• Written by Sonali Subhadarsini, Product Manager

On a typical Monday morning, the human resources team is already dealing with a multitude of queries from employees, ranging from questions about company policies to requests for time off, and the shift supervisor is checking the maintenance log to ensure everything is in order, while the category manager is comparing two suppliers to determine which one to use for the upcoming event, all of which can be time-consuming and take away from more strategic tasks, which is where AI productivity in the enterprise for human resources can help return time to people, but the question remains as to whether this time shows up anywhere measurable.

The difference between time saved and time redeployed

The introduction of AI-powered tools in human resources is often touted as a way to save time, but what this really means is that time is being redeployed, and this distinction is crucial, as simply saving time does not necessarily translate to increased productivity or efficiency, whereas redeploying time to more strategic tasks can have a significant impact on the organisation, for instance, the category manager can use the time saved from comparing suppliers to negotiate better deals, which can lead to cost savings for the organisation.

For example, a human resources team that uses AI to automate routine tasks such as answering frequently asked questions or processing employee data can free up time for more complex tasks such as talent development or succession planning, which can have a greater impact on the organisation, and this is where the shift supervisor can play a crucial role in ensuring that the time saved is being redeployed effectively.

Why self-reported time savings overstate the effect

One of the challenges in measuring the impact of AI on human resources productivity is that self-reported time savings can be unreliable, as people may overestimate the amount of time they save or underestimate the amount of time they spend on tasks, which can lead to inaccurate measurements of productivity gains, and this is particularly problematic when trying to determine whether the time saved is being redeployed effectively.

Furthermore, self-reported time savings can also be influenced by various biases, such as the desire to please management or the tendency to focus on short-term gains, which can further distort the accuracy of the measurements, and this is why it is essential to use more objective measures of productivity, such as repeat question volume or time to answer, to get a more accurate picture of the impact of AI on human resources productivity.

The human resources data this depends on

The effective deployment of AI in human resources depends on the availability and quality of various types of data, including policy library, headcount and skills, attrition history, and hiring plan, which can provide valuable insights into the organisation's human resources operations and help identify areas where AI can have the greatest impact, and this is where the category manager can play a key role in ensuring that the data is accurate and up-to-date.

For instance, having a comprehensive policy library can help AI-powered tools provide accurate and consistent answers to employee queries, while data on headcount and skills can help identify areas where training or recruitment may be needed, and this can be particularly useful for the shift supervisor who needs to ensure that the team has the necessary skills to perform their tasks effectively, and for more information on how to manage human resources data, you can visit our human resources page.

What it changes about

The introduction of AI in human resources can change the way the organisation approaches various tasks and operations, particularly in terms of policy questions and planning, which can often be based on impressions or intuition rather than data-driven insights, and this is where AI can help provide more accurate and objective information, enabling the human resources team to make more informed decisions, and this can be particularly useful for the category manager who needs to make decisions about suppliers or recruitment.

For example, AI-powered tools can help analyse data on employee queries and provide insights into the most common questions and areas of concern, which can help the human resources team develop more effective policies and procedures, and this can also help reduce the volume of repeat questions, freeing up time for more strategic tasks, and this is where the shift supervisor can play a crucial role in ensuring that the time saved is being redeployed effectively.

Measured with

The impact of AI on human resources productivity can be measured using various metrics, including repeat question volume, time to answer, and attrition by tenure, which can provide valuable insights into the effectiveness of AI-powered tools and help identify areas for improvement, and this is where the category manager can play a key role in ensuring that the metrics are accurate and relevant.

For instance, a decrease in repeat question volume can indicate that AI-powered tools are providing accurate and consistent answers to employee queries, while a reduction in time to answer can indicate that AI is helping to streamline human resources operations, and this can be particularly useful for the shift supervisor who needs to ensure that the team is working efficiently, and if you have any questions about how to measure the impact of AI on human resources productivity, you can contact us for more information.

What this does not do

While AI can have a significant impact on human resources productivity, it is not a panacea for all human resources challenges, and there are certain situations where AI may not be the best solution, such as in situations where human judgement and empathy are required, or where the data is incomplete or inaccurate, and this is where the human resources team needs to be careful in determining when to use AI and when to rely on human intuition and expertise.

Furthermore, AI is not a replacement for human resources staff, but rather a tool to augment and support their work, and this is where the shift supervisor and category manager can play a crucial role in ensuring that AI is used effectively and efficiently, and that the time saved is being redeployed to more strategic tasks, and this can help ensure that the organisation is getting the most out of its investment in AI, and that the human resources team is able to provide the best possible support to employees.