AI-powered chatbots or virtual assistants can conduct initial pre-screening interviews with candidates, asking relevant questions and assessing their suitability for the role. This saves time for both employers and candidates.
Case Study: Unilever
Unilever recruits more than 30,000 people annually and processes around 1.8 million job applications globally. To manage this immense volume, Unilever partnered with Pymetrics to develop an AI-driven recruitment platform. Candidates are first assessed through a series of gamified tests that evaluate their aptitude, logic, and risk tolerance. These assessments are powered by machine learning algorithms that match candidates’ profiles with those of successful employees in similar roles.
The second stage involves an AI-analyzed video interview. Here, machine learning algorithms assess candidates based on their responses, body language, and speech patterns. This AI-driven process has allowed Unilever to reduce the time spent on interviews and candidate assessments by 70,000 person-hours annually. The system also provides feedback to all applicants, ensuring a transparent and fair process, and has significantly increased diversity in hiring by eliminating unconscious bias from the early stages of recruitment.
Case Study Bon Secours Mercy Health
Bon Secours Mercy Health is a major U.S. Catholic health system and the largest not-for-profit healthcare provider in Ireland. They hire about 20,000 staff from outside the organisation each year.
By using a AI tools, BSMH overhauled their recruitment process into a personalised, efficient, and seamless experience for job seekers.
Their job applicants can now easily find and apply for tailored opportunities, receive customised job alerts, and access 24/7 assistance through the chatbot. On the backend, talent teams can engage with leads effectively by segmenting them based on real-time data, ensuring the right message is delivered at the right time.
Through the use of AI, BSMH is seeking to differentiate itself in a crowded market, especially among sought-after candidates like registered nurses and other priority clinical pathways. Since implementing their new AI-based process, monitoring data show that  total external recruitment is up 28%, external nursing recruitment is up 31%, and early graduate recruitment is up 37%.