The state of AI adoption in talent

The adoption of talent-centric AI features is influenced by two primary factors: assumed compliance risk and perceived value. From a risk perspective, organizations are demanding algorithmic transparency, auditability, and assurance that they will not be exposed to liability. Despite this barrier, AI-driven capabilities that drive instant, positive value have gained the most traction. Applications of the technology for talent acquisition, including candidate self-scheduling and resume evaluation, were found to be particularly useful for organizations with high hiring volumes. For example, self-scheduling can virtually eliminate the one- to five-day timeframe typically associated with coordinating and scheduling interviews. Additionally, AI-enabled screening capabilities can reduce time spent evaluating resumes by more than 70 percent. In talent management, assistive capabilities for performance management can save managers 40 to 50 percent of their time spent on annual reviews, while improving the quality of employee-set goals. As agentic AI takes center stage in 2026, vendors’ ability to demonstrate outcomes and educate customers on the inner workings of AI investments will be key to driving value for customers and successfully differentiating in what has become a largely homogeneous market.