Case study: Comparing human and agentic AI costs for recruitment operations

Recruitment operations provide a compelling case study for evaluating the economic trade-offs between human and agentic AI systems, but the ROI calculation depends critically on your current operational baseline. Organizations evaluating agentic AI investments often ask a fundamental question: "What if we simply optimize our existing human processes instead?" To address this directly, this analysis presents two distinct scenarios that bracket the range of human operational efficiency.

Scenario A models 45-minute curriculum vitae (CV) or resume screening times. Scenario B demonstrates optimized human operations at 15 minutes per application, which is a 66% efficiency improvement. For example, this improvement might be achieved through streamlined processes, experienced recruiters, or specialized tools.

By comparing identical agent system capabilities against these different human performance baselines, we reveal how existing process efficiency impacts ROI calculations, break-even timelines, and strategic implementation decisions. This dual-scenario approach serves multiple purposes. It prevents organizations from dismissing agentic AI by assuming process optimization alone is sufficient. It also helps organizations with already-efficient processes understand their specific economics. In addition, these scenarios highlight when non-financial advantages, such as 24/7 availability and scalability, become primary decision factors. Understanding these economic dynamics across different efficiency baselines enables organizations to make informed decisions about where and when to deploy agentic AI systems for maximum business impact.