• Written by Azhar Aliyar, Director

What happens when a category manager asks about employee data in our purchase order system, and how can we ensure that personally identifiable information, or PII, does not end up in places it should not reach, is a question that has sparked debate in our organisation, and the answer lies in understanding what PII in AI systems is, which refers to any data that can be used to identify an individual, such as names, addresses, or social security numbers, and how it is handled in our AI-powered query system, AsscherAi.

Definition of PII in AI systems

PII in AI systems, such as AsscherAi, refers to any data that can be used to identify an individual, including names, addresses, social security numbers, and other sensitive information, and it is essential to define it clearly to ensure that our organisation handles it correctly, and to do so, we must consider the various types of data that our AI system processes, including employee data, customer data, and supplier data, and determine which of these datasets contain PII.

The definition of PII is crucial because it helps us to identify the data that requires special handling and protection, and in our organisation, we have implemented strict policies and procedures to ensure that PII is handled correctly, including access controls, encryption, and regular audits, and we have also established a data governance team to oversee the handling of PII and ensure that it is compliant with relevant regulations, and for more information on our data governance policies, you can visit our website at home page.

Difference from other data types

PII is often confused with other types of data, such as business data or financial data, but it is distinct and requires special handling, and one of the main differences between PII and other data types is that PII is directly related to an individual, whereas business data or financial data may not be, and this distinction is essential to understand, as it helps us to determine which data requires special protection and handling.

For example, a shift supervisor may need to access employee data to manage schedules and payroll, but this data should be handled differently than business data, such as sales figures or inventory levels, and our AI system, AsscherAi, is designed to handle these different types of data correctly, and to provide access to authorised personnel only, and if you have any questions about our data handling policies, you can contact us at contact page.

Applications in a large organisation

In a large organisation, PII applies in various contexts, including human resources, customer service, and supply chain management, and it is essential to handle PII correctly in these contexts to ensure compliance with regulations and to protect individual privacy, and our organisation has implemented various measures to ensure that PII is handled correctly, including training programs for employees and regular audits of our data handling practices.

For instance, in our human resources department, we use AsscherAi to manage employee data, including PII, and we have implemented strict access controls to ensure that only authorised personnel can access this data, and we also use encryption to protect PII when it is transmitted or stored, and we have established a data governance team to oversee the handling of PII and ensure that it is compliant with relevant regulations.

In our customer service department, we also use AsscherAi to manage customer data, including PII, and we have implemented measures to ensure that customer PII is handled correctly, including access controls and encryption, and we also provide training to our customer service representatives on the importance of handling PII correctly.

Limitations of PII in AI systems

While PII in AI systems is essential for handling sensitive data correctly, it is not a solution for all data handling challenges, and it has limitations, such as the need for regular updates and maintenance to ensure that PII is handled correctly, and the potential for errors or breaches if PII is not handled correctly, and our organisation is aware of these limitations and has implemented measures to mitigate them.

For example, we have established a data governance team to oversee the handling of PII and ensure that it is compliant with relevant regulations, and we also provide regular training to our employees on the importance of handling PII correctly, and we have implemented strict access controls and encryption to protect PII when it is transmitted or stored.

When PII is the wrong choice

PII is not always the right solution for handling data, and there are cases where it may not be applicable or may even be counterproductive, such as when handling aggregate data or anonymised data, and in these cases, other data handling measures may be more appropriate, and our organisation is aware of these cases and has implemented alternative measures to handle data correctly.

For instance, when handling aggregate data, such as sales figures or inventory levels, PII may not be relevant, and other data handling measures, such as access controls and encryption, may be more appropriate, and our organisation has implemented these measures to ensure that aggregate data is handled correctly, and we have also established a data governance team to oversee the handling of aggregate data and ensure that it is compliant with relevant regulations.