs?
To enhance sales processes and customer support, a business analyst should use AI applications that include lead scoring, opportunity forecasting, and case classification. Lead scoring helps prioritize leads based on their potential to convert, opportunity forecasting anticipates future sales opportunities, and case classification organizes support cases to improve customer service efficiency.
How does AI within CRM help sales representatives better understand previous customer interactions?
AI within CRM helps sales representatives better understand previous customer interactions by providing call summaries. These summaries give insights into past conversations, highlighting key points and issues discussed, which aids in preparing for future engagements with the customer.
Why is it critical to consider privacy concerns when dealing with AI and CRM data?
Considering privacy concerns when dealing with AI and CRM data is critical because it ensures compliance with laws and regulations. Various laws and regulations, such as GDPR and CCPA, require organizations to handle personal data responsibly and protect individuals' privacy. Failure to comply with these regulations can lead to severe penalties and legal consequences. Therefore, prioritizing privacy helps organizations avoid legal issues and maintain trust with their customers.
A data quality expert at Cloud Kicks wants to ensure that each new contact contains at least an email address or phone number.
Which feature should they use to accomplish this?
To ensure that each new contact contains at least an email address or phone number, the data quality expert should use a validation rule. Validation rules help to enforce data integrity by ensuring that the data entered into the system meets specified criteria before allowing the user to save it. In this scenario, a validation rule can be created to check that either the email address or phone number field is populated, and throw an error if neither field is filled out.