Building the Case for AI in HR

I hope you're doing well. This week, I came across the Port Royal Logic, a 17th-century classic that demonstrates how breaking down ideas into clear, precise parts leads to more effective reasoning and communication. What struck me is how it tried to make logic almost quantitative—treating reasoning like something that could be measured, structured, and tested.

The same principle applies when examining the business case for AI in HR transformation.

I am attaching a paper that Draup developed along the lines of AI in HR.  This paper is built on a model company, ACME (A theoretical customer).  The main motivation of this paper is to showcase the working formulas of modeling AI impact, so that you can use this model to assess the impact in your company.  

For context, our ACME model customer is a mid-sized enterprise with ~5,000 employees and ~200 planned hires annually. But with attrition at 15% (~750 exits each year), HR is spending far more time backfilling lost talent than focusing on growth. They face:

• $45M Annual Cost of Attrition – Each of the 750 exits costs ~$60K in replacement and productivity loss.
• 45 Days to Hire – Vacancy delays alone cost ~$1.8M annually.
• 5,000 Monthly HR Queries – Draining over 5,000 hours of HR time each year.

By embedding AI across Talent Acquisition, Retention, and HR Service Delivery, ACME could:

• Cut time-to-hire by ~30%, saving ~$520K per year.
• Retain 100 additional employees annually, saving $6M+.
• Automate 80% of HR queries, freeing up 4,000+ hours.

Action:  This paper is meant to go beyond theory—it provides a practical framework you can adapt to your own context. By plugging in your company’s data, you can quickly quantify the value of AI in HR and build a strong, evidence-based case for transformation.