WorkWhile CEO Simon Khalaf predicts a labor shortage in the U.S. due to increased demand for employees. According to him, from July to August, the demand for workers on the platform rose by 22%, and by the end of September, it increased by another 14%. Currently, the company has more job openings than available workers. "This job apocalypse is an absolute myth," stated Khalaf. He added that there are no job losses associated with the application of AI. According to him, the U.S. is entering an era of acute labor shortage. Khalaf points out that AI infrastructure requires labor to build data centers, creating additional demand for labor professions such as forklift operators. He argues that shifting workers to data center construction projects may leave eCommerce companies and distribution centers competing for the same labor. Additionally, the shortage of labor resources is faced with existing employer expenses for replacing departing employees.
Khalaf noted that the average worker retention rate in the U.S. is approximately 45%, while in some segments served by WorkWhile, the turnover rate exceeds 100% per year. By applying AI, WorkWhile addresses this issue by matching workers with employers and using past experience to determine the potential for workers to return to previous assignments. The company demonstrates a task repeat rate of over 95% without the need to reassign the worker or employer to a new task. "What our AI systems do is connect the right people with the right job where they can excel and feel satisfaction," explained Khalaf. He associates this approach with the well-known saying: working at a job you love is not work.
WorkWhile also applies predictive models to account for attendance. The company's technology allows for assessing the likelihood of a worker showing up or canceling, enabling the rapid engagement of other workers through the on-demand market. Khalaf noted that WorkWhile has reduced short-term employee absences by more than half. Additionally, he compared workers' financial needs with WorkWhile's own working capital needs. Workers receive payment within 24 hours after completing a shift, while clients typically pay the company within 35 days. As a result, WorkWhile is forced to engage in borrowing to cover this gap. Workers face the challenge of bridging the gap between income and obligations, using credit cards and loans to cover gaps. Khalaf mentioned that WorkWhile uses internal resources to find additional shifts before debt arises. "If our AI models predict that workers won't have enough money to pay a bill, we send them to work or additional hours. This way, they can earn money, pay the bill, and avoid fees and interest," added Khalaf.
Since the launch of WorkWhile Money, 34% of workers have become debt-free. Meanwhile, about 40% of workers rely on the platform as their primary source of income. Currently, employers are asking WorkWhile to expand services beyond temporary workers, including the application of technology for full-time work. Khalaf noted that this creates challenges with connectivity, training, and readiness of flexible workers without the need for employers to retrain for each new task. WorkWhile provides training and certification for professions such as food handling and forklift operation, and uses AI agents to reduce training materials. The company aims not just to match workers with open shifts. Khalaf described a model that applies data for reassignments, attendance, training, and opportunities for workers to earn additional income.
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