• Written by Muhammed Abdulla NC, CEO

The decision to allocate budget to an AI deployment in human resources is typically made by a department head, who currently bases it on rough estimates of the cost of the AI model itself, without considering where the actual spend accumulates. This judgement is defended by the fact that the majority of the budget is often consumed by integration and data work, rather than the model's licensing fees.

Integration and data work as the dominant line

The cost of integrating an AI system with existing human resources systems, such as payroll and performance management software, can be substantial. A HR manager, for example, may need to work with the IT department to ensure that the AI system can access and process the relevant data, which can be a time-consuming and labour-intensive process. This work is essential to the success of the AI deployment, but it is often overlooked when estimating the total cost of the project.

A significant portion of the budget may also be spent on data preparation, including data cleaning, data transformation, and data loading. This work is necessary to ensure that the AI system has access to high-quality data, which is essential for accurate and reliable results. The data preparation process can be complex and time-consuming, requiring significant resources and expertise.

Run cost against query volume

The run cost of an AI system in human resources is often directly related to the volume of queries it receives. A system that is designed to answer frequent and complex queries, such as those related to employee benefits or performance management, may require more powerful hardware and more advanced software, which can increase the run cost. In contrast, a system that is designed to answer simple and infrequent queries, such as those related to employee contact information, may require less powerful hardware and less advanced software, which can reduce the run cost.

A category manager, for example, may use an AI system to compare the costs and benefits of different employee benefits packages, and the system may need to process a large volume of queries to provide accurate and reliable results. In this case, the run cost of the system would be directly related to the volume of queries it receives, and the category manager would need to carefully consider the cost-benefit analysis of the system to ensure that it is providing value to the organisation.

The cost of a wrong answer nobody caught

One of the most significant costs of an AI system in human resources is the cost of a wrong answer that nobody catches. If an AI system provides an incorrect answer to a query, and the error is not detected, it can have serious consequences for the organisation, including financial losses, reputational damage, and legal liability. The cost of a wrong answer can be difficult to estimate, but it is essential to consider it when evaluating the total cost of an AI deployment.

A shift supervisor, for example, may use an AI system to determine the eligibility of an employee for a promotion, and if the system provides an incorrect answer, it could result in an unfair or discriminatory decision. In this case, the cost of the wrong answer could be substantial, and the organisation would need to carefully consider the risks and benefits of using an AI system for this type of decision.

Attributing spend to a process rather than a model

When evaluating the cost of an AI deployment in human resources, it is essential to attribute the spend to the process rather than the model. This means considering the cost of the entire process, including data preparation, integration, and maintenance, rather than just the cost of the AI model itself. By taking a more holistic approach to cost estimation, organisations can get a more accurate picture of the total cost of ownership and make more informed decisions about their AI deployments.

For more information on how to attribute spend to a process, organisations can visit our human resource page, which provides guidance and resources on how to implement AI systems in human resources. Additionally, organisations can contact us directly to discuss their specific needs and requirements, and to get more information on how to get the most out of their AI deployments, by visiting our contact us page.

When AI is the wrong choice

While AI can be a powerful tool in human resources, there are certain situations where it may not be the best choice. For example, if an organisation has a simple and well-defined process that does not require complex decision-making or data analysis, it may be more cost-effective to use a traditional software solution rather than an AI system. Additionally, if an organisation has limited data or limited resources, it may be more difficult to implement and maintain an AI system, and a traditional software solution may be a better option.

In these situations, organisations should carefully consider their options and choose the solution that best meets their needs and requirements. By taking a careful and considered approach to AI deployment, organisations can ensure that they are getting the most out of their investment and achieving their desired outcomes.